Rachael Kretsch
Ph.D. Student in Biophysics, admitted Autumn 2019
All Publications
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Complex Water Networks Visualized through 2.2-2.3 A Cryogenic Electron Microscopy of RNA.
bioRxiv : the preprint server for biology
2025
Abstract
The stability and function of biomolecules are directly influenced by their myriad interactions with water. In this study, we investigated water through cryogenic electron microscopy (cryo-EM) on a highly solvated molecule, the Tetrahymena ribozyme, determined at 2.2 and 2.3 A resolutions. By employing segmentation-guided water and ion modeling (SWIM), an approach combining resolvability and chemical parameters, we automatically modeled and cross-validated water molecules and Mg 2+ ions in the ribozyme core, revealing the extensive involvement of water in mediating RNA non-canonical interactions. Unexpectedly, in regions where SWIM does not model ordered water, we observed highly similar densities in both cryo-EM maps. In many of these regions, the cryo-EM densities superimpose with complex water networks predicted by molecular dynamics (MD), supporting their assignment as water and suggesting a biophysical explanation for their elusiveness to conventional atomic coordinate modeling. Our study demonstrates an approach to unveil both rigid and flexible waters that surround biomolecules through cryo-EM map densities, statistical and chemical metrics, and MD simulations.
View details for DOI 10.1101/2025.01.23.634578
View details for PubMedID 39896454
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Conformational ensembles reveal the origins of serine protease catalysis.
Science (New York, N.Y.)
2025; 387 (6735): eado5068
Abstract
Enzymes exist in ensembles of states that encode the energetics underlying their catalysis. Conformational ensembles built from 1231 structures of 17 serine proteases revealed atomic-level changes across their reaction states. By comparing the enzymatic and solution reaction, we identified molecular features that provide catalysis and quantified their energetic contributions to catalysis. Serine proteases precisely position their reactants in destabilized conformers, creating a downhill energetic gradient that selectively favors the motions required for reaction while limiting off-pathway conformational states. The same catalytic features have repeatedly evolved in proteases and additional enzymes across multiple distinct structural folds. Our ensemble-function analyses revealed previously unknown catalytic features, provided quantitative models based on simple physical and chemical principles, and identified motifs recurrent in nature that may inspire enzyme design.
View details for DOI 10.1126/science.ado5068
View details for PubMedID 39946472
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RNA-Puzzles Round V: blind predictions of 23 RNA structures.
Nature methods
2024
Abstract
RNA-Puzzles is a collective endeavor dedicated to the advancement and improvement of RNA three-dimensional structure prediction. With agreement from structural biologists, RNA structures are predicted by modeling groups before publication of the experimental structures. We report a large-scale set of predictions by 18 groups for 23 RNA-Puzzles: 4 RNA elements, 2 Aptamers, 4 Viral elements, 5 Ribozymes and 8 Riboswitches. We describe automatic assessment protocols for comparisons between prediction and experiment. Our analyses reveal some critical steps to be overcome to achieve good accuracy in modeling RNA structures: identification of helix-forming pairs and of non-Watson-Crick modules, correct coaxial stacking between helices and avoidance of entanglements. Three of the top four modeling groups in this round also ranked among the top four in the CASP15 contest.
View details for DOI 10.1038/s41592-024-02543-9
View details for PubMedID 39623050
View details for PubMedCentralID 3312550
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Tertiary folds of the SL5 RNA from the 5' proximal region of SARS-CoV-2 and related coronaviruses.
Proceedings of the National Academy of Sciences of the United States of America
2024; 121 (10): e2320493121
Abstract
Coronavirus genomes sequester their start codons within stem-loop 5 (SL5), a structured, 5' genomic RNA element. In most alpha- and betacoronaviruses, the secondary structure of SL5 is predicted to contain a four-way junction of helical stems, some of which are capped with UUYYGU hexaloops. Here, using cryogenic electron microscopy (cryo-EM) and computational modeling with biochemically determined secondary structures, we present three-dimensional structures of SL5 from six coronaviruses. The SL5 domain of betacoronavirus severe-acute-respiratory-syndrome-related coronavirus 2 (SARS-CoV-2), resolved at 4.7 Å resolution, exhibits a T-shaped structure, with its UUYYGU hexaloops at opposing ends of a coaxial stack, the T's "arms." Further analysis of SL5 domains from SARS-CoV-1 and MERS (7.1 and 6.4 to 6.9 Å resolution, respectively) indicate that the junction geometry and inter-hexaloop distances are conserved features across these human-infecting betacoronaviruses. The MERS SL5 domain displays an additional tertiary interaction, which is also observed in the non-human-infecting betacoronavirus BtCoV-HKU5 (5.9 to 8.0 Å resolution). SL5s from human-infecting alphacoronaviruses, HCoV-229E and HCoV-NL63 (6.5 and 8.4 to 9.0 Å resolution, respectively), exhibit the same coaxial stacks, including the UUYYGU-capped arms, but with a phylogenetically distinct crossing angle, an X-shape. As such, all SL5 domains studied herein fold into stable tertiary structures with cross-genus similarities and notable differences, with implications for potential protein-binding modes and therapeutic targets.
View details for DOI 10.1073/pnas.2320493121
View details for PubMedID 38427602
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Ribonanza: deep learning of RNA structure through dual crowdsourcing.
bioRxiv : the preprint server for biology
2024
Abstract
Prediction of RNA structure from sequence remains an unsolved problem, and progress has been slowed by a paucity of experimental data. Here, we present Ribonanza, a dataset of chemical mapping measurements on two million diverse RNA sequences collected through Eterna and other crowdsourced initiatives. Ribonanza measurements enabled solicitation, training, and prospective evaluation of diverse deep neural networks through a Kaggle challenge, followed by distillation into a single, self-contained model called RibonanzaNet. When fine tuned on auxiliary datasets, RibonanzaNet achieves state-of-the-art performance in modeling experimental sequence dropout, RNA hydrolytic degradation, and RNA secondary structure, with implications for modeling RNA tertiary structure.
View details for DOI 10.1101/2024.02.24.581671
View details for PubMedID 38464325
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CASP15 cryo-EM protein and RNA targets: Refinement and analysis using experimental maps.
Proteins
2023; 91 (12): 1935-1951
Abstract
CASP assessments primarily rely on comparing predicted coordinates with experimental reference structures. However, experimental structures by their nature are only models themselves-their construction involves a certain degree of subjectivity in interpreting density maps and translating them to atomic coordinates. Here, we directly utilized density maps to evaluate the predictions by employing a method for ranking the quality of protein chain predