Ron Dror
Cheriton Family Professor and Professor, by courtesy, of Structural Biology and of Molecular & Cellular Physiology
Computer Science
Bio
Ron Dror is the Cheriton Family Professor of Computer Science in the Stanford Artificial Intelligence Lab. Dr. Dror leads a research group that uses molecular simulation and machine learning to elucidate biomolecular structure, dynamics, and function, and to guide the development of more effective medicines. He collaborates extensively with experimentalists in both academia and industry.
Before moving to Stanford, Dr. Dror served as second-in-command of D. E. Shaw Research, a hundred-person company, having joined as its first hire. He designed computer hardware, software, and algorithms that accelerate molecular dynamics simulations by orders of magnitude, and applied these simulations to the study of protein function, protein folding, and protein-drug interactions.
Dr. Dror earned a PhD in Electrical Engineering and Computer Science at MIT, where he developed machine learning methods for computer vision and genomics. He earned an MPhil in Biological Sciences as a Churchill Scholar at the University of Cambridge, as well as undergraduate degrees in Mathematics and in Electrical and Computer Engineering at Rice University, summa cum laude. He has been awarded a Fulbright Scholarship and fellowships from the National Science Foundation, the Department of Defense, and the Whitaker Foundation, as well as two Gordon Bell Prizes and several Best Paper awards. His work has been highlighted by Science as a top-10 breakthrough of the year.
Academic Appointments
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Professor, Computer Science
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Professor (By courtesy), Molecular & Cellular Physiology
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Professor (By courtesy), Structural Biology
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Member, Bio-X
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Faculty Affiliate, Institute for Human-Centered Artificial Intelligence (HAI)
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Faculty Fellow, Sarafan ChEM-H
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Member, Wu Tsai Neurosciences Institute
Honors & Awards
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Cheriton Family Professorship, Stanford University (2023)
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Best Paper Award, Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track (2021)
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Ravi Faculty Scholar, Stanford University (2018)
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Gordon Bell Prize (Performance), ACM (2014)
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Best Paper Award, International Parallel and Distributed Processing Symposium (2013)
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Best Paper Award, ACM/IEEE Conference on Supercomputing (SC11) (2011)
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Top 10 Breakthroughs of the Year, Science Magazine (2010)
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Best Paper Award, ACM/IEEE Conference on Supercomputing (SC09) (2009)
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Gordon Bell Prize (Special Achievement), ACM (2009)
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Profiled in feature on “EECS Alums: Major Players and Thinkers", MIT Department of Electrical Engineering and Computer Science (2009)
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Best Paper Award, ACM/IEEE Conference on Supercomputing (SC06) (2006)
Current Research and Scholarly Interests
My lab’s research focuses on computational biology, with an emphasis on 3D molecular structure. We combine two approaches: (1) Bottom-up: given the basic physics governing atomic interactions, use simulations to predict molecular behavior; (2) Top-down: given experimental data, use machine learning to predict molecular structures and properties. We collaborate closely with experimentalists and apply our methods to the discovery of safer, more effective drugs.
2024-25 Courses
- Computational Biology: Structure and Organization of Biomolecules and Cells
BIOE 279, BIOMEDIN 279, BIOPHYS 279, CME 279, CS 279 (Aut) - Seminar in Artificial Intelligence in Healthcare
CS 522 (Aut) -
Independent Studies (21)
- Advanced Reading and Research
CS 499 (Aut, Win, Spr) - Advanced Reading and Research
CS 499P (Aut, Win, Spr) - Curricular Practical Training
APPPHYS 291 (Aut, Win, Spr) - Curricular Practical Training
CS 390A (Aut, Win, Spr) - Curricular Practical Training
CS 390B (Aut, Win, Spr) - Directed Investigation
BIOE 392 (Aut, Win, Spr) - Directed Reading and Research
BIOMEDIN 299 (Aut, Win, Spr, Sum) - Directed Reading in Biophysics
BIOPHYS 399 (Aut, Win, Spr, Sum) - Directed Reading in Neurosciences
NEPR 299 (Aut, Win, Spr, Sum) - Directed Study
BIOE 391 (Aut, Win, Spr) - Graduate Research
BIOPHYS 300 (Aut, Win, Spr, Sum) - Independent Project
CS 399 (Aut, Win, Spr) - Independent Project
CS 399P (Aut, Win, Spr) - Independent Work
CS 199 (Aut, Win, Spr) - Independent Work
CS 199P (Aut, Win, Spr) - Medical Scholars Research
BIOMEDIN 370 (Aut, Win, Spr, Sum) - Part-time Curricular Practical Training
CS 390D (Aut, Win, Spr) - Ph.D. Research
CME 400 (Aut, Win, Spr) - Research
PHYSICS 490 (Aut, Win, Spr) - Senior Project
CS 191 (Aut, Win, Spr) - Writing Intensive Senior Research Project
CS 191W (Aut, Win, Spr)
- Advanced Reading and Research
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Prior Year Courses
2023-24 Courses
- Computational Biology: Structure and Organization of Biomolecules and Cells
BIOE 279, BIOMEDIN 279, BIOPHYS 279, CME 279, CS 279 (Aut) - Seminar in Artificial Intelligence in Healthcare
CS 522 (Aut)
2022-23 Courses
- Computational Biology: Structure and Organization of Biomolecules and Cells
BIOE 279, BIOMEDIN 279, BIOPHYS 279, CME 279, CS 279 (Aut) - Computational Biology: Structure of Biomolecules
OSPMADRD 70 (Win)
2021-22 Courses
- Computational Biology: Structure and Organization of Biomolecules and Cells
BIOE 279, BIOMEDIN 279, BIOPHYS 279, CME 279, CS 279 (Aut) - Seminar in Artificial Intelligence in Healthcare
CS 522 (Aut)
- Computational Biology: Structure and Organization of Biomolecules and Cells
Stanford Advisees
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Doctoral Dissertation Reader (AC)
Anusri Pampari -
Postdoctoral Faculty Sponsor
Yuxuan Zhuang -
Doctoral Dissertation Advisor (AC)
EJ Fine, Masha Karelina, Rohan Koodli, Briana Sobecks -
Master's Program Advisor
Shreya D'Souza, Joseph Dehoney, Poojit Hegde, Aaron Jin, Brent Ju, Aakriti Lakshmanan, Michael Maffezzoli, Kenan Ye -
Doctoral Dissertation Co-Advisor (AC)
Jessica Karaguesian, Aviv Korman -
Doctoral (Program)
Ayush Pandit, Daniel Richman
Graduate and Fellowship Programs
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Biomedical Informatics (Phd Program)
All Publications
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Geometric Deep Learning for Structure-Based Ligand Design.
ACS central science
2023; 9 (12): 2257-2267
Abstract
A pervasive challenge in drug design is determining how to expand a ligand-a small molecule that binds to a target biomolecule-in order to improve various properties of the ligand. Adding single chemical groups, known as fragments, is important for lead optimization tasks, and adding multiple fragments is critical for fragment-based drug design. We have developed a comprehensive framework that uses machine learning and three-dimensional protein-ligand structures to address this challenge. Our method, FRAME, iteratively determines where on a ligand to add fragments, selects fragments to add, and predicts the geometry of the added fragments. On a comprehensive benchmark, FRAME consistently improves predicted affinity and selectivity relative to the initial ligand, while generating molecules with more drug-like chemical properties than docking-based methods currently in widespread use. FRAME learns to accurately describe molecular interactions despite being given no prior information on such interactions. The resulting framework for quality molecular hypothesis generation can be easily incorporated into the workflows of medicinal chemists for diverse tasks, including lead optimization, fragment-based drug discovery, and de novo drug design.
View details for DOI 10.1021/acscentsci.3c00572
View details for PubMedID 38161364
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Geometric deep learning of RNA structure.
Science (New York, N.Y.)
2021; 373 (6558): 1047-1051
Abstract
RNA molecules adopt three-dimensional structures that are critical to their function and of interest in drug discovery. Few RNA structures are known, however, and predicting them computationally has proven challenging. We introduce a machine learning approach that enables identification of accurate structural models without assumptions about their defining characteristics, despite being trained with only 18 known RNA structures. The resulting scoring function, the Atomic Rotationally Equivariant Scorer (ARES), substantially outperforms previous methods and consistently produces the best results in community-wide blind RNA structure prediction challenges. By learning effectively even from a small amount of data, our approach overcomes a major limitation of standard deep neural networks. Because it uses only atomic coordinates as inputs and incorporates no RNA-specific information, this approach is applicable to diverse problems in structural biology, chemistry, materials science, and beyond.
View details for DOI 10.1126/science.abe5650
View details for PubMedID 34446608
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How GPCR Phosphorylation Patterns Orchestrate Arrestin-Mediated Signaling.
Cell
2020
Abstract
Binding of arrestin to phosphorylated G-protein-coupled receptors (GPCRs) controls many aspects of cell signaling. The number and arrangement of phosphates may vary substantially for a given GPCR, and different phosphorylation patterns trigger different arrestin-mediated effects. Here, we determine how GPCR phosphorylation influences arrestin behavior by using atomic-level simulations and site-directed spectroscopy to reveal the effects of phosphorylation patterns on arrestin binding and conformation. We find that patterns favoring binding differ from those favoring activation-associated conformational change. Both binding and conformation depend more on arrangement of phosphates than on their total number, with phosphorylation at different positions sometimes exerting opposite effects. Phosphorylation patterns selectively favor a wide variety of arrestin conformations, differently affecting arrestin sites implicated in scaffolding distinct signaling proteins. We also reveal molecular mechanisms of these phenomena. Our work reveals the structural basis for the long-standing "barcode" hypothesis and has important implications for design of functionally selective GPCR-targeted drugs.
View details for DOI 10.1016/j.cell.2020.11.014
View details for PubMedID 33296703
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Molecular mechanism of biased signaling in a prototypical G protein-coupled receptor.
Science (New York, N.Y.)
2020; 367 (6480): 881–87
Abstract
Biased signaling, in which different ligands that bind to the same G protein-coupled receptor preferentially trigger distinct signaling pathways, holds great promise for the design of safer and more effective drugs. Its structural mechanism remains unclear, however, hampering efforts to design drugs with desired signaling profiles. Here, we use extensive atomic-level molecular dynamics simulations to determine how arrestin bias and G protein bias arise at the angiotensin II type 1 receptor. The receptor adopts two major signaling conformations, one of which couples almost exclusively to arrestin, whereas the other also couples effectively to a G protein. A long-range allosteric network allows ligands in the extracellular binding pocket to favor either of the two intracellular conformations. Guided by this computationally determined mechanism, we designed ligands with desired signaling profiles.
View details for DOI 10.1126/science.aaz0326
View details for PubMedID 32079767
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Molecular mechanism of GPCR-mediated arrestin activation
NATURE
2018; 557 (7705): 452-+
Abstract
Despite intense interest in discovering drugs that cause G-protein-coupled receptors (GPCRs) to selectively stimulate or block arrestin signalling, the structural mechanism of receptor-mediated arrestin activation remains unclear1,2. Here we reveal this mechanism through extensive atomic-level simulations of arrestin. We find that the receptor's transmembrane core and cytoplasmic tail-which bind distinct surfaces on arrestin-can each independently stimulate arrestin activation. We confirm this unanticipated role of the receptor core, and the allosteric coupling between these distant surfaces of arrestin, using site-directed fluorescence spectroscopy. The effect of the receptor core on arrestin conformation is mediated primarily by interactions of the intracellular loops of the receptor with the arrestin body, rather than the marked finger-loop rearrangement that is observed upon receptor binding. In the absence of a receptor, arrestin frequently adopts active conformations when its own C-terminal tail is disengaged, which may explain why certain arrestins remain active long after receptor dissociation. Our results, which suggest that diverse receptor binding modes can activate arrestin, provide a structural foundation for the design of functionally selective ('biased') GPCR-targeted ligands with desired effects on arrestin signalling.
View details for PubMedID 29720655
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Signaling Modulation Mediated by Ligand Water Interactions with the Sodium Site at μOR.
ACS central science
2024; 10 (8): 1490-1503
Abstract
The mu opioid receptor (μOR) is a target for clinically used analgesics. However, adverse effects, such as respiratory depression and physical dependence, necessitate the development of alternative treatments. Recently we reported a novel strategy to design functionally selective opioids by targeting the sodium binding allosteric site in μOR with a supraspinally active analgesic named C6guano. Presently, to improve systemic activity of this ligand, we used structure-based design, identifying a new ligand named RO76 where the flexible alkyl linker and polar guanidine guano group is swapped with a benzyl alcohol, and the sodium site is targeted indirectly through waters. A cryoEM structure of RO76 bound to the μOR-Gi complex confirmed that RO76 interacts with the sodium site residues through a water molecule, unlike C6guano which engages the sodium site directly. Signaling assays coupled with APEX based proximity labeling show binding in the sodium pocket modulates receptor efficacy and trafficking. In mice, RO76 was systemically active in tail withdrawal assays and showed reduced liabilities compared to those of morphine. In summary, we show that targeting water molecules in the sodium binding pocket may be an avenue to modulate signaling properties of opioids, and which may potentially be extended to other G-protein coupled receptors where this site is conserved.
View details for DOI 10.1021/acscentsci.4c00525
View details for PubMedID 39220695
View details for PubMedCentralID PMC11363324
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The Art and Science of Molecular Docking.
Annual review of biochemistry
2024
Abstract
Molecular docking has become an essential part of a structural biologist's and medicinal chemist's toolkits. Given a chemical compound and the three-dimensional structure of a molecular target-for example, a protein-docking methods fit the compound into the target, predicting the compound's bound structure and binding energy. Docking can be used to discover novel ligands for a target by screening large virtual compound libraries. Docking can also provide a useful starting point for structure-based ligand optimization or for investigating a ligand's mechanism of action. Advances in computational methods, including both physics-based and machine learning approaches, as well as in complementary experimental techniques, are making docking an even more powerful tool. We review how docking works and how it can drive drug discovery and biological research. We also describe its current limitations and ongoing efforts to overcome them.
View details for DOI 10.1146/annurev-biochem-030222-120000
View details for PubMedID 38594926
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CryoEM structures of the human CLC-2 voltage-gated chloride channel reveal a ball-and-chain gating mechanism.
eLife
2024; 12
Abstract
CLC-2 is a voltage-gated chloride channel that contributes to electrical excitability and ion homeostasis in many different tissues. Among the nine mammalian CLC homologs, CLC-2 is uniquely activated by hyperpolarization, rather than depolarization, of the plasma membrane. The molecular basis for the divergence in polarity of voltage gating among closely related homologs has been a long-standing mystery, in part because few CLC channel structures are available. Here, we report cryoEM structures of human CLC-2 at 2.46 - 2.76 Å, in the presence and absence of the selective inhibitor AK-42. AK-42 binds within the extracellular entryway of the Cl--permeation pathway, occupying a pocket previously proposed through computational docking studies. In the apo structure, we observed two distinct conformations involving rotation of one of the cytoplasmic C-terminal domains (CTDs). In the absence of CTD rotation, an intracellular N-terminal 15-residue hairpin peptide nestles against the TM domain to physically occlude the Cl--permeation pathway. This peptide is highly conserved among species variants of CLC-2 but is not present in other CLC homologs. Previous studies suggested that the N-terminal domain of CLC-2 influences channel properties via a "ball-and-chain" gating mechanism, but conflicting data cast doubt on such a mechanism, and thus the structure of the N-terminal domain and its interaction with the channel has been uncertain. Through electrophysiological studies of an N-terminal deletion mutant lacking the 15-residue hairpin peptide, we support a model in which the N-terminal hairpin of CLC-2 stabilizes a closed state of the channel by blocking the cytoplasmic Cl--permeation pathway.
View details for DOI 10.7554/eLife.90648
View details for PubMedID 38345841
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GPR161 structure uncovers the redundant role of sterol-regulated ciliary cAMP signaling in the Hedgehog pathway.
Nature structural & molecular biology
2024
Abstract
The orphan G protein-coupled receptor (GPCR) GPR161 plays a central role in development by suppressing Hedgehog signaling. The fundamental basis of how GPR161 is activated remains unclear. Here, we determined a cryogenic-electron microscopy structure of active human GPR161 bound to heterotrimeric Gs. This structure revealed an extracellular loop 2 that occupies the canonical GPCR orthosteric ligand pocket. Furthermore, a sterol that binds adjacent to transmembrane helices 6 and 7 stabilizes a GPR161 conformation required for Gs coupling. Mutations that prevent sterol binding to GPR161 suppress Gs-mediated signaling. These mutants retain the ability to suppress GLI2 transcription factor accumulation in primary cilia, a key function of ciliary GPR161. By contrast, a protein kinase A-binding site in the GPR161 C terminus is critical in suppressing GLI2 ciliary accumulation. Our work highlights how structural features of GPR161 interface with the Hedgehog pathway and sets a foundation to understand the role of GPR161 function in other signaling pathways.
View details for DOI 10.1038/s41594-024-01223-8
View details for PubMedID 38326651
View details for PubMedCentralID 8378848
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How accurately can one predict drug binding modes using AlphaFold models?
eLife
2023; 12
Abstract
Computational prediction of protein structure has been pursued intensely for decades, motivated largely by the goal of using structural models for drug discovery. Recently developed machine-learning methods such as AlphaFold 2 (AF2) have dramatically improved protein structure prediction, with reported accuracy approaching that of experimentally determined structures. To what extent do these advances translate to an ability to predict more accurately how drugs and drug candidates bind to their target proteins? Here, we carefully examine the utility of AF2 protein structure models for predicting binding poses of drug-like molecules at the largest class of drug targets, the G-protein-coupled receptors. We find that AF2 models capture binding pocket structures much more accurately than traditional homology models, with errors nearly as small as differences between structures of the same protein determined experimentally with different ligands bound. Strikingly, however, the accuracy of ligand-binding poses predicted by computational docking to AF2 models is not significantly higher than when docking to traditional homology models and is much lower than when docking to structures determined experimentally without these ligands bound. These results have important implications for all those who might use predicted protein structures for drug discovery.
View details for DOI 10.7554/eLife.89386
View details for PubMedID 38131311
View details for PubMedCentralID PMC10746139
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Xanomeline displays concomitant orthosteric and allosteric binding modes at the M4 mAChR.
Nature communications
2023; 14 (1): 5440
Abstract
The M4 muscarinic acetylcholine receptor (M4 mAChR) has emerged as a drug target of high therapeutic interest due to its expression in regions of the brain involved in the regulation of psychosis, cognition, and addiction. The mAChR agonist, xanomeline, has provided significant improvement in the Positive and Negative Symptom Scale (PANSS) scores in a Phase II clinical trial for the treatment of patients suffering from schizophrenia. Here we report the active state cryo-EM structure of xanomeline bound to the human M4 mAChR in complex with the heterotrimeric Gi1 transducer protein. Unexpectedly, two molecules of xanomeline were found to concomitantly bind to the monomeric M4 mAChR, with one molecule bound in the orthosteric (acetylcholine-binding) site and a second molecule in an extracellular vestibular allosteric site. Molecular dynamic simulations supports the structural findings, and pharmacological validation confirmed that xanomeline acts as a dual orthosteric and allosteric ligand at the human M4 mAChR. These findings provide a basis for further understanding xanomeline's complex pharmacology and highlight the myriad of ways through which clinically relevant ligands can bind to and regulate GPCRs.
View details for DOI 10.1038/s41467-023-41199-5
View details for PubMedID 37673901
View details for PubMedCentralID PMC10482975
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Structural basis for ion selectivity in potassium-selective channelrhodopsins.
Cell
2023
Abstract
KCR channelrhodopsins (K+-selective light-gated ion channels) have received attention as potential inhibitory optogenetic tools but more broadly pose a fundamental mystery regarding how their K+ selectivity is achieved. Here, we present 2.5-2.7 Å cryo-electron microscopy structures of HcKCR1 and HcKCR2 and of a structure-guided mutant with enhanced K+ selectivity. Structural, electrophysiological, computational, spectroscopic, and biochemical analyses reveal a distinctive mechanism for K+ selectivity; rather than forming the symmetrical filter of canonical K+ channels achieving both selectivity and dehydration, instead, three extracellular-vestibule residues within each monomer form a flexible asymmetric selectivity gate, while a distinct dehydration pathway extends intracellularly. Structural comparisons reveal a retinal-binding pocket that induces retinal rotation (accounting for HcKCR1/HcKCR2 spectral differences), and design of corresponding KCR variants with increased K+ selectivity (KALI-1/KALI-2) provides key advantages for optogenetic inhibition in vitro and in vivo. Thus, discovery of a mechanism for ion-channel K+ selectivity also provides a framework for next-generation optogenetics.
View details for DOI 10.1016/j.cell.2023.08.009
View details for PubMedID 37652010
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Bias profile and efficacy-driven selectivity of xanomeline at the muscarinic acetylcholine receptor family
WILEY. 2023: 666-667
View details for Web of Science ID 001043027400529
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A positively tuned voltage indicator for extended electrical recordings in the brain.
Nature methods
2023; 20 (7): 1104-1113
Abstract
Genetically encoded voltage indicators (GEVIs) enable optical recording of electrical signals in the brain, providing subthreshold sensitivity and temporal resolution not possible with calcium indicators. However, one- and two-photon voltage imaging over prolonged periods with the same GEVI has not yet been demonstrated. Here, we report engineering of ASAP family GEVIs to enhance photostability by inversion of the fluorescence-voltage relationship. Two of the resulting GEVIs, ASAP4b and ASAP4e, respond to 100-mV depolarizations with ≥180% fluorescence increases, compared with the 50% fluorescence decrease of the parental ASAP3. With standard microscopy equipment, ASAP4e enables single-trial detection of spikes in mice over the course of minutes. Unlike GEVIs previously used for one-photon voltage recordings, ASAP4b and ASAP4e also perform well under two-photon illumination. By imaging voltage and calcium simultaneously, we show that ASAP4b and ASAP4e can identify place cells and detect voltage spikes with better temporal resolution than commonly used calcium indicators. Thus, ASAP4b and ASAP4e extend the capabilities of voltage imaging to standard one- and two-photon microscopes while improving the duration of voltage recordings.
View details for DOI 10.1038/s41592-023-01913-z
View details for PubMedID 37429962
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Structural basis for activation of CB1 by an endocannabinoid analog.
Nature communications
2023; 14 (1): 2672
Abstract
Endocannabinoids (eCBs) are endogenous ligands of the cannabinoid receptor 1 (CB1), a G protein-coupled receptor that regulates a number of therapeutically relevant physiological responses. Hence, understanding the structural and functional consequences of eCB-CB1 interactions has important implications for designing effective drugs targeting this receptor. To characterize the molecular details of eCB interaction with CB1, we utilized AMG315, an analog of the eCB anandamide to determine the structure of the AMG315-bound CB1 signaling complex. Compared to previous structures, the ligand binding pocket shows some differences. Using docking, molecular dynamics simulations, and signaling assays we investigated the functional consequences of ligand interactions with the "toggle switch" residues F2003.36 and W3566.48. Further, we show that ligand-TM2 interactions drive changes to residues on the intracellular side of TM2 and are a determinant of efficacy in activating G protein. These intracellular TM2 rearrangements are unique to CB1 and are exploited by a CB1-specific allosteric modulator.
View details for DOI 10.1038/s41467-023-37864-4
View details for PubMedID 37160876
View details for PubMedCentralID PMC10169858
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Protein model quality assessment using rotation-equivariant transformations on point clouds.
Proteins
2023
Abstract
Machine learning research concerning protein structure has seen a surge in popularity over the last years with promising advances for basic science and drug discovery. Working with macromolecular structure in a machine learning context requires an adequate numerical representation, and researchers have extensively studied representations such as graphs, discretized 3D grids, and distance maps. As part of CASP14, we explored a new and conceptually simple representation in a blind experiment: atoms as points in 3D, each with associated features. These features-initially just the basic element type of each atom-are updated through a series of neural network layers featuring rotation-equivariant convolutions. Starting from all atoms, we further aggregate information at the level of alpha carbons before making a prediction at the level of the entire protein structure. We find that this approach yields competitive results in protein model quality assessment despite its simplicity and despite the fact that it incorporates minimal prior information and is trained on relatively little data. Its performance and generality are particularly noteworthy in an era where highly complex, customized machine learning methods such as AlphaFold 2 have come to dominate protein structure prediction.
View details for DOI 10.1002/prot.26494
View details for PubMedID 37158708
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Constrained catecholamines gain β2AR selectivity through allosteric effects on pocket dynamics.
Nature communications
2023; 14 (1): 2138
Abstract
G protein-coupled receptors (GPCRs) within the same subfamily often share high homology in their orthosteric pocket and therefore pose challenges to drug development. The amino acids that form the orthosteric binding pocket for epinephrine and norepinephrine in the β1 and β2 adrenergic receptors (β1AR and β2AR) are identical. Here, to examine the effect of conformational restriction on ligand binding kinetics, we synthesized a constrained form of epinephrine. Surprisingly, the constrained epinephrine exhibits over 100-fold selectivity for the β2AR over the β1AR. We provide evidence that the selectivity may be due to reduced ligand flexibility that enhances the association rate for the β2AR, as well as a less stable binding pocket for constrained epinephrine in the β1AR. The differences in the amino acid sequence of the extracellular vestibule of the β1AR allosterically alter the shape and stability of the binding pocket, resulting in a marked difference in affinity compared to the β2AR. These studies suggest that for receptors containing identical binding pocket residues, the binding selectivity may be influenced in an allosteric manner by surrounding residues, like those of the extracellular loops (ECLs) that form the vestibule. Exploiting these allosteric influences may facilitate the development of more subtype-selective ligands for GPCRs.
View details for DOI 10.1038/s41467-023-37808-y
View details for PubMedID 37059717
View details for PubMedCentralID PMC10104803
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Molecular mechanism of biased signaling at the kappa opioid receptor.
Nature communications
2023; 14 (1): 1338
Abstract
The κ-opioid receptor (KOR) has emerged as an attractive drug target for pain management without addiction, and biased signaling through particular pathways of KOR may be key to maintaining this benefit while minimizing side-effect liabilities. As for most G protein-coupled receptors (GPCRs), however, the molecular mechanisms of ligand-specific signaling at KOR have remained unclear. To better understand the molecular determinants of KOR signaling bias, we apply structure determination, atomic-level molecular dynamics (MD) simulations, and functional assays. We determine a crystal structure of KOR bound to the G protein-biased agonist nalfurafine, the first approved KOR-targeting drug. We also identify an arrestin-biased KOR agonist, WMS-X600. Using MD simulations of KOR bound to nalfurafine, WMS-X600, and a balanced agonist U50,488, we identify three active-state receptor conformations, including one that appears to favor arrestin signaling over G protein signaling and another that appears to favor G protein signaling over arrestin signaling. These results, combined with mutagenesis validation, provide a molecular explanation of how agonists achieve biased signaling at KOR.
View details for DOI 10.1038/s41467-023-37041-7
View details for PubMedID 36906681
View details for PubMedCentralID PMC10008561
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Structural basis of efficacy-driven ligand selectivity at GPCRs.
Nature chemical biology
2023
Abstract
A drug's selectivity for target receptors is essential to its therapeutic utility, but achieving selectivity between similar receptors is challenging. The serendipitous discovery of ligands that stimulate target receptors more strongly than closely related receptors, despite binding with similar affinities, suggests a solution. The molecular mechanism of such 'efficacy-driven selectivity' has remained unclear, however, hindering design of such ligands. Here, using atomic-level simulations, we reveal the structural basis for the efficacy-driven selectivity of a long-studied clinical drug candidate, xanomeline, between closely related muscarinic acetylcholine receptors (mAChRs). Xanomeline's binding mode is similar across mAChRs in their inactive states but differs between mAChRs in their active states, with divergent effects on active-state stability. We validate this mechanism experimentally and use it to design ligands with altered efficacy-driven selectivity. Our results suggest strategies for the rational design of ligands that achieve efficacy-driven selectivity for many pharmaceutically important G-protein-coupled receptors.
View details for DOI 10.1038/s41589-022-01247-5
View details for PubMedID 36782010
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Insights into distinct signaling profiles of the OR activated by diverse agonists.
Nature chemical biology
2022
Abstract
Drugs targeting the mu-opioid receptor (muOR) are the most effective analgesics available but are also associated with fatal respiratory depression through a pathway that remains unclear. Here we investigated the mechanistic basis of action of lofentanil (LFT) and mitragynine pseudoindoxyl (MP), two muOR agonists with different safety profiles. LFT, one of the most lethal opioids, and MP, a kratom plant derivative with reduced respiratory depression in animal studies, exhibited markedly different efficacy profiles for G protein subtype activation and beta-arrestin recruitment. Cryo-EM structures of muOR-Gi1 complex with MP (2.5A) and LFT (3.2A) revealed that the two ligands engage distinct subpockets, and molecular dynamics simulations showed additional differences in the binding site that promote distinct active-state conformations on the intracellular side of the receptor where G proteins and beta-arrestins bind. These observations highlight how drugs engaging different parts of the muOR orthosteric pocket can lead to distinct signaling outcomes.
View details for DOI 10.1038/s41589-022-01208-y
View details for PubMedID 36411392
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Signaling snapshots of a serotonin receptor activated by the prototypical psychedelic LSD.
Neuron
2022
Abstract
Serotonin (5-hydroxytryptamine [5-HT]) 5-HT2-family receptors represent essential targets for lysergic acid diethylamide (LSD) and all other psychedelic drugs. Although the primary psychedelic drug effects are mediated by the 5-HT2A serotonin receptor (HTR2A), the 5-HT2B serotonin receptor (HTR2B) has been used as a model receptor to study the activation mechanisms of psychedelic drugs due to its high expression and similarity to HTR2A. In this study, we determined the cryo-EM structures of LSD-bound HTR2B in the transducer-free, Gq-protein-coupled, and beta-arrestin-1-coupled states. These structures provide distinct signaling snapshots of LSD's action, ranging from the transducer-free, partially active state to the transducer-coupled, fully active states. Insights from this study will both provide comprehensive molecular insights into the signaling mechanisms of the prototypical psychedelic LSD and accelerate the discovery of novel psychedelic drugs.
View details for DOI 10.1016/j.neuron.2022.08.006
View details for PubMedID 36087581
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Autoantibody mimicry of hormone action at the thyrotropin receptor.
Nature
2022
Abstract
Thyroid hormones are vital to metabolism, growth and development1. Thyroid hormone synthesis is controlled by thyrotropin (TSH), which acts at the thyrotropin receptor (TSHR)2. Autoantibodies that activate the TSHR pathologically increase thyroid hormones in Graves' disease3. How autoantibodies mimic TSH function remains unclear. We determined cryogenic-electron microscopy structures of active and inactive TSHR. In inactive TSHR, the extracellular domain lies close to the membrane bilayer. TSH selects an upright orientation of the extracellular domain due to steric clashes between a conserved hormone glycan and the membrane bilayer. An activating autoantibody from a Graves' disease patient selects a similar upright orientation of the extracellular domain. Reorientation of the extracellular domain transduces a conformational change in the seven transmembrane domain via a conserved hinge domain, a tethered peptide agonist, and a phospholipid that binds within the seven transmembrane domain. Rotation of the TSHR extracellular domain relative to the membrane bilayer is sufficient for receptor activation, revealing a shared mechanism for other glycoprotein hormone receptors that may also extend to other G protein-coupled receptors with large extracellular domains.
View details for DOI 10.1038/s41586-022-05159-1
View details for PubMedID 35940205
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Cryo-EM, Protein Engineering, and Simulation Enable the Development of Peptide Therapeutics against Acute Myeloid Leukemia.
ACS central science
2022; 8 (2): 214-222
Abstract
Cryogenic electron microscopy (cryo-EM) has emerged as a viable structural tool for molecular therapeutics development against human diseases. However, it remains a challenge to determine structures of proteins that are flexible and smaller than 30 kDa. The 11 kDa KIX domain of CREB-binding protein (CBP), a potential therapeutic target for acute myeloid leukemia and other cancers, is a protein which has defied structure-based inhibitor design. Here, we develop an experimental approach to overcome the size limitation by engineering a protein double-shell to sandwich the KIX domain between apoferritin as the inner shell and maltose-binding protein as the outer shell. To assist homogeneous orientations of the target, disulfide bonds are introduced at the target-apoferritin interface, resulting in a cryo-EM structure at 2.6 A resolution. We used molecular dynamics simulations to design peptides that block the interaction of the KIX domain of CBP with the intrinsically disordered pKID domain of CREB. The double-shell design allows for fluorescence polarization assays confirming the binding between the KIX domain in the double-shell and these interacting peptides. Further cryo-EM analysis reveals a helix-helix interaction between a single KIX helix and the best peptide, providing a possible strategy for developments of next-generation inhibitors.
View details for DOI 10.1021/acscentsci.1c01090
View details for PubMedID 35233453
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Structural basis for channel conduction in the pump-like channelrhodopsin ChRmine.
Cell
1800
Abstract
ChRmine, a recently discovered pump-like cation-conducting channelrhodopsin, exhibits puzzling properties (large photocurrents, red-shifted spectrum, and extreme light sensitivity) that have created new opportunities in optogenetics. ChRmine and its homologs function as ion channels but, by primary sequence, more closely resemble ion pump rhodopsins; mechanisms for passive channel conduction in this family have remained mysterious. Here, we present the 2.0A resolution cryo-EM structure of ChRmine, revealing architectural features atypical for channelrhodopsins: trimeric assembly, a short transmembrane-helix 3, a twisting extracellular-loop 1, large vestibules within the monomer, and an opening at the trimer interface. We applied this structure to design three proteins (rsChRmine and hsChRmine, conferring further red-shifted and high-speed properties, respectively, and frChRmine, combining faster and more red-shifted performance) suitable for fundamental neuroscience opportunities. These results illuminate the conduction and gating of pump-like channelrhodopsins and point the way toward further structure-guided creation of channelrhodopsins for applications across biology.
View details for DOI 10.1016/j.cell.2022.01.007
View details for PubMedID 35114111
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Atypical structural snapshots of human cytomegalovirus GPCR interactions with host G proteins.
Science advances
1800; 8 (3): eabl5442
Abstract
Human cytomegalovirus (HCMV) encodes G protein-coupled receptors (GPCRs) US28 and US27, which facilitate viral pathogenesis through engagement of host G proteins. Here we report cryo-electron microscopy structures of US28 and US27 forming nonproductive and productive complexes with Gi and Gq, respectively, exhibiting unusual features with functional implications. The "orphan" GPCR US27 lacks a ligand-binding pocket and has captured a guanosine diphosphate-bound inactive Gi through a tenuous interaction. The docking modes of CX3CL1-US28 and US27 to Gi favor localization to endosome-like curved membranes, where US28 and US27 can function as nonproductive Gi sinks to attenuate host chemokine-dependent Gi signaling. The CX3CL1-US28-Gq/11 complex likely represents a trapped intermediate during productive signaling, providing a view of a transition state in GPCR-G protein coupling for signaling. Our collective results shed new insight into unique G protein-mediated HCMV GPCR structural mechanisms, compared to mammalian GPCR counterparts, for subversion of host immunity.
View details for DOI 10.1126/sciadv.abl5442
View details for PubMedID 35061538
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Leveraging nonstructural data to predict structures and affinities of protein-ligand complexes.
Proceedings of the National Academy of Sciences of the United States of America
1800; 118 (51)
Abstract
Over the past five decades, tremendous effort has been devoted to computational methods for predicting properties of ligands-i.e., molecules that bind macromolecular targets. Such methods, which are critical to rational drug design, fall into two categories: physics-based methods, which directly model ligand interactions with the target given the target's three-dimensional (3D) structure, and ligand-based methods, which predict ligand properties given experimental measurements for similar ligands. Here, we present a rigorous statistical framework to combine these two sources of information. We develop a method to predict a ligand's pose-the 3D structure of the ligand bound to its target-that leverages a widely available source of information: a list of other ligands that are known to bind the same target but for which no 3D structure is available. This combination of physics-based and ligand-based modeling improves pose prediction accuracy across all major families of drug targets. Using the same framework, we develop a method for virtual screening of drug candidates, which outperforms standard physics-based and ligand-based virtual screening methods. Our results suggest broad opportunities to improve prediction of various ligand properties by combining diverse sources of information through customized machine-learning approaches.
View details for DOI 10.1073/pnas.2112621118
View details for PubMedID 34921117
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Structure and mechanism of the SGLT family of glucose transporters.
Nature
2021
Abstract
Glucose is a primary energy source in living cells. The discovery in 1960s that a sodium gradient powers the active uptake of glucose in the intestine1 heralded the concept of a secondary active transporter that can catalyse the movement of a substrate against an electrochemical gradient by harnessing energy from another coupled substrate. Subsequently, coupled Na+/glucose transport was found to be mediated by sodium-glucose cotransporters2,3 (SGLTs). SGLTs are responsible for active glucose and galactose absorption in the intestine and for glucose reabsorption in the kidney4, and are targeted by multiple drugs to treat diabetes5. Several members within the SGLT family transport key metabolites other than glucose2. Here we report cryo-electron microscopy structures of the prototypic human SGLT1 and a related monocarboxylate transporter SMCT1 from the same family. The structures, together with molecular dynamics simulations and functional studies, define the architecture of SGLTs, uncover the mechanism of substrate binding and selectivity, and shed light on water permeability of SGLT1. These results provide insights into the multifaceted functions of SGLTs.
View details for DOI 10.1038/s41586-021-04211-w
View details for PubMedID 34880492
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Selective G protein signaling driven by substance P-neurokinin receptor dynamics.
Nature chemical biology
2021
Abstract
The neuropeptide substance P (SP) is important in pain and inflammation. SP activates the neurokinin-1 receptor (NK1R) to signal via Gq and Gs proteins. Neurokinin A also activates NK1R, but leads to selective Gq signaling. How two stimuli yield distinct G protein signaling at the same G protein-coupled receptor remains unclear. We determined cryogenic-electron microscopy structures of active NK1R bound to SP or the Gq-biased peptide SP6-11. Peptide interactions deep within NK1R are critical for receptor activation. Conversely, interactions between SP and NK1R extracellular loops are required for potent Gs signaling but not Gq signaling. Molecular dynamics simulations showed that these superficial contacts restrict SP flexibility. SP6-11, which lacks these interactions, is dynamic while bound to NK1R. Structural dynamics of NK1R agonists therefore depend on interactions with the receptor extracellular loops and regulate G protein signaling selectivity. Similar interactions between other neuropeptides and their cognate receptors may tune intracellular signaling.
View details for DOI 10.1038/s41589-021-00890-8
View details for PubMedID 34711980
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Structure and mechanism of blood-brain-barrier lipid transporter MFSD2A.
Nature
2021
Abstract
MFSD2A is a sodium-dependent lysophosphatidylcholine symporter that is responsible for the uptake of docosahexaenoic acid into the brain1,2, which is crucial for the development and performance of the brain3. Mutations that affect MFSD2A cause microcephaly syndromes4,5. The ability of MFSD2A to transport lipid is also a key mechanism that underlies its function as an inhibitor of transcytosis to regulate the blood-brain barrier6,7. Thus, MFSD2A represents an attractive target for modulating the permeability of the blood-brain barrier for drug delivery. Here we report the cryo-electron microscopy structure of mouse MFSD2A. Our structure defines the architecture of this important transporter, reveals its unique extracellular domain and uncovers its substrate-binding cavity. The structure-together with our functional studies and molecular dynamics simulations-identifies a conserved sodium-binding site, reveals a potential lipid entry pathway and helps to rationalize MFSD2A mutations that underlie microcephaly syndromes. These results shed light on the critical lipid transport function of MFSD2A and provide a framework to aid in the design of specific modulators for therapeutic purposes.
View details for DOI 10.1038/s41586-021-03782-y
View details for PubMedID 34349262
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Gold nanoparticles and tilt pairs to assess protein flexibility by cryo-electron microscopy.
Ultramicroscopy
2021; 227: 113302
Abstract
A computational method was developed to recover the three-dimensional coordinates of gold nanoparticles specifically attached to a protein complex from tilt-pair images collected by electron microscopy. The program was tested on a simulated dataset and applied to a real dataset comprising tilt-pair images recorded by cryo electron microscopy of RNA polymerase II in a complex with four gold-labeled single-chain antibody fragments. The positions of the gold nanoparticles were determined, and comparison of the coordinates among the tetrameric particles revealed the range of motion within the protein complexes.
View details for DOI 10.1016/j.ultramic.2021.113302
View details for PubMedID 34062386
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Simple biochemical features underlie transcriptional activation domain diversity and dynamic, fuzzy binding to Mediator.
eLife
2021; 10
Abstract
Gene activator proteins comprise distinct DNA-binding and transcriptional activation domains (ADs). Because few ADs have been described, we tested domains tiling all yeast transcription factors for activation in vivo and identified 150 ADs. By mRNA display, we showed that 73% of ADs bound the Med15 subunit of Mediator, and that binding strength was correlated with activation. AD-Mediator interaction in vitro was unaffected by a large excess of free activator protein, pointing to a dynamic mechanism of interaction. Structural modeling showed that ADs interact with Med15 without shape complementarity ('fuzzy' binding). ADs shared no sequence motifs, but mutagenesis revealed biochemical and structural constraints. Finally, a neural network trained on AD sequences accurately predicted ADs in human proteins and in other yeast proteins, including chromosomal proteins and chromatin remodeling complexes. These findings solve the longstanding enigma of AD structure and function and provide a rationale for their role in biology.
View details for DOI 10.7554/eLife.68068
View details for PubMedID 33904398
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Delineating the Ligand-Receptor Interactions That Lead to Biased Signaling at the μ-Opioid Receptor.
Journal of chemical information and modeling
2021
Abstract
Biased agonists, which selectively stimulate certain signaling pathways controlled by a G protein-coupled receptor (GPCR), hold great promise as drugs that maximize efficacy while minimizing dangerous side effects. Biased agonists of the μ-opioid receptor (μOR) are of particular interest as a means to achieve analgesia through G protein signaling without dose-limiting side effects such as respiratory depression and constipation. Rational structure-based design of biased agonists remains highly challenging, however, because the ligand-mediated interactions that are key to activation of each signaling pathway remain unclear. We identify several compounds for which the R- and S-enantiomers have distinct bias profiles at the μOR. These compounds serve as excellent comparative tools to study bias because the identical physicochemical properties of enantiomer pairs ensure that differences in bias profiles are due to differences in interactions with the μOR binding pocket. Atomic-level simulations of compounds at μOR indicate that R- and S-enantiomers adopt different poses that form distinct interactions with the binding pocket. A handful of specific interactions with highly conserved binding pocket residues appear to be responsible for substantial differences in arrestin recruitment between enantiomers. Our results offer guidance for rational design of biased agonists at μOR and possibly at related GPCRs.
View details for DOI 10.1021/acs.jcim.1c00585
View details for PubMedID 34251810
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Hierarchical,rotation-equivariant neural networks to select structural models of protein complexes.
Proteins
2020
Abstract
Predicting the structure of multi-protein complexes is a grand challenge in biochemistry, with major implications for basic science and drug discovery. Computational structure prediction methods generally leverage pre-defined structural features to distinguish accurate structural models from less accurate ones. This raises the question of whether it is possible to learn characteristics of accurate models directly from atomic coordinates of protein complexes, with no prior assumptions. Here we introduce a machine learning method that learns directly from the 3D positions of all atoms to identify accurate models of protein complexes, without using any pre-computed physics-inspired or statistical terms. Our neural network architecture combines multiple ingredients that together enable end-to-end learning from molecular structures containing tens of thousands of atoms: a point-based representation of atoms, equivariance with respect to rotation and translation, local convolutions, and hierarchical subsampling operations. When used in combination with previously developed scoring functions, our network substantially improves the identification of accurate structural models among a large set of possible models. Our network can also be used to predict the accuracy of a given structural model in absolute terms. The architecture we present is readily applicable to other tasks involving learning on 3D structures of large atomic systems. This article is protected by copyright. All rights reserved.
View details for DOI 10.1002/prot.26033
View details for PubMedID 33289162
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Structural and functional characterization of G protein-coupled receptors with deep mutational scanning.
eLife
2020; 9
Abstract
In humans, the >800 G protein-coupled receptors (GPCRs) are responsible for transducing diverse chemical stimuli to alter cell state, and are the largest class of drug targets. Their myriad structural conformations and various modes of signaling make it challenging to understand their structure and function. Here we developed a platform to characterize large libraries of GPCR variants in human cell lines with a barcoded transcriptional reporter of G-protein signal transduction. We tested 7,800 of 7,828 possible single amino acid substitutions to the beta-2 adrenergic receptor (beta2AR) at four concentrations of the agonist isoproterenol. We identified residues specifically important for beta2AR signaling, mutations in the human population that are potentially loss of function, and residues that modulate basal activity. Using unsupervised learning, we resolve residues critical for signaling, including all major structural motifs and molecular interfaces. We also find a previously uncharacterized structural latch spanning the first two extracellular loops that is highly conserved across Class A GPCRs and is conformationally rigid in both the inactive and active states of the receptor. More broadly, by linking deep mutational scanning with engineered transcriptional reporters, we establish a generalizable method for exploring pharmacogenomics, structure and function across broad classes of drug receptors.
View details for DOI 10.7554/eLife.54895
View details for PubMedID 33084570
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Angiotensin and biased analogs induce structurally distinct active conformations within a GPCR.
Science (New York, N.Y.)
2020; 367 (6480): 888–92
Abstract
Biased agonists of G protein-coupled receptors (GPCRs) preferentially activate a subset of downstream signaling pathways. In this work, we present crystal structures of angiotensin II type 1 receptor (AT1R) (2.7 to 2.9 angstroms) bound to three ligands with divergent bias profiles: the balanced endogenous agonist angiotensin II (AngII) and two strongly beta-arrestin-biased analogs. Compared with other ligands, AngII promotes more-substantial rearrangements not only at the bottom of the ligand-binding pocket but also in a key polar network in the receptor core, which forms a sodium-binding site in most GPCRs. Divergences from the family consensus in this region, which appears to act as a biased signaling switch, may predispose the AT1R and certain other GPCRs (such as chemokine receptors) to adopt conformations that are capable of activating beta-arrestin but not heterotrimeric Gq protein signaling.
View details for DOI 10.1126/science.aay9813
View details for PubMedID 32079768
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Determining How GPCR Phosphorylation Patterns Affect Arrestin-Mediated Signaling
CELL PRESS. 2020: 319A
View details for Web of Science ID 000513023202100
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Structure of a GRK5-Calmodulin Complex Reveals Molecular Mechanism of GRK Activation and Substrate Targeting.
Molecular cell
2020
Abstract
The phosphorylation of G protein-coupled receptors (GPCRs) by GPCR kinases (GRKs) facilitates arrestin binding and receptor desensitization. Although this process can be regulated by Ca2+-binding proteins such as calmodulin (CaM) and recoverin, the molecular mechanisms are poorly understood. Here, we report structural, computational, and biochemical analysis of a CaM complex with GRK5, revealing how CaM shapes GRK5 response to calcium. The CaM N and C domains bind independently to two helical regions at the GRK5 N and C termini to inhibit GPCR phosphorylation, though only the C domain interaction disrupts GRK5 membrane association, thereby facilitating cytoplasmic translocation. The CaM N domain strongly activates GRK5 via ordering of the amphipathic αN-helix of GRK5 and allosteric disruption of kinase-RH domain interaction for phosphorylation of cytoplasmic GRK5 substrates. These results provide a framework for understanding how two functional effects, GRK5 activation and localization, can cooperate under control of CaM for selective substrate targeting by GRK5.
View details for DOI 10.1016/j.molcel.2020.11.026
View details for PubMedID 33321095
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Structure of hepcidin-bound ferroportin reveals iron homeostatic mechanisms.
Nature
2020
Abstract
The serum iron level in humans is tightly controlled by the action of the hormone hepcidin on the iron efflux transporter ferroportin. Hepcidin regulates iron absorption and recycling by inducing ferroportin internalization and degradation1. Aberrant ferroportin activity can lead to diseases of iron overload, such as hemochromatosis, or iron limitation anemias2. Here, we determined cryogenic electron microscopy (cryo-EM) structures of ferroportin in lipid nanodiscs, both in the apo state and in complex with cobalt, an iron mimetic, and hepcidin. These structures and accompanying molecular dynamics simulations identify two metal binding sites within the N- and C-domains of ferroportin. Hepcidin binds ferroportin in an outward-open conformation and completely occludes the iron efflux pathway to inhibit transport. The carboxy-terminus of hepcidin directly contacts the divalent metal in the ferroportin C-domain. We further show that hepcidin binding to ferroportin is coupled to iron binding, with an 80-fold increase in hepcidin affinity in the presence of iron. These results suggest a model for hepcidin regulation of ferroportin, where only iron loaded ferroportin molecules are targeted for degradation. More broadly, our structural and functional insights are likely to enable more targeted manipulation of the hepcidin-ferroportin axis in disorders of iron homeostasis.
View details for DOI 10.1038/s41586-020-2668-z
View details for PubMedID 32814342
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Structure and mechanism of the cation-chloride cotransporter NKCC1.
Nature
2019
Abstract
Cation-chloride cotransporters (CCCs) mediate the electroneutral transport of chloride, potassium and/or sodium across the membrane. They have critical roles in regulating cell volume, controlling ion absorption and secretion across epithelia, and maintaining intracellular chloride homeostasis. These transporters are primary targets for some of the most commonly prescribed drugs. Here we determined the cryo-electron microscopy structure of the Na-K-Cl cotransporter NKCC1, an extensively studied member of the CCC family,from Danio rerio. The structure defines the architecture of this protein family and reveals how cytosolic and transmembrane domains are strategically positioned for communication. Structural analyses, functional characterizations and computational studies reveal the ion-translocation pathway, ion-binding sites and key residues for transport activity. These results provide insights into ion selectivity, coupling and translocation, and establish a framework for understanding the physiological functions of CCCs and interpreting disease-related mutations.
View details for DOI 10.1038/s41586-019-1438-2
View details for PubMedID 31367042
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Smoothened stimulation by membrane sterols drives Hedgehog pathway activity.
Nature
2019
Abstract
Hedgehog signalling is fundamental to embryonic development and postnatal tissue regeneration1. Aberrant postnatal Hedgehog signalling leads to several malignancies, including basal cell carcinoma and paediatric medulloblastoma2. Hedgehog proteins bind to and inhibit the transmembrane cholesterol transporter Patched-1 (PTCH1), which permits activation of the seven-transmembrane transducer Smoothened (SMO) via a mechanism that is poorly understood. Here we report the crystal structure of active mouse SMO bound to both the agonist SAG21k and to an intracellular binding nanobody that stabilizes a physiologically relevant active state. Analogous to other G protein-coupled receptors, the activation of SMO is associated with subtle motions in the extracellular domain, and larger intracellular changes. In contrast to recent models3-5, a cholesterol molecule that is critical for SMO activation is bound deep within the seven-transmembrane pocket. We propose that the inactivation of PTCH1 by Hedgehog allows a transmembrane sterol to access this seven-transmembrane site (potentially through a hydrophobic tunnel), which drives the activation of SMO. These results-combined with signalling studies and molecular dynamics simulations-delineate the structural basis for PTCH1-SMO regulation, and suggest a strategy for overcoming clinical resistance to SMO inhibitors.
View details for DOI 10.1038/s41586-019-1355-4
View details for PubMedID 31263273
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Conformational transitions of a neurotensin receptor1-Gi1complex.
Nature
2019
Abstract
Neurotensin receptor1 (NTSR1) is a G-protein-coupled receptor (GPCR) that engages multiple subtypes of G protein, and is involved in the regulation of blood pressure, body temperature, weight and the response to pain. Here we present structures of human NTSR1 in complex with the agonist JMV449 and the heterotrimeric Gi1 protein, at a resolution of 3A. We identify two conformations: a canonical-state complex that is similar to recently reported GPCR-Gi/o complexes (in which the nucleotide-binding pocket adopts moreflexible conformations that may facilitate nucleotide exchange), and a non-canonical state in which the G protein is rotated by about 45degrees relative to the receptor and exhibits a more rigid nucleotide-binding pocket. In the non-canonical state, NTSR1 exhibits features of both active and inactive conformations, which suggests that the structure may represent an intermediate form along the activation pathway of G proteins. This structural information, complemented by molecular dynamics simulations and functional studies, provides insights into the complex process of G-protein activation.
View details for DOI 10.1038/s41586-019-1337-6
View details for PubMedID 31243364
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How Effectively Can Adaptive Sampling Methods Capture Spontaneous Ligand Binding?
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
2019; 15 (3): 2053–63
Abstract
Molecular dynamics (MD) simulations that capture the spontaneous binding of drugs and other ligands to their target proteins can reveal a great deal of useful information, but most drug-like ligands bind on time scales longer than those accessible to individual MD simulations. Adaptive sampling methods-in which one performs multiple rounds of simulation, with the initial conditions of each round based on the results of previous rounds-offer a promising potential solution to this problem. No comprehensive analysis of the performance gains from adaptive sampling is available for ligand binding, however, particularly for protein-ligand systems typical of those encountered in drug discovery. Moreover, most previous work presupposes knowledge of the ligand's bound pose. Here we outline existing methods for adaptive sampling of the ligand-binding process and introduce several improvements, with a focus on methods that do not require prior knowledge of the binding site or bound pose. We then evaluate these methods by comparing them to traditional, long MD simulations for realistic protein-ligand systems. We find that adaptive sampling simulations typically fail to reach the bound pose more efficiently than traditional MD. However, adaptive sampling identifies multiple potential binding sites more efficiently than traditional MD and also provides better characterization of binding pathways. We explain these results by showing that protein-ligand binding is an example of an exploration-exploitation dilemma. Existing adaptive sampling methods for ligand binding in the absence of a known bound pose vastly favor the broad exploration of protein-ligand space, sometimes failing to sufficiently exploit intermediate states as they are discovered. We suggest potential avenues for future research to address this shortcoming.
View details for PubMedID 30645108
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Diverse GPCRs exhibit conserved water networks for stabilization and activation
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2019; 116 (8): 3288–93
View details for DOI 10.1073/pnas.1809251116
View details for Web of Science ID 000459074400073
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Structure of a Signaling Cannabinoid Receptor 1-G Protein Complex
CELL
2019; 176 (3): 448-+
View details for DOI 10.1016/j.cell.2018.11.040
View details for Web of Science ID 000456526100007
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Angiotensin Analogs with Divergent Bias Stabilize Distinct Receptor Conformations.
Cell
2019
Abstract
"Biased" G protein-coupled receptor (GPCR) agonists preferentially activate pathways mediated by G proteins or beta-arrestins. Here, we use double electron-electron resonance spectroscopy to probe the changes that ligands induce in the conformational distribution of the angiotensin II type I receptor. Monitoring distances between 10 pairs of nitroxide labels distributed across the intracellular regions enabled mapping of four underlying sets of conformations. Ligands from different functional classes have distinct, characteristic effects on the conformational heterogeneity of the receptor. Compared to angiotensin II, the endogenous agonist, agonists with enhanced Gq coupling more strongly stabilize an "open" conformation with an accessible transducer-binding site. beta-arrestin-biased agonists deficient in Gq coupling do not stabilize this open conformation but instead favor two more occluded conformations. These data suggest a structural mechanism for biased ligand action at the angiotensin receptor that can be exploited to rationally design GPCR-targeting drugs with greater specificity of action.
View details for PubMedID 30639099
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Cryptic pocket formation underlies allosteric modulator selectivity at muscarinic GPCRs.
Nature communications
2019; 10 (1): 3289
Abstract
Allosteric modulators are highly desirable as drugs, particularly for G-protein-coupled receptor (GPCR) targets, because allosteric drugs can achieve selectivity between closely related receptors. The mechanisms by which allosteric modulators achieve selectivity remain elusive, however, particularly given recent structures that reveal similar allosteric binding sites across receptors. Here we show that positive allosteric modulators (PAMs) of the M1 muscarinic acetylcholine receptor (mAChR) achieve exquisite selectivity by occupying a dynamic pocket absent in existing crystal structures. This cryptic pocket forms far more frequently in molecular dynamics simulations of the M1 mAChR than in those of other mAChRs. These observations reconcile mutagenesis data that previously appeared contradictory. Further mutagenesis experiments validate our prediction that preventing cryptic pocket opening decreases the affinity of M1-selective PAMs. Our findings suggest opportunities for the design of subtype-specific drugs exploiting cryptic pockets that open in certain receptors but not in other receptors with nearly identical static structures.
View details for DOI 10.1038/s41467-019-11062-7
View details for PubMedID 31337749
- End-to-End Learning on 3D Protein Structure for Interface Prediction. Advances in Neural Information Processing Systems Conference on Neural Information Processing Systems (NeurIPS) 2019: 15642–15651
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End-to-End Learning on 3D Protein Structure for Interface Prediction
NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2019
View details for Web of Science ID 000535866907031
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Structure of a Signaling Cannabinoid Receptor 1-G Protein Complex.
Cell
2018
Abstract
Cannabis elicits its mood-enhancing and analgesic effects through the cannabinoid receptor 1 (CB1), aG protein-coupled receptor (GPCR) that signals primarily through the adenylyl cyclase-inhibiting heterotrimeric G protein Gi. Activation of CB1-Gi signaling pathways holds potential for treating a number of neurological disorders and is thus crucial to understand the mechanism of Gi activation by CB1. Here, we present the structure of the CB1-Gi signaling complex bound to the highly potent agonist MDMB-Fubinaca (FUB), a recently emerged illicit synthetic cannabinoid infused in street drugs that have been associated with numerous overdoses and fatalities. The structure illustrates how FUB stabilizes the receptor in an active state to facilitate nucleotide exchange in Gi. The results compose the structural framework to explain CB1 activation by different classes of ligands and provide insights into the G protein coupling and selectivity mechanisms adopted by the receptor.
View details for PubMedID 30639101
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Publisher Correction: Structural insights into binding specificity, efficacy and bias of a beta2AR partial agonist.
Nature chemical biology
2018
Abstract
In the version of this paper originally published, the structure for epinephrine shown in Figure 1a was redrawn with an extra carbon. The structure has been replaced in the HTML and PDF versions of the article. The original and corrected versions of the structure are shown below.
View details for PubMedID 30504785
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Structural insights into binding specificity, efficacy and bias of a beta2AR partial agonist.
Nature chemical biology
2018; 14 (11): 1059–66
Abstract
Salmeterol is a partial agonist for the beta2 adrenergic receptor (beta2AR) and the first long-acting beta2AR agonist to be widely used clinically for the treatment of asthma and chronic obstructive pulmonary disease. Salmeterol's safety and mechanism of action have both been controversial. To understand its unusual pharmacological action and partial agonism, we obtained the crystal structure of salmeterol-bound beta2AR in complex with an active-state-stabilizing nanobody. The structure reveals the location of the salmeterol exosite, where sequence differences between beta1AR and beta2AR explain the high receptor-subtype selectivity. A structural comparison with the beta2AR bound to the full agonist epinephrine reveals differences in the hydrogen-bond network involving residues Ser2045.43 and Asn2936.55. Mutagenesis and biophysical studies suggested that these interactions lead to a distinct active-state conformation that is responsible for the partial efficacy of G-protein activation and the limited beta-arrestin recruitment for salmeterol.
View details for PubMedID 30327561
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Entry from the Lipid Bilayer: A Possible Pathway for Inhibition of a Peptide G Protein-Coupled Receptor by a Lipophilic Small Molecule
BIOCHEMISTRY
2018; 57 (39): 5748–58
Abstract
The pathways that G protein-coupled receptor (GPCR) ligands follow as they bind to or dissociate from their receptors are largely unknown. Protease-activated receptor-1 (PAR1) is a GPCR activated by intramolecular binding of a tethered agonist peptide that is exposed by thrombin cleavage. By contrast, the PAR1 antagonist vorapaxar is a lipophilic drug that binds in a pocket almost entirely occluded from the extracellular solvent. The binding and dissociation pathway of vorapaxar is unknown. Starting with the crystal structure of vorapaxar bound to PAR1, we performed temperature-accelerated molecular dynamics simulations of ligand dissociation. In the majority of simulations, vorapaxar exited the receptor laterally into the lipid bilayer through openings in the transmembrane helix (TM) bundle. Prior to full dissociation, vorapaxar paused in metastable intermediates stabilized by interactions with the receptor and lipid headgroups. Derivatives of vorapaxar with alkyl chains predicted to extend between TM6 and TM7 into the lipid bilayer inhibited PAR1 with apparent on rates similar to that of the parent compound in cell signaling assays. These data are consistent with vorapaxar binding to PAR1 via a pathway that passes between TM6 and TM7 from the lipid bilayer, in agreement with the most consistent pathway observed by molecular dynamics. While there is some evidence of entry of the ligand into rhodopsin and lipid-activated GPCRs from the cell membrane, our study provides the first such evidence for a peptide-activated GPCR and suggests that metastable intermediates along drug binding and dissociation pathways can be stabilized by specific interactions between lipids and the ligand.
View details for DOI 10.1021/acs.biochem.8b00577
View details for Web of Science ID 000446542800012
View details for PubMedID 30102523
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Structural basis for sigma(1) receptor ligand recognition
NATURE STRUCTURAL & MOLECULAR BIOLOGY
2018; 25 (10): 981-+
Abstract
The σ1 receptor is a poorly understood membrane protein expressed throughout the human body. Ligands targeting the σ1 receptor are in clinical trials for treatment of Alzheimer's disease, ischemic stroke, and neuropathic pain. However, relatively little is known regarding the σ1 receptor's molecular function. Here, we present crystal structures of human σ1 receptor bound to the antagonists haloperidol and NE-100, and the agonist (+)-pentazocine, at crystallographic resolutions of 3.1 Å, 2.9 Å, and 3.1 Å, respectively. These structures reveal a unique binding pose for the agonist. The structures and accompanying molecular dynamics (MD) simulations identify agonist-induced structural rearrangements in the receptor. Additionally, we show that ligand binding to σ1 is a multistep process that is rate limited by receptor conformational change. We used MD simulations to reconstruct a ligand binding pathway involving two major conformational changes. These data provide a framework for understanding the molecular basis for σ1 agonism.
View details for PubMedID 30291362
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Molecular Dynamics Simulation for All.
Neuron
2018; 99 (6): 1129–43
Abstract
The impact of molecular dynamics (MD) simulations in molecular biology and drug discovery has expanded dramatically in recent years. These simulations capture the behavior of proteins and other biomolecules in full atomic detail and at very fine temporal resolution. Major improvements in simulation speed, accuracy, and accessibility, together with the proliferation of experimental structural data, have increased the appeal of biomolecular simulation to experimentalists-a trend particularly noticeable in, although certainly not limited to, neuroscience. Simulations have proven valuable in deciphering functional mechanisms of proteins and other biomolecules, in uncovering the structural basis for disease, and in the design and optimization of small molecules, peptides, and proteins. Here we describe, in practical terms, the types of information MD simulations can provide and the ways in which they typically motivate further experimental work.
View details for PubMedID 30236283
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Structural mechanisms of selectivity and gating in anion channelrhodopsins.
Nature
2018
Abstract
Both designed and natural anion-conducting channelrhodopsins (dACRs and nACRs, respectively) have been widely applied in optogenetics (enabling selective inhibition of target-cell activity during animal behaviour studies), but each class exhibits performance limitations, underscoring trade-offs in channel structure-function relationships. Therefore, molecular and structural insights into dACRs and nACRs will be critical not only for understanding the fundamental mechanisms of these light-gated anionchannels, but also to create next-generation optogenetic tools. Here we report crystal structures of the dACR iC++, along with spectroscopic, electrophysiological and computational analyses that provide unexpected insights into pH dependence, substrate recognition, channel gating and ion selectivity of both dACRs and nACRs. These results enabled us to create an anion-conducting channelrhodopsin integrating the key features of large photocurrent and fast kinetics alongside exclusive anion selectivity.
View details for PubMedID 30158697
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Crystal structure of the natural anion-conducting channelrhodopsin GtACR1.
Nature
2018
Abstract
The naturally occurring channelrhodopsin variant anion channelrhodopsin-1 (ACR1), discovered in the cryptophyte algae Guillardia theta, exhibits large light-gated anionconductance and high anionselectivity when expressed in heterologous settings, properties that support its use as an optogenetic tool to inhibit neuronal firing with light. However, molecular insight into ACR1 is lacking owing to the absence of structural information underlying light-gated anion conductance. Here we present the crystal structure of G. theta ACR1 at 2.9A resolution. The structure reveals unusual architectural features that span the extracellular domain, retinal-binding pocket, Schiff-base region, and anion-conduction pathway. Together with electrophysiological and spectroscopic analyses, these findings reveal the fundamental molecular basis of naturally occurring light-gated anion conductance, and provide a framework for designing the next generation of optogenetic tools.
View details for PubMedID 30158696
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Structure of the µ-opioid receptor-Gi protein complex.
Nature
2018
Abstract
The mu-opioid receptor (muOR) is a G-protein-coupled receptor (GPCR) and the target of most clinically and recreationally used opioids. The induced positive effects of analgesia and euphoria are mediated by muOR signalling through the adenylyl cyclase-inhibiting heterotrimeric G protein Gi. Here we present the 3.5A resolution cryo-electron microscopy structure of the muOR bound to the agonist peptide DAMGO and nucleotide-free Gi. DAMGO occupies the morphinan ligand pocket, with its Nterminus interacting with conserved receptor residues and its Cterminus engaging regions important for opioid-ligand selectivity. Comparison of the muOR-Gi complex to previously determined structures of other GPCRs bound to the stimulatory G protein Gs reveals differences in the position of transmembrane receptor helix 6 and in the interactions between the G protein alpha-subunit and the receptor core. Together, these results shed light on the structural features that contribute to the Gi protein-coupling specificity of the OR.
View details for PubMedID 29899455
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Catalytic activation of beta-arrestin by GPCRs
NATURE
2018; 557 (7705): 381-+
Abstract
β-arrestins are critical regulator and transducer proteins for G-protein-coupled receptors (GPCRs). β-arrestin is widely believed to be activated by forming a stable and stoichiometric GPCR-β-arrestin scaffold complex, which requires and is driven by the phosphorylated tail of the GPCR. Here we demonstrate a distinct and additional mechanism of β-arrestin activation that does not require stable GPCR-β-arrestin scaffolding or the GPCR tail. Instead, it occurs through transient engagement of the GPCR core, which destabilizes a conserved inter-domain charge network in β-arrestin. This promotes capture of β-arrestin at the plasma membrane and its accumulation in clathrin-coated endocytic structures (CCSs) after dissociation from the GPCR, requiring a series of interactions with membrane phosphoinositides and CCS-lattice proteins. β-arrestin clustering in CCSs in the absence of the upstream activating GPCR is associated with a β-arrestin-dependent component of the cellular ERK (extracellular signal-regulated kinase) response. These results delineate a discrete mechanism of cellular β-arrestin function that is activated catalytically by GPCRs.
View details for PubMedID 29720660
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One receptor, many partners: How do GPCRs stimulate diverse signaling proteins?
AMER CHEMICAL SOC. 2018
View details for Web of Science ID 000435537706812
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Molecular simulation and machine learning for the design of finely tuned drugs
AMER CHEMICAL SOC. 2018
View details for Web of Science ID 000435537706446
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G(i)- and G(s)-coupled GPCRs show different modes of G-protein binding
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2018; 115 (10): 2383–88
Abstract
More than two decades ago, the activation mechanism for the membrane-bound photoreceptor and prototypical G protein-coupled receptor (GPCR) rhodopsin was uncovered. Upon light-induced changes in ligand-receptor interaction, movement of specific transmembrane helices within the receptor opens a crevice at the cytoplasmic surface, allowing for coupling of heterotrimeric guanine nucleotide-binding proteins (G proteins). The general features of this activation mechanism are conserved across the GPCR superfamily. Nevertheless, GPCRs have selectivity for distinct G-protein family members, but the mechanism of selectivity remains elusive. Structures of GPCRs in complex with the stimulatory G protein, Gs, and an accessory nanobody to stabilize the complex have been reported, providing information on the intermolecular interactions. However, to reveal the structural selectivity filters, it will be necessary to determine GPCR-G protein structures involving other G-protein subtypes. In addition, it is important to obtain structures in the absence of a nanobody that may influence the structure. Here, we present a model for a rhodopsin-G protein complex derived from intermolecular distance constraints between the activated receptor and the inhibitory G protein, Gi, using electron paramagnetic resonance spectroscopy and spin-labeling methodologies. Molecular dynamics simulations demonstrated the overall stability of the modeled complex. In the rhodopsin-Gi complex, Gi engages rhodopsin in a manner distinct from previous GPCR-Gs structures, providing insight into specificity determinants.
View details for PubMedID 29463720
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Mechanism of Substrate Translocation in an Alternating Access Transporter
CELL PRESS. 2018: 207A
View details for Web of Science ID 000430439600286
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Structure-inspired design of beta-arrestin-biased ligands for aminergic GPCRs
NATURE CHEMICAL BIOLOGY
2018; 14 (2): 126-+
Abstract
Development of biased ligands targeting G protein-coupled receptors (GPCRs) is a promising approach for current drug discovery. Although structure-based drug design of biased agonists remains challenging even with an abundance of GPCR crystal structures, we present an approach for translating GPCR structural data into β-arrestin-biased ligands for aminergic GPCRs. We identified specific amino acid-ligand contacts at transmembrane helix 5 (TM5) and extracellular loop 2 (EL2) responsible for Gi/o and β-arrestin signaling, respectively, and targeted those residues to develop biased ligands. For these ligands, we found that bias is conserved at other aminergic GPCRs that retain similar residues at TM5 and EL2. Our approach provides a template for generating arrestin-biased ligands by modifying predicted ligand interactions that block TM5 interactions and promote EL2 interactions. This strategy may facilitate the structure-guided design of arrestin-biased ligands at other GPCRs, including polypharmacological biased ligands.
View details for PubMedID 29227473
View details for PubMedCentralID PMC5771956
- Structure-inspired design of β-arrestin-biased ligands for aminergic GPCRs Nature Chemical Biology 2018: 126-134
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D-4 dopamine receptor high-resolution structures enable the discovery of selective agonists
SCIENCE
2017; 358 (6361): 381-+
Abstract
Dopamine receptors are implicated in the pathogenesis and treatment of nearly every neuropsychiatric disorder. Although thousands of drugs interact with these receptors, our molecular understanding of dopaminergic drug selectivity and design remains clouded. To illuminate dopamine receptor structure, function, and ligand recognition, we determined crystal structures of the D4 dopamine receptor in its inactive state bound to the antipsychotic drug nemonapride, with resolutions up to 1.95 angstroms. These structures suggest a mechanism for the control of constitutive signaling, and their unusually high resolution enabled a structure-based campaign for new agonists of the D4 dopamine receptor. The ability to efficiently exploit structure for specific probe discovery-rapidly moving from elucidating receptor structure to discovering previously unrecognized, selective agonists-testifies to the power of structure-based approaches.
View details for PubMedID 29051383
View details for PubMedCentralID PMC5856174
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Mechanism of substrate translocation in an alternating access transporter
AMER CHEMICAL SOC. 2017
View details for Web of Science ID 000429525604063
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Revealing the structural basis for GPCR signaling through atomic-level simulation
AMER CHEMICAL SOC. 2017
View details for Web of Science ID 000429556702618
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Structural and Functional Analysis of a beta(2)-Adrenergic Receptor Complex with GRK5
CELL
2017; 169 (3): 407-?
Abstract
The phosphorylation of agonist-occupied G-protein-coupled receptors (GPCRs) by GPCR kinases (GRKs) functions to turn off G-protein signaling and turn on arrestin-mediated signaling. While a structural understanding of GPCR/G-protein and GPCR/arrestin complexes has emerged in recent years, the molecular architecture of a GPCR/GRK complex remains poorly defined. We used a comprehensive integrated approach of cross-linking, hydrogen-deuterium exchange mass spectrometry (MS), electron microscopy, mutagenesis, molecular dynamics simulations, and computational docking to analyze GRK5 interaction with the β2-adrenergic receptor (β2AR). These studies revealed a dynamic mechanism of complex formation that involves large conformational changes in the GRK5 RH/catalytic domain interface upon receptor binding. These changes facilitate contacts between intracellular loops 2 and 3 and the C terminus of the β2AR with the GRK5 RH bundle subdomain, membrane-binding surface, and kinase catalytic cleft, respectively. These studies significantly contribute to our understanding of the mechanism by which GRKs regulate the function of activated GPCRs. PAPERCLIP.
View details for DOI 10.1016/j.cell.2017.03.047
View details for Web of Science ID 000399560600006
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Mechanism of Substrate Translocation in an Alternating Access Transporter
CELL
2017; 169 (1): 96-?
Abstract
Transporters shuttle molecules across cell membranes by alternating among distinct conformational states. Fundamental questions remain about how transporters transition between states and how such structural rearrangements regulate substrate translocation. Here, we capture the translocation process by crystallography and unguided molecular dynamics simulations, providing an atomic-level description of alternating access transport. Simulations of a SWEET-family transporter initiated from an outward-open, glucose-bound structure reported here spontaneously adopt occluded and inward-open conformations. Strikingly, these conformations match crystal structures, including our inward-open structure. Mutagenesis experiments further validate simulation predictions. Our results reveal that state transitions are driven by favorable interactions formed upon closure of extracellular and intracellular "gates" and by an unfavorable transmembrane helix configuration when both gates are closed. This mechanism leads to tight allosteric coupling between gates, preventing them from opening simultaneously. Interestingly, the substrate appears to take a "free ride" across the membrane without causing major structural rearrangements in the transporter.
View details for DOI 10.1016/j.cell.2017.03.010
View details for Web of Science ID 000397090000011
View details for PubMedID 28340354
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Crystal Structure of an LSD-Bound Human Serotonin Receptor.
Cell
2017; 168 (3): 377-389 e12
Abstract
The prototypical hallucinogen LSD acts via serotonin receptors, and here we describe the crystal structure of LSD in complex with the human serotonin receptor 5-HT2B. The complex reveals conformational rearrangements to accommodate LSD, providing a structural explanation for the conformational selectivity of LSD's key diethylamide moiety. LSD dissociates exceptionally slow from both 5-HT2BR and 5-HT2AR-a major target for its psychoactivity. Molecular dynamics (MD) simulations suggest that LSD's slow binding kinetics may be due to a "lid" formed by extracellular loop 2 (EL2) at the entrance to the binding pocket. A mutation predicted to increase the mobility of this lid greatly accelerates LSD's binding kinetics and selectively dampens LSD-mediated β-arrestin2 recruitment. This study thus reveals an unexpected binding mode of LSD; illuminates key features of its kinetics, stereochemistry, and signaling; and provides a molecular explanation for LSD's actions at human serotonin receptors. PAPERCLIP.
View details for DOI 10.1016/j.cell.2016.12.033
View details for PubMedID 28129538
View details for PubMedCentralID PMC5289311
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GPCR Dynamics: Structures in Motion
CHEMICAL REVIEWS
2017; 117 (1): 139-155
Abstract
The function of G protein-coupled receptors (GPCRs)-which represent the largest class of both human membrane proteins and drug targets-depends critically on their ability to change shape, transitioning among distinct conformations. Determining the structural dynamics of GPCRs is thus essential both for understanding the physiology of these receptors and for the rational design of GPCR-targeted drugs. Here we review what is currently known about the flexibility and dynamics of GPCRs, as determined through crystallography, spectroscopy, and computer simulations. We first provide an overview of the types of motion exhibited by a GPCR and then discuss GPCR dynamics in the context of ligand binding, activation, allosteric modulation, and biased signaling. Finally, we discuss the implications of GPCR conformational plasticity for drug design.
View details for DOI 10.1021/acs.chemrev.6b00177
View details for Web of Science ID 000392036100007
View details for PubMedID 27622975
- Identification of phosphorylation codes for arrestin recruitment by G protein-coupled receptors Cell 2017: 457-469
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Identification of Phosphorylation Codes for Arrestin Recruitment by G Protein-Coupled Receptors.
Cell
2017; 170 (3): 457–69.e13
Abstract
G protein-coupled receptors (GPCRs) mediate diverse signaling in part through interaction with arrestins, whose binding promotes receptor internalization and signaling through G protein-independent pathways. High-affinity arrestin binding requires receptor phosphorylation, often at the receptor's C-terminal tail. Here, we report an X-ray free electron laser (XFEL) crystal structure of the rhodopsin-arrestin complex, in which the phosphorylated C terminus of rhodopsin forms an extended intermolecular β sheet with the N-terminal β strands of arrestin. Phosphorylation was detected at rhodopsin C-terminal tail residues T336 and S338. These two phospho-residues, together with E341, form an extensive network of electrostatic interactions with three positively charged pockets in arrestin in a mode that resembles binding of the phosphorylated vasopressin-2 receptor tail to β-arrestin-1. Based on these observations, we derived and validated a set of phosphorylation codes that serve as a common mechanism for phosphorylation-dependent recruitment of arrestins by GPCRs.
View details for PubMedID 28753425
View details for PubMedCentralID PMC5567868
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Mechanism of intracellular allosteric β2AR antagonist revealed by X-ray crystal structure.
Nature
2017; 548 (7668): 480–84
Abstract
G-protein-coupled receptors (GPCRs) pose challenges for drug discovery efforts because of the high degree of structural homology in the orthosteric pocket, particularly for GPCRs within a single subfamily, such as the nine adrenergic receptors. Allosteric ligands may bind to less-conserved regions of these receptors and therefore are more likely to be selective. Unlike orthosteric ligands, which tonically activate or inhibit signalling, allosteric ligands modulate physiologic responses to hormones and neurotransmitters, and may therefore have fewer adverse effects. The majority of GPCR crystal structures published to date were obtained with receptors bound to orthosteric antagonists, and only a few structures bound to allosteric ligands have been reported. Compound 15 (Cmpd-15) is an allosteric modulator of the β2 adrenergic receptor (β2AR) that was recently isolated from a DNA-encoded small-molecule library. Orthosteric β-adrenergic receptor antagonists, known as beta-blockers, are amongst the most prescribed drugs in the world and Cmpd-15 is the first allosteric beta-blocker. Cmpd-15 exhibits negative cooperativity with agonists and positive cooperativity with inverse agonists. Here we present the structure of the β2AR bound to a polyethylene glycol-carboxylic acid derivative (Cmpd-15PA) of this modulator. Cmpd-15PA binds to a pocket formed primarily by the cytoplasmic ends of transmembrane segments 1, 2, 6 and 7 as well as intracellular loop 1 and helix 8. A comparison of this structure with inactive- and active-state structures of the β2AR reveals the mechanism by which Cmpd-15 modulates agonist binding affinity and signalling.
View details for PubMedID 28813418
- Mechanism of intracellular allosteric β2AR antagonist revealed by X-ray crystal structure Nature 2017: 480-484
- D4 dopamine receptor high-resolution structures enable the discovery of selective agonists Science 2017: 381-386
- Structural and functional analysis of a β2-adrenergic receptor complex with GRK5 Cell 2017: 407-421
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Crystal Structure of a Full-Length Human Tetraspanin Reveals a Cholesterol-Binding Pocket
CELL
2016; 167 (4): 1041-?
Abstract
Tetraspanins comprise a diverse family of four-pass transmembrane proteins that play critical roles in the immune, reproductive, genitourinary, and auditory systems. Despite their pervasive roles in human physiology, little is known about the structure of tetraspanins or the molecular mechanisms underlying their various functions. Here, we report the crystal structure of human CD81, a full-length tetraspanin. The transmembrane segments of CD81 pack as two largely separated pairs of helices, capped by the large extracellular loop (EC2) at the outer membrane leaflet. The two pairs of helices converge at the inner leaflet to create an intramembrane pocket with additional electron density corresponding to a bound cholesterol molecule within the cavity. Molecular dynamics simulations identify an additional conformation in which EC2 separates substantially from the transmembrane domain. Cholesterol binding appears to modulate CD81 activity in cells, suggesting a potential mechanism for regulation of tetraspanin function.
View details for DOI 10.1016/j.cell.2016.09.056
View details for Web of Science ID 000389469000020
View details for PubMedID 27881302
View details for PubMedCentralID PMC5127602
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Revealing Atomic-Level Mechanisms of Protein Allostery with Molecular Dynamics Simulations
PLOS COMPUTATIONAL BIOLOGY
2016; 12 (6)
Abstract
Molecular dynamics (MD) simulations have become a powerful and popular method for the study of protein allostery, the widespread phenomenon in which a stimulus at one site on a protein influences the properties of another site on the protein. By capturing the motions of a protein's constituent atoms, simulations can enable the discovery of allosteric binding sites and the determination of the mechanistic basis for allostery. These results can provide a foundation for applications including rational drug design and protein engineering. Here, we provide an introduction to the investigation of protein allostery using molecular dynamics simulation. We emphasize the importance of designing simulations that include appropriate perturbations to the molecular system, such as the addition or removal of ligands or the application of mechanical force. We also demonstrate how the bidirectional nature of allostery-the fact that the two sites involved influence one another in a symmetrical manner-can facilitate such investigations. Through a series of case studies, we illustrate how these concepts have been used to reveal the structural basis for allostery in several proteins and protein complexes of biological and pharmaceutical interest.
View details for DOI 10.1371/journal.pcbi.1004746
View details for Web of Science ID 000379349700002
View details for PubMedID 27285999
View details for PubMedCentralID PMC4902200
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Molecular Basis of Ligand Dissociation from the Adenosine A(2A) Receptor
MOLECULAR PHARMACOLOGY
2016; 89 (5): 485-491
Abstract
How drugs dissociate from their targets is largely unknown. We investigated the molecular basis of this process in the adenosine A2Areceptor (A2AR), a prototypical G protein-coupled receptor (GPCR). Through kinetic radioligand binding experiments, we characterized mutant receptors selected based on molecular dynamic simulations of the antagonist ZM241385 dissociating from the A2AR. We discovered mutations that dramatically altered the ligand's dissociation rate despite only marginally influencing its binding affinity, demonstrating that even receptor features with little contribution to affinity may prove critical to the dissociation process. Our results also suggest that ZM241385 follows a multistep dissociation pathway, consecutively interacting with distinct receptor regions, a mechanism that may also be common to many other GPCRs.
View details for DOI 10.1124/mol.115.102657
View details for Web of Science ID 000374963400001
View details for PubMedID 26873858
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Structural insights into mu-opioid receptor activation
NATURE
2015; 524 (7565): 315-?
Abstract
Activation of the μ-opioid receptor (μOR) is responsible for the efficacy of the most effective analgesics. To shed light on the structural basis for μOR activation, here we report a 2.1 Å X-ray crystal structure of the murine μOR bound to the morphinan agonist BU72 and a G protein mimetic camelid antibody fragment. The BU72-stabilized changes in the μOR binding pocket are subtle and differ from those observed for agonist-bound structures of the β2-adrenergic receptor (β2AR) and the M2 muscarinic receptor. Comparison with active β2AR reveals a common rearrangement in the packing of three conserved amino acids in the core of the μOR, and molecular dynamics simulations illustrate how the ligand-binding pocket is conformationally linked to this conserved triad. Additionally, an extensive polar network between the ligand-binding pocket and the cytoplasmic domains appears to play a similar role in signal propagation for all three G-protein-coupled receptors.
View details for DOI 10.1038/nature14886
View details for Web of Science ID 000359714000028
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Structural basis for nucleotide exchange in heterotrimeric G proteins
SCIENCE
2015; 348 (6241): 1361-1365
Abstract
G protein-coupled receptors (GPCRs) relay diverse extracellular signals into cells by catalyzing nucleotide release from heterotrimeric G proteins, but the mechanism underlying this quintessential molecular signaling event has remained unclear. Here we use atomic-level simulations to elucidate the nucleotide-release mechanism. We find that the G protein α subunit Ras and helical domains-previously observed to separate widely upon receptor binding to expose the nucleotide-binding site-separate spontaneously and frequently even in the absence of a receptor. Domain separation is necessary but not sufficient for rapid nucleotide release. Rather, receptors catalyze nucleotide release by favoring an internal structural rearrangement of the Ras domain that weakens its nucleotide affinity. We use double electron-electron resonance spectroscopy and protein engineering to confirm predictions of our computationally determined mechanism.
View details for DOI 10.1126/science.aaa5264
View details for Web of Science ID 000356449500051
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Identifying localized changes in large systems: Change-point detection for biomolecular simulations
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2015; 112 (24): 7454-7459
Abstract
Research on change-point detection, the classical problem of detecting abrupt changes in sequential data, has focused predominantly on datasets with a single observable. A growing number of time series datasets, however, involve many observables, often with the property that a given change typically affects only a few of the observables. We introduce a general statistical method that, given many noisy observables, detects points in time at which various subsets of the observables exhibit simultaneous changes in data distribution and explicitly identifies those subsets. Our work is motivated by the problem of identifying the nature and timing of biologically interesting conformational changes that occur during atomic-level simulations of biomolecules such as proteins. This problem has proved challenging both because each such conformational change might involve only a small region of the molecule and because these changes are often subtle relative to the ever-present background of faster structural fluctuations. We show that our method is effective in detecting biologically interesting conformational changes in molecular dynamics simulations of both folded and unfolded proteins, even in cases where these changes are difficult to detect using alternative techniques. This method may also facilitate the detection of change points in other types of sequential data involving large numbers of observables-a problem likely to become increasingly important as such data continue to proliferate in a variety of application domains.
View details for DOI 10.1073/pnas.1415846112
View details for Web of Science ID 000356251800044
View details for PubMedID 26025225
View details for PubMedCentralID PMC4475967
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Structural basis for chemokine recognition and activation of a viral G protein-coupled receptor
SCIENCE
2015; 347 (6226): 1113-1117
Abstract
Chemokines are small proteins that function as immune modulators through activation of chemokine G protein-coupled receptors (GPCRs). Several viruses also encode chemokines and chemokine receptors to subvert the host immune response. How protein ligands activate GPCRs remains unknown. We report the crystal structure at 2.9 angstrom resolution of the human cytomegalovirus GPCR US28 in complex with the chemokine domain of human CX3CL1 (fractalkine). The globular body of CX3CL1 is perched on top of the US28 extracellular vestibule, whereas its amino terminus projects into the central core of US28. The transmembrane helices of US28 adopt an active-state-like conformation. Atomic-level simulations suggest that the agonist-independent activity of US28 may be due to an amino acid network evolved in the viral GPCR to destabilize the receptor's inactive state.
View details for DOI 10.1126/science.aaa5026
View details for Web of Science ID 000350354200046
View details for PubMedCentralID PMC4445376
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Insights into the Role of Asp79(2.50) in beta(2) Adrenergic Receptor Activation from Molecular Dynamics Simulations
BIOCHEMISTRY
2014; 53 (46): 7283-7296
Abstract
Achieving a molecular-level understanding of G-protein-coupled receptor (GPCR) activation has been a long-standing goal in biology and could be important for the development of novel drugs. Recent breakthroughs in structural biology have led to the determination of high-resolution crystal structures for the β2 adrenergic receptor (β2AR) in inactive and active states, which provided an unprecedented opportunity to understand receptor signaling at the atomic level. We used molecular dynamics (MD) simulations to explore the potential roles of ionizable residues in β2AR activation. One such residue is the strongly conserved Asp79(2.50), which is buried in a transmembrane cavity and becomes dehydrated upon β2AR activation. MD free energy calculations based on β2AR crystal structures suggested an increase in the population of the protonated state of Asp79(2.50) upon activation, which may contribute to the experimentally observed pH-dependent activation of this receptor. Analysis of MD simulations (in total > 100 μs) with two different protonation states further supported the conclusion that the protonated Asp79(2.50) shifts the conformation of the β2AR toward more active-like states. On the basis of our calculations and analysis of other GPCR crystal structures, we suggest that the protonation state of Asp(2.50) may act as a functionally important microswitch in the activation of the β2AR and other class A receptors.
View details for DOI 10.1021/bi5008723
View details for Web of Science ID 000345551800013
View details for PubMedID 25347607
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Anton 2: Raising the bar for performance and programmability in a special-purpose molecular dynamics supercomputer
SC14: INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE AND ANALYSIS
2014: 41-53
View details for DOI 10.1109/SC.2014.9
View details for Web of Science ID 000393484400004
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The role of ligands on the equilibria between functional States of a g protein-coupled receptor.
Journal of the American Chemical Society
2013; 135 (25): 9465-9474
Abstract
G protein-coupled receptors exhibit a wide variety of signaling behaviors in response to different ligands. When a small label was incorporated on the cytosolic interface of transmembrane helix 6 (Cys-265), (19)F NMR spectra of the β2 adrenergic receptor (β2AR) reconstituted in maltose/neopentyl glycol detergent micelles revealed two distinct inactive states, an activation intermediate state en route to activation, and, in the presence of a G protein mimic, a predominant active state. Analysis of the spectra as a function of temperature revealed that for all ligands, the activation intermediate is entropically favored and enthalpically disfavored. β2AR enthalpy changes toward activation are notably lower than those observed with rhodopsin, a likely consequence of basal activity and the fact that the ionic lock and other interactions stabilizing the inactive state of β2AR are weaker. Positive entropy changes toward activation likely reflect greater mobility (configurational entropy) in the cytoplasmic domain, as confirmed through an order parameter analysis. Ligands greatly influence the overall changes in enthalpy and entropy of the system and the corresponding changes in population and amplitude of motion of given states, suggesting a complex landscape of states and substates.
View details for DOI 10.1021/ja404305k
View details for PubMedID 23721409
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Hardware Support for Fine-Grained Event-Driven Computation in Anton 2
ACM SIGPLAN NOTICES
2013; 48 (4): 549-560
View details for Web of Science ID 000321213100045
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The Dynamic Process of beta(2)-Adrenergic Receptor Activation
CELL
2013; 152 (3): 532-542
Abstract
G-protein-coupled receptors (GPCRs) can modulate diverse signaling pathways, often in a ligand-specific manner. The full range of functionally relevant GPCR conformations is poorly understood. Here, we use NMR spectroscopy to characterize the conformational dynamics of the transmembrane core of the β(2)-adrenergic receptor (β(2)AR), a prototypical GPCR. We labeled β(2)AR with (13)CH(3)ε-methionine and obtained HSQC spectra of unliganded receptor as well as receptor bound to an inverse agonist, an agonist, and a G-protein-mimetic nanobody. These studies provide evidence for conformational states not observed in crystal structures, as well as substantial conformational heterogeneity in agonist- and inverse-agonist-bound preparations. They also show that for β(2)AR, unlike rhodopsin, an agonist alone does not stabilize a fully active conformation, suggesting that the conformational link between the agonist-binding pocket and the G-protein-coupling surface is not rigid. The observed heterogeneity may be important for β(2)AR's ability to engage multiple signaling and regulatory proteins.
View details for DOI 10.1016/j.cell.2013.01.008
View details for Web of Science ID 000314362800022
View details for PubMedID 23374348
View details for PubMedCentralID PMC3586676
- The dynamic process of β2-adrenergic receptor activation Cell 2013: 532-542
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Extending the generality of molecular dynamics simulations on a special-purpose machine
IEEE 27TH INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM (IPDPS 2013)
2013: 933-945
View details for DOI 10.1109/IPDPS.2013.93
View details for Web of Science ID 000332828000081
- Structural basis for modulation of a GPCR by allosteric drugs Nature 2013: 295-299
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High-resolution crystal structure of human protease-activated receptor 1
NATURE
2012; 492 (7429): 387-?
Abstract
Protease-activated receptor 1 (PAR1) is the prototypical member of a family of G-protein-coupled receptors that mediate cellular responses to thrombin and related proteases. Thrombin irreversibly activates PAR1 by cleaving the amino-terminal exodomain of the receptor, which exposes a tethered peptide ligand that binds the heptahelical bundle of the receptor to affect G-protein activation. Here we report the 2.2 Å resolution crystal structure of human PAR1 bound to vorapaxar, a PAR1 antagonist. The structure reveals an unusual mode of drug binding that explains how a small molecule binds virtually irreversibly to inhibit receptor activation by the tethered ligand of PAR1. In contrast to deep, solvent-exposed binding pockets observed in other peptide-activated G-protein-coupled receptors, the vorapaxar-binding pocket is superficial but has little surface exposed to the aqueous solvent. Protease-activated receptors are important targets for drug development. The structure reported here will aid the development of improved PAR1 antagonists and the discovery of antagonists to other members of this receptor family.
View details for DOI 10.1038/nature11701
View details for Web of Science ID 000312488200047
View details for PubMedID 23222541
View details for PubMedCentralID PMC3531875
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Refinement of protein structure homology models via long, all-atom molecular dynamics simulations
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
2012; 80 (8): 2071-2079
Abstract
Accurate computational prediction of protein structure represents a longstanding challenge in molecular biology and structure-based drug design. Although homology modeling techniques are widely used to produce low-resolution models, refining these models to high resolution has proven difficult. With long enough simulations and sufficiently accurate force fields, molecular dynamics (MD) simulations should in principle allow such refinement, but efforts to refine homology models using MD have for the most part yielded disappointing results. It has thus far been unclear whether MD-based refinement is limited primarily by accessible simulation timescales, force field accuracy, or both. Here, we examine MD as a technique for homology model refinement using all-atom simulations, each at least 100 μs long-more than 100 times longer than previous refinement simulations-and a physics-based force field that was recently shown to successfully fold a structurally diverse set of fast-folding proteins. In MD simulations of 24 proteins chosen from the refinement category of recent Critical Assessment of Structure Prediction (CASP) experiments, we find that in most cases, simulations initiated from homology models drift away from the native structure. Comparison with simulations initiated from the native structure suggests that force field accuracy is the primary factor limiting MD-based refinement. This problem can be mitigated to some extent by restricting sampling to the neighborhood of the initial model, leading to structural improvement that, while limited, is roughly comparable to the leading alternative methods.
View details for DOI 10.1002/prot.24098
View details for Web of Science ID 000306132400014
View details for PubMedID 22513870
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Evaluating the Effects of Cutoffs and Treatment of Long-range Electrostatics in Protein Folding Simulations
PLOS ONE
2012; 7 (6)
Abstract
The use of molecular dynamics simulations to provide atomic-level descriptions of biological processes tends to be computationally demanding, and a number of approximations are thus commonly employed to improve computational efficiency. In the past, the effect of these approximations on macromolecular structure and stability has been evaluated mostly through quantitative studies of small-molecule systems or qualitative observations of short-timescale simulations of biological macromolecules. Here we present a quantitative evaluation of two commonly employed approximations, using a test system that has been the subject of a number of previous protein folding studies--the villin headpiece. In particular, we examined the effect of (i) the use of a cutoff-based force-shifting technique rather than an Ewald summation for the treatment of electrostatic interactions, and (ii) the length of the cutoff used to determine how many pairwise interactions are included in the calculation of both electrostatic and van der Waals forces. Our results show that the free energy of folding is relatively insensitive to the choice of cutoff beyond 9 Å, and to whether an Ewald method is used to account for long-range electrostatic interactions. In contrast, we find that the structural properties of the unfolded state depend more strongly on the two approximations examined here.
View details for DOI 10.1371/journal.pone.0039918
View details for Web of Science ID 000305892100138
View details for PubMedID 22768169
View details for PubMedCentralID PMC3386949
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Oncogenic Mutations Counteract Intrinsic Disorder in the EGFR Kinase and Promote Receptor Dimerization
CELL
2012; 149 (4): 860-870
Abstract
The mutation and overexpression of the epidermal growth factor receptor (EGFR) are associated with the development of a variety of cancers, making this prototypical dimerization-activated receptor tyrosine kinase a prominent target of cancer drugs. Using long-timescale molecular dynamics simulations, we find that the N lobe dimerization interface of the wild-type EGFR kinase domain is intrinsically disordered and that it becomes ordered only upon dimerization. Our simulations suggest, moreover, that some cancer-linked mutations distal to the dimerization interface, particularly the widespread L834R mutation (also referred to as L858R), facilitate EGFR dimerization by suppressing this local disorder. Corroborating these findings, our biophysical experiments and kinase enzymatic assays indicate that the L834R mutation causes abnormally high activity primarily by promoting EGFR dimerization rather than by allowing activation without dimerization. We also find that phosphorylation of EGFR kinase domain at Tyr845 may suppress the intrinsic disorder, suggesting a molecular mechanism for autonomous EGFR signaling.
View details for DOI 10.1016/j.cell.2012.02.063
View details for Web of Science ID 000303934700018
View details for PubMedID 22579287
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Structure and dynamics of the M3 muscarinic acetylcholine receptor
NATURE
2012; 482 (7386): 552-556
Abstract
Acetylcholine, the first neurotransmitter to be identified, exerts many of its physiological actions via activation of a family of G-protein-coupled receptors (GPCRs) known as muscarinic acetylcholine receptors (mAChRs). Although the five mAChR subtypes (M1-M5) share a high degree of sequence homology, they show pronounced differences in G-protein coupling preference and the physiological responses they mediate. Unfortunately, despite decades of effort, no therapeutic agents endowed with clear mAChR subtype selectivity have been developed to exploit these differences. We describe here the structure of the G(q/11)-coupled M3 mAChR ('M3 receptor', from rat) bound to the bronchodilator drug tiotropium and identify the binding mode for this clinically important drug. This structure, together with that of the G(i/o)-coupled M2 receptor, offers possibilities for the design of mAChR subtype-selective ligands. Importantly, the M3 receptor structure allows a structural comparison between two members of a mammalian GPCR subfamily displaying different G-protein coupling selectivities. Furthermore, molecular dynamics simulations suggest that tiotropium binds transiently to an allosteric site en route to the binding pocket of both receptors. These simulations offer a structural view of an allosteric binding mode for an orthosteric GPCR ligand and provide additional opportunities for the design of ligands with different affinities or binding kinetics for different mAChR subtypes. Our findings not only offer insights into the structure and function of one of the most important GPCR families, but may also facilitate the design of improved therapeutics targeting these critical receptors.
View details for DOI 10.1038/nature10867
View details for Web of Science ID 000300770500056
View details for PubMedID 22358844
View details for PubMedCentralID PMC3529910
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Systematic Validation of Protein Force Fields against Experimental Data
PLOS ONE
2012; 7 (2)
Abstract
Molecular dynamics simulations provide a vehicle for capturing the structures, motions, and interactions of biological macromolecules in full atomic detail. The accuracy of such simulations, however, is critically dependent on the force field--the mathematical model used to approximate the atomic-level forces acting on the simulated molecular system. Here we present a systematic and extensive evaluation of eight different protein force fields based on comparisons of experimental data with molecular dynamics simulations that reach a previously inaccessible timescale. First, through extensive comparisons with experimental NMR data, we examined the force fields' abilities to describe the structure and fluctuations of folded proteins. Second, we quantified potential biases towards different secondary structure types by comparing experimental and simulation data for small peptides that preferentially populate either helical or sheet-like structures. Third, we tested the force fields' abilities to fold two small proteins--one α-helical, the other with β-sheet structure. The results suggest that force fields have improved over time, and that the most recent versions, while not perfect, provide an accurate description of many structural and dynamical properties of proteins.
View details for DOI 10.1371/journal.pone.0032131
View details for Web of Science ID 000302875500077
View details for PubMedID 22384157
View details for PubMedCentralID PMC3285199
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Biomolecular Simulation: A Computational Microscope for Molecular Biology
ANNUAL REVIEW OF BIOPHYSICS, VOL 41
2012; 41: 429-452
Abstract
Molecular dynamics simulations capture the behavior of biological macromolecules in full atomic detail, but their computational demands, combined with the challenge of appropriately modeling the relevant physics, have historically restricted their length and accuracy. Dramatic recent improvements in achievable simulation speed and the underlying physical models have enabled atomic-level simulations on timescales as long as milliseconds that capture key biochemical processes such as protein folding, drug binding, membrane transport, and the conformational changes critical to protein function. Such simulation may serve as a computational microscope, revealing biomolecular mechanisms at spatial and temporal scales that are difficult to observe experimentally. We describe the rapidly evolving state of the art for atomic-level biomolecular simulation, illustrate the types of biological discoveries that can now be made through simulation, and discuss challenges motivating continued innovation in this field.
View details for DOI 10.1146/annurev-biophys-042910-155245
View details for Web of Science ID 000307955100020
View details for PubMedID 22577825
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Computationally efficient molecular dynamics integrators with improved sampling accuracy
MOLECULAR PHYSICS
2012; 110 (9-10): 967-983
View details for DOI 10.1080/00268976.2012.681311
View details for Web of Science ID 000304474700041
- Mechanism of voltage gating in K+ channels Science 2012: 229-233
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How Fast-Folding Proteins Fold
SCIENCE
2011; 334 (6055): 517-520
Abstract
An outstanding challenge in the field of molecular biology has been to understand the process by which proteins fold into their characteristic three-dimensional structures. Here, we report the results of atomic-level molecular dynamics simulations, over periods ranging between 100 μs and 1 ms, that reveal a set of common principles underlying the folding of 12 structurally diverse proteins. In simulations conducted with a single physics-based energy function, the proteins, representing all three major structural classes, spontaneously and repeatedly fold to their experimentally determined native structures. Early in the folding process, the protein backbone adopts a nativelike topology while certain secondary structure elements and a small number of nonlocal contacts form. In most cases, folding follows a single dominant route in which elements of the native structure appear in an order highly correlated with their propensity to form in the unfolded state.
View details for DOI 10.1126/science.1208351
View details for Web of Science ID 000296230500048
View details for PubMedID 22034434
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Pathway and mechanism of drug binding to G-protein-coupled receptors
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2011; 108 (32): 13118-13123
Abstract
How drugs bind to their receptors--from initial association, through drug entry into the binding pocket, to adoption of the final bound conformation, or "pose"--has remained unknown, even for G-protein-coupled receptor modulators, which constitute one-third of all marketed drugs. We captured this pharmaceutically critical process in atomic detail using the first unbiased molecular dynamics simulations in which drug molecules spontaneously associate with G-protein-coupled receptors to achieve final poses matching those determined crystallographically. We found that several beta blockers and a beta agonist all traverse the same well-defined, dominant pathway as they bind to the β(1)- and β(2)-adrenergic receptors, initially making contact with a vestibule on each receptor's extracellular surface. Surprisingly, association with this vestibule, at a distance of 15 Å from the binding pocket, often presents the largest energetic barrier to binding, despite the fact that subsequent entry into the binding pocket requires the receptor to deform and the drug to squeeze through a narrow passage. The early barrier appears to reflect the substantial dehydration that takes place as the drug associates with the vestibule. Our atomic-level description of the binding process suggests opportunities for allosteric modulation and provides a structural foundation for future optimization of drug-receptor binding and unbinding rates.
View details for DOI 10.1073/pnas.1104614108
View details for Web of Science ID 000293691400036
View details for PubMedID 21778406
View details for PubMedCentralID PMC3156183
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How Does a Drug Molecule Find Its Target Binding Site?
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
2011; 133 (24): 9181-9183
Abstract
Although the thermodynamic principles that control the binding of drug molecules to their protein targets are well understood, detailed experimental characterization of the process by which such binding occurs has proven challenging. We conducted relatively long, unguided molecular dynamics simulations in which a ligand (the cancer drug dasatinib or the kinase inhibitor PP1) was initially placed at a random location within a box that also contained a protein (Src kinase) to which that ligand was known to bind. In several of these simulations, the ligand correctly identified its target binding site, forming a complex virtually identical to the crystallographically determined bound structure. The simulated trajectories provide a continuous, atomic-level view of the entire binding process, revealing persistent and noteworthy intermediate conformations and shedding light on the role of water molecules. The technique we employed, which does not assume any prior knowledge of the binding site's location, may prove particularly useful in the development of allosteric inhibitors that target previously undiscovered binding sites.
View details for DOI 10.1021/ja202726y
View details for Web of Science ID 000291915100013
View details for PubMedID 21545110
View details for PubMedCentralID PMC3221467
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OVERCOMING COMMUNICATION LATENCY BARRIERS IN MASSIVELY PARALLEL SCIENTIFIC COMPUTATION
IEEE MICRO
2011; 31 (3): 8-19
View details for Web of Science ID 000291445700002
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Structure and function of an irreversible agonist-beta(2) adrenoceptor complex
NATURE
2011; 469 (7329): 236-240
Abstract
G-protein-coupled receptors (GPCRs) are eukaryotic integral membrane proteins that modulate biological function by initiating cellular signalling in response to chemically diverse agonists. Despite recent progress in the structural biology of GPCRs, the molecular basis for agonist binding and allosteric modulation of these proteins is poorly understood. Structural knowledge of agonist-bound states is essential for deciphering the mechanism of receptor activation, and for structure-guided design and optimization of ligands. However, the crystallization of agonist-bound GPCRs has been hampered by modest affinities and rapid off-rates of available agonists. Using the inactive structure of the human β(2) adrenergic receptor (β(2)AR) as a guide, we designed a β(2)AR agonist that can be covalently tethered to a specific site on the receptor through a disulphide bond. The covalent β(2)AR-agonist complex forms efficiently, and is capable of activating a heterotrimeric G protein. We crystallized a covalent agonist-bound β(2)AR-T4L fusion protein in lipid bilayers through the use of the lipidic mesophase method, and determined its structure at 3.5 Å resolution. A comparison to the inactive structure and an antibody-stabilized active structure (companion paper) shows how binding events at both the extracellular and intracellular surfaces are required to stabilize an active conformation of the receptor. The structures are in agreement with long-timescale (up to 30 μs) molecular dynamics simulations showing that an agonist-bound active conformation spontaneously relaxes to an inactive-like conformation in the absence of a G protein or stabilizing antibody.
View details for DOI 10.1038/nature09665
View details for Web of Science ID 000286143400043
View details for PubMedID 21228876
View details for PubMedCentralID PMC3074335
- Activation mechanism of the β2-adrenergic receptor Proceedings of the National Academy of Sciences of the United States of America 2011: 18684-18689
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Radix-8 Digit-by-Rounding: Achieving High-Performance Reciprocals, Square Roots, and Reciprocal Square Roots
2011 20TH IEEE SYMPOSIUM ON COMPUTER ARITHMETIC (ARITH-20)
2011: 149-158
View details for DOI 10.1109/ARITH.2011.28
View details for Web of Science ID 000296333300018
- Structure and function of an irreversible agonist–β2 adrenoceptor complex Nature 2011: 236-240
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Atomic-Level Characterization of the Structural Dynamics of Proteins
SCIENCE
2010; 330 (6002): 341-346
Abstract
Molecular dynamics (MD) simulations are widely used to study protein motions at an atomic level of detail, but they have been limited to time scales shorter than those of many biologically critical conformational changes. We examined two fundamental processes in protein dynamics--protein folding and conformational change within the folded state--by means of extremely long all-atom MD simulations conducted on a special-purpose machine. Equilibrium simulations of a WW protein domain captured multiple folding and unfolding events that consistently follow a well-defined folding pathway; separate simulations of the protein's constituent substructures shed light on possible determinants of this pathway. A 1-millisecond simulation of the folded protein BPTI reveals a small number of structurally distinct conformational states whose reversible interconversion is slower than local relaxations within those states by a factor of more than 1000.
View details for DOI 10.1126/science.1187409
View details for Web of Science ID 000282986700033
View details for PubMedID 20947758
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Equipartition and the Calculation of Temperature in Biomolecular Simulations
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
2010; 6 (7): 2045-2058
Abstract
Since the behavior of biomolecules can be sensitive to temperature, the ability to accurately calculate and control the temperature in molecular dynamics (MD) simulations is important. Standard analysis of equilibrium MD simulations-even constant-energy simulations with negligible long-term energy drift-often yields different calculated temperatures for different motions, however, in apparent violation of the statistical mechanical principle of equipartition of energy. Although such analysis provides a valuable warning that other simulation artifacts may exist, it leaves the actual value of the temperature uncertain. We observe that Tolman's generalized equipartition theorem should hold for long stable simulations performed using velocity-Verlet or other symplectic integrators, because the simulated trajectory is thought to sample almost exactly from a continuous trajectory generated by a shadow Hamiltonian. From this we conclude that all motions should share a single simulation temperature, and we provide a new temperature estimator that we test numerically in simulations of a diatomic fluid and of a solvated protein. Apparent temperature variations between different motions observed using standard estimators do indeed disappear when using the new estimator. We use our estimator to better understand how thermostats and barostats can exacerbate integration errors. In particular, we find that with large (albeit widely used) time steps, the common practice of using two thermostats to remedy so-called hot solvent-cold solute problems can have the counterintuitive effect of causing temperature imbalances. Our results, moreover, highlight the utility of multiple-time step integrators for accurate and efficient simulation.
View details for DOI 10.1021/ct9002916
View details for Web of Science ID 000279751500014
View details for PubMedID 26615934
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Exploring atomic resolution physiology on a femtosecond to millisecond timescale using molecular dynamics simulations
JOURNAL OF GENERAL PHYSIOLOGY
2010; 135 (6): 555-562
View details for DOI 10.1085/jgp.200910373
View details for Web of Science ID 000278186500003
View details for PubMedID 20513757
View details for PubMedCentralID PMC2888062
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Improved side-chain torsion potentials for the Amber ff99SB protein force field
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
2010; 78 (8): 1950-1958
Abstract
Recent advances in hardware and software have enabled increasingly long molecular dynamics (MD) simulations of biomolecules, exposing certain limitations in the accuracy of the force fields used for such simulations and spurring efforts to refine these force fields. Recent modifications to the Amber and CHARMM protein force fields, for example, have improved the backbone torsion potentials, remedying deficiencies in earlier versions. Here, we further advance simulation accuracy by improving the amino acid side-chain torsion potentials of the Amber ff99SB force field. First, we used simulations of model alpha-helical systems to identify the four residue types whose rotamer distribution differed the most from expectations based on Protein Data Bank statistics. Second, we optimized the side-chain torsion potentials of these residues to match new, high-level quantum-mechanical calculations. Finally, we used microsecond-timescale MD simulations in explicit solvent to validate the resulting force field against a large set of experimental NMR measurements that directly probe side-chain conformations. The new force field, which we have termed Amber ff99SB-ILDN, exhibits considerably better agreement with the NMR data.
View details for DOI 10.1002/prot.22711
View details for Web of Science ID 000277767700012
View details for PubMedID 20408171
View details for PubMedCentralID PMC2970904
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Principles of conduction and hydrophobic gating in K+ channels
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2010; 107 (13): 5833-5838
Abstract
We present the first atomic-resolution observations of permeation and gating in a K(+) channel, based on molecular dynamics simulations of the Kv1.2 pore domain. Analysis of hundreds of simulated permeation events revealed a detailed conduction mechanism, resembling the Hodgkin-Keynes "knock-on" model, in which translocation of two selectivity filter-bound ions is driven by a third ion; formation of this knock-on intermediate is rate determining. In addition, at reverse or zero voltages, we observed pore closure by a novel "hydrophobic gating" mechanism: A dewetting transition of the hydrophobic pore cavity-fastest when K(+) was not bound in selectivity filter sites nearest the cavity-caused the open, conducting pore to collapse into a closed, nonconducting conformation. Such pore closure corroborates the idea that voltage sensors can act to prevent pore collapse into the intrinsically more stable, closed conformation, and it further suggests that molecular-scale dewetting facilitates a specific biological function: K(+) channel gating. Existing experimental data support our hypothesis that hydrophobic gating may be a fundamental principle underlying the gating of voltage-sensitive K(+) channels. We suggest that hydrophobic gating explains, in part, why diverse ion channels conserve hydrophobic pore cavities, and we speculate that modulation of cavity hydration could enable structural determination of both open and closed channels.
View details for DOI 10.1073/pnas.0911691107
View details for Web of Science ID 000276159500027
View details for PubMedID 20231479
View details for PubMedCentralID PMC2851896
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Improved Twiddle Access for Fast Fourier Transforms
IEEE TRANSACTIONS ON SIGNAL PROCESSING
2010; 58 (3): 1122-1130
View details for DOI 10.1109/TSP.2009.2035984
View details for Web of Science ID 000274472600015
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Minimizing thermodynamic length to select intermediate states for free-energy calculations and replica-exchange simulations (vol 80, 046705, 2009)
PHYSICAL REVIEW E
2009; 80 (4)
View details for DOI 10.1103/PhysRevE.80.049904
View details for Web of Science ID 000271350700119
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Automated Event Detection and Activity Monitoring in Long Molecular Dynamics Simulations
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
2009; 5 (10): 2595-2605
Abstract
Events of scientific interest in molecular dynamics (MD) simulations, including conformational changes, folding transitions, and translocations of ligands and reaction products, often correspond to high-level structural rearrangements that alter contacts between molecules or among different parts of a molecule. Due to advances in computer architecture and software, MD trajectories representing such structure-changing events have become easier to generate, but the length of these trajectories poses a challenge to scientific interpretation and analysis. In this paper, we present automated methods for the detection of potentially important structure-changing events in long MD trajectories. In contrast with traditional tools for the analysis of such trajectories, our methods provide a detailed report of broken and formed contacts that aids in the identification of specific time-dependent side-chain interactions. Our approach employs a coarse-grained representation of amino acid side chains, a contact metric based on higher order generalizations of Delaunay tetrahedralization, techniques for detecting significant shifts in the resulting contact time series, and a new kernel-based measure of contact alteration activity. The analysis methods we describe are incorporated in a newly developed package, called TimeScapes, which is freely available and compatible with trajectories generated by a variety of popular MD programs. Tests based on actual microsecond time scale simulations demonstrate that the package can be used to efficiently detect and characterize important conformational changes in realistic protein systems.
View details for DOI 10.1021/ct900229u
View details for Web of Science ID 000270595800003
View details for PubMedID 26631775
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Long-timescale molecular dynamics simulations of protein structure and function
CURRENT OPINION IN STRUCTURAL BIOLOGY
2009; 19 (2): 120-127
Abstract
Molecular dynamics simulations allow for atomic-level characterization of biomolecular processes such as the conformational transitions associated with protein function. The computational demands of such simulations, however, have historically prevented them from reaching the microsecond and greater timescales on which these events often occur. Recent advances in algorithms, software, and computer hardware have made microsecond-timescale simulations with tens of thousands of atoms practical, with millisecond-timescale simulations on the horizon. This review outlines these advances in high-performance molecular dynamics simulation and discusses recent applications to studies of protein dynamics and function as well as experimental validation of the underlying computational models.
View details for DOI 10.1016/j.sbi.2009.03.004
View details for Web of Science ID 000266114000002
View details for PubMedID 19361980
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A conserved protonation-dependent switch controls drug binding in the Abl kinase
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2009; 106 (1): 139-144
Abstract
In many protein kinases, a characteristic conformational change (the "DFG flip") connects catalytically active and inactive conformations. Many kinase inhibitors--including the cancer drug imatinib--selectively target a specific DFG conformation, but the function and mechanism of the flip remain unclear. Using long molecular dynamics simulations of the Abl kinase, we visualized the DFG flip in atomic-level detail and formulated an energetic model predicting that protonation of the DFG aspartate controls the flip. Consistent with our model's predictions, we demonstrated experimentally that the kinetics of imatinib binding to Abl kinase have a pH dependence that disappears when the DFG aspartate is mutated. Our model suggests a possible explanation for the high degree of conservation of the DFG motif: that the flip, modulated by electrostatic changes inherent to the catalytic cycle, allows the kinase to access flexible conformations facilitating nucleotide binding and release.
View details for DOI 10.1073/pnas.0811223106
View details for Web of Science ID 000262263900028
View details for PubMedID 19109437
View details for PubMedCentralID PMC2610013
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Elucidating membrane protein function through long-timescale molecular dynamics simulation
2009 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-20
2009: 2340-2342
Abstract
Recent advances in algorithms, software, and hardware for molecular dynamics (MD) simulations have brought previously inaccessible simulation timescales within reach, allowing the use of MD simulation to address a substantially broader set of questions regarding protein function. MD has proved particularly useful in elucidating the functional mechanisms of membrane proteins, whose dynamics are especially difficult to characterize experimentally. Here, we illustrate the utility of state-of-the-art high-performance MD simulations in the study of membrane proteins, using as examples a G-protein-coupled receptor, an aquaporin, and an antiporter. In each case, we used MD either to deduce an atomic-level mechanism for protein function or to reconcile apparent discrepancies among recent experimental observations.
View details for Web of Science ID 000280543601319
View details for PubMedID 19965181
- . Identification of two distinct inactive conformations of the β2-adrenergic receptor reconciles structural and biochemical observations Proceedings of the National Academy of Sciences of the United States of America 2009: 4689-4694
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Dynamic control of slow water transport by aquaporin 0: Implications for hydration and junction stability in the eye lens
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2008; 105 (38): 14430-14435
Abstract
Aquaporin 0 (AQP0), the most abundant membrane protein in mammalian lens fiber cells, not only serves as the primary water channel in this tissue but also appears to mediate the formation of thin junctions between fiber cells. AQP0 is remarkably less water permeable than other aquaporins, but the structural basis and biological significance of this low permeability remain uncertain, as does the permeability of the protein in a reported junctional form. To address these issues, we performed molecular dynamics (MD) simulations of water transport through membrane-embedded AQP0 in both its (octameric) junctional and (tetrameric) nonjunctional forms. From our simulations, we measured an osmotic permeability for the nonjunctional form that agrees with experiment and found that the distinct dynamics of the conserved, lumen-protruding side chains of Tyr-23 and Tyr-149 modulate water passage, accounting for the slow permeation. The junctional and nonjunctional forms conducted water equivalently, in contrast to a previous suggestion based on static crystal structures that water conduction is lost on junction formation. Our analysis suggests that the low water permeability of AQP0 may help maintain the mechanical stability of the junction. We hypothesize that the structural features leading to low permeability may have evolved in part to allow AQP0 to form junctions that both conduct water and contribute to the organizational structure of the fiber cell tissue and microcirculation within it, as required to maintain transparency of the lens.
View details for DOI 10.1073/pnas.0802401105
View details for Web of Science ID 000259592400038
View details for PubMedID 18787121
View details for PubMedCentralID PMC2533686
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Anton, a special-purpose machine for molecular dynamics simulation
COMMUNICATIONS OF THE ACM
2008; 51 (7): 91-97
View details for DOI 10.1145/1364782.1364802
View details for Web of Science ID 000257116300021
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Microsecond molecular dynamics simulation shows effect of slow loop dynamics on backbone amide order parameters of proteins
JOURNAL OF PHYSICAL CHEMISTRY B
2008; 112 (19): 6155-6158
Abstract
A molecular-level understanding of the function of a protein requires knowledge of both its structural and dynamic properties. NMR spectroscopy allows the measurement of generalized order parameters that provide an atomistic description of picosecond and nanosecond fluctuations in protein structure. Molecular dynamics (MD) simulation provides a complementary approach to the study of protein dynamics on similar time scales. Comparisons between NMR spectroscopy and MD simulations can be used to interpret experimental results and to improve the quality of simulation-related force fields and integration methods. However, apparent systematic discrepancies between order parameters extracted from simulations and experiments are common, particularly for elements of noncanonical secondary structure. In this paper, results from a 1.2 micros explicit solvent MD simulation of the protein ubiquitin are compared with previously determined backbone order parameters derived from NMR relaxation experiments [Tjandra, N.; Feller, S. E.; Pastor, R. W.; Bax, A. J. Am. Chem. Soc. 1995, 117, 12562-12566]. The simulation reveals fluctuations in three loop regions that occur on time scales comparable to or longer than that of the overall rotational diffusion of ubiquitin and whose effects would not be apparent in experimentally derived order parameters. A coupled analysis of internal and overall motion yields simulated order parameters substantially closer to the experimentally determined values than is the case for a conventional analysis of internal motion alone. Improved agreement between simulation and experiment also is encouraging from the viewpoint of assessing the accuracy of long MD simulations.
View details for DOI 10.1021/jp077018h
View details for Web of Science ID 000255649600033
View details for PubMedID 18311962
View details for PubMedCentralID PMC2805408
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Hierarchical Simulation-Based Verification of Anton, a Special-Purpose Parallel Machine
2008 IEEE INTERNATIONAL CONFERENCE ON COMPUTER DESIGN
2008: 340-347
View details for Web of Science ID 000266685600052
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Incorporating Flexibility in Anton, a Specialized Machine for Molecular Dynamics Simulation
2008 IEEE 14TH INTERNATIONAL SYMPOSIUM ON HIGH PEFORMANCE COMPUTER ARCHITECTURE
2008: 315-326
View details for Web of Science ID 000263593200029
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High-Throughput Pairwise Point Interactions in Anton, a Specialized Machine for Molecular Dynamics Simulation
2008 IEEE 14TH INTERNATIONAL SYMPOSIUM ON HIGH PEFORMANCE COMPUTER ARCHITECTURE
2008: 303-314
View details for Web of Science ID 000263593200028
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Mechanism of Na+/H+ antiporting
SCIENCE
2007; 317 (5839): 799-803
Abstract
Na+/H+ antiporters are central to cellular salt and pH homeostasis. The structure of Escherichia coli NhaA was recently determined, but its mechanisms of transport and pH regulation remain elusive. We performed molecular dynamics simulations of NhaA that, with existing experimental data, enabled us to propose an atomically detailed model of antiporter function. Three conserved aspartates are key to our proposed mechanism: Asp164 (D164) is the Na+-binding site, D163 controls the alternating accessibility of this binding site to the cytoplasm or periplasm, and D133 is crucial for pH regulation. Consistent with experimental stoichiometry, two protons are required to transport a single Na+ ion: D163 protonates to reveal the Na+-binding site to the periplasm, and subsequent protonation of D164 releases Na+. Additional mutagenesis experiments further validated the model.
View details for DOI 10.1126/science.1142824
View details for Web of Science ID 000248624500039
View details for PubMedID 17690293
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A common, avoidable source of error in molecular dynamics integrators
JOURNAL OF CHEMICAL PHYSICS
2007; 126 (4)
View details for DOI 10.1063/1.2431176
View details for Web of Science ID 000243891100069
View details for PubMedID 17286520
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Zonal methods for the parallel execution of range-limited N-body simulations
JOURNAL OF COMPUTATIONAL PHYSICS
2007; 221 (1): 303-329
View details for DOI 10.1016/j.jcp.2006.06.014
View details for Web of Science ID 000244321000016
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The midpoint method for parallelization of particle simulations
JOURNAL OF CHEMICAL PHYSICS
2006; 124 (18)
Abstract
The evaluation of interactions between nearby particles constitutes the majority of the computational workload involved in classical molecular dynamics (MD) simulations. In this paper, we introduce a new method for the parallelization of range-limited particle interactions that proves particularly suitable to MD applications. Because it applies not only to pairwise interactions but also to interactions involving three or more particles, the method can be used for evaluation of both nonbonded and bonded forces in a MD simulation. It requires less interprocessor data transfer than traditional spatial decomposition methods at all but the lowest levels of parallelism. It gains an additional practical advantage in certain commonly used interprocessor communication networks by distributing the communication burden more evenly across network links and by decreasing the associated latency. When used to parallelize MD, it further reduces communication requirements by allowing the computations associated with short-range nonbonded interactions, long-range electrostatics, bonded interactions, and particle migration to use much of the same communicated data. We also introduce certain variants of this method that can significantly improve the balance of computational load across processors.
View details for DOI 10.1063/1.2191489
View details for Web of Science ID 000237477800011
View details for PubMedID 16709099
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Gaussian split Ewald: A fast Ewald mesh method for molecular simulation
JOURNAL OF CHEMICAL PHYSICS
2005; 122 (5)
Abstract
Gaussian split Ewald (GSE) is a versatile Ewald mesh method that is fast and accurate when used with both real-space and k-space Poisson solvers. While real-space methods are known to be asymptotically superior to k-space methods in terms of both computational cost and parallelization efficiency, k-space methods such as smooth particle-mesh Ewald (SPME) have thus far remained dominant because they have been more efficient than existing real-space methods for simulations of typical systems in the size range of current practical interest. Real-space GSE, however, is approximately a factor of 2 faster than previously described real-space Ewald methods for the level of force accuracy typically required in biomolecular simulations, and is competitive with leading k-space methods even for systems of moderate size. Alternatively, GSE may be combined with a k-space Poisson solver, providing a conveniently tunable k-space method that performs comparably to SPME. The GSE method follows naturally from a uniform framework that we introduce to concisely describe the differences between existing Ewald mesh methods.
View details for DOI 10.1063/1.1839571
View details for Web of Science ID 000226880100002
View details for PubMedID 15740304
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Statistical characterization of real-world illumination
JOURNAL OF VISION
2004; 4 (9): 821-837
Abstract
Although studies of vision and graphics often assume simple illumination models, real-world illumination is highly complex, with reflected light incident on a surface from almost every direction. One can capture the illumination from every direction at one point photographically using a spherical illumination map. This work illustrates, through analysis of photographically acquired, high dynamic range illumination maps, that real-world illumination possesses a high degree of statistical regularity. The marginal and joint wavelet coefficient distributions and harmonic spectra of illumination maps resemble those documented in the natural image statistics literature. However, illumination maps differ from typical photographs in that illumination maps are statistically nonstationary and may contain localized light sources that dominate their power spectra. Our work provides a foundation for statistical models of real-world illumination, thereby facilitating the understanding of human material perception, the design of robust computer vision systems, and the rendering of realistic computer graphics imagery.
View details for DOI 10.1167/4.9.11
View details for Web of Science ID 000224835300012
View details for PubMedID 15493972
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Bayesian estimation of transcript levels using a general model of array measurement noise
JOURNAL OF COMPUTATIONAL BIOLOGY
2003; 10 (3-4): 433-452
Abstract
Gene arrays demonstrate a promising ability to characterize expression levels across the entire genome but suffer from significant levels of measurement noise. We present a rigorous new approach to estimate transcript levels and ratios from one or more gene array experiments, given a model of measurement noise and available prior information. The Bayesian estimation of array measurements (BEAM) technique provides a principled method to identify changes in expression level, combine repeated measurements, or deal with negative expression level measurements. BEAM is more flexible than existing techniques, because it does not assume a specific functional form for noise and prior models. Instead, it relies on computational techniques that apply to a broad range of models. We use Affymetrix yeast chip data to illustrate the process of developing accurate noise and prior models from existing experimental data. The resulting noise model includes novel features such as heavy-tailed additive noise and a gene-specific bias term. We also verify that the resulting noise and prior models fit data from an Affymetrix human chip set.
View details for Web of Science ID 000184535800013
View details for PubMedID 12935337
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Real-world illumination and the perception of surface reflectance properties
JOURNAL OF VISION
2003; 3 (5): 347-368
Abstract
Under typical viewing conditions, we find it easy to distinguish between different materials, such as metal, plastic, and paper. Recognizing materials from their surface reflectance properties (such as lightness and gloss) is a nontrivial accomplishment because of confounding effects of illumination. However, if subjects have tacit knowledge of the statistics of illumination encountered in the real world, then it is possible to reject unlikely image interpretations, and thus to estimate surface reflectance even when the precise illumination is unknown. A surface reflectance matching task was used to measure the accuracy of human surface reflectance estimation. The results of the matching task demonstrate that subjects can match surface reflectance properties reliably and accurately in the absence of context, as long as the illumination is realistic. Matching performance declines when the illumination statistics are not representative of the real world. Together these findings suggest that subjects do use stored assumptions about the statistics of real-world illumination to estimate surface reflectance. Systematic manipulations of pixel and wavelet properties of illuminations reveal that the visual system's assumptions about illumination are of intermediate complexity (e.g., presence of edges and bright light sources), rather than of high complexity (e.g., presence of recognizable objects in the environment).
View details for DOI 10.1167/3.5.3
View details for Web of Science ID 000223081500003
View details for PubMedID 12875632
- Accuracy of velocity estimation by Reichardt corr¬elators Journal of the Optical Society of America A 2001: 241-252
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A mathematical criterion based on phase response curves for stability in a ring of coupled oscillators
BIOLOGICAL CYBERNETICS
1999; 80 (1): 11-23
Abstract
Canavier et al. (1997) used phase response curves (PRCs) of individual oscillators to characterize the possible modes of phase-locked entrainment of an N-oscillator ring network. We extend this work by developing a mathematical criterion to determine the local stability of such a mode based on the PRCs. Our method does not assume symmetry; neither the oscillators nor their connections need be identical. To use these techniques for predicting modes and determining their stability, one need only determine the PRC of each oscillator in the ring either experimentally or from a computational model. We show that network stability cannot be determined by simply testing the ability of each oscillator to entrain the next. Stability depends on the number of neurons in the ring, the type of mode, and the slope of each PRC at the point of entrainment of the respective neuron. We also describe simple criteria which are either necessary or sufficient for stability and examine the implications of these results.
View details for Web of Science ID 000078109300002
View details for PubMedID 20809292
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Phase response characteristics of model neurons determine which patterns are expressed in a ring circuit model of gait generation
BIOLOGICAL CYBERNETICS
1997; 77 (6): 367-380
Abstract
In order to assess the relative contributions to pattern-generation of the intrinsic properties of individual neurons and of their connectivity, we examined a ring circuit composed of four complex physiologically based oscillators. This circuit produced patterns that correspond to several quadrupedal gaits, including the walk, the bound, and the gallop. An analysis using the phase response curve (PRC) of an uncoupled oscillator accurately predicted all modes exhibited by this circuit and their phasic relationships--with the caveat that in certain parameter ranges, bistability in the individual oscillators added nongait patterns that were not amenable to PRC analysis, but further enriched the pattern-generating repertoire of the circuit. The key insights in the PRC analysis were that in a gait pattern, since all oscillators are entrained at the same frequency, the phase advance or delay caused by the action of each oscillator on its postsynaptic oscillator must be the same, and the sum of the normalized phase differences around the ring must equal to an integer. As suggested by several previous studies, our analysis showed that the capacity to exhibit a large number of patterns is inherent in the ring circuit configuration. In addition, our analysis revealed that the shape of the PRC for the individual oscillators determines which of the theoretically possible modes can be generated using these oscillators as circuit elements. PRCs that have a complex shape enable a circuit to produce a wider variety of patterns, and since complex neurons tend to have complex PRCs, enriching the repertoire of patterns exhibited by a circuit may be the function of some intrinsic neuronal complexity. Our analysis showed that gait transitions, or more generally, pattern transitions, in a ring circuit do not require rewiring the circuit or any changes in the strength of the connections. Instead, transitions can be achieved by using a control parameter, such as stimulus intensity, to sculpt the PRC so that it has the appropriate shape for the desired pattern(s). A transition can then be achieved simply by changing the value of the control parameter so that the first pattern either ceases to exist or loses stability, while a second pattern either comes into existence or gains stability. Our analysis illustrates the predictive value of PRCs in circuit analysis and can be extended to provide a design method for pattern-generating circuits.
View details for Web of Science ID 000071002200001
View details for PubMedID 9433752
- A search for best constants in the Hardy-Littlewood maximal theorem Journal of Fourier Analysis and Applications 1996: 473-486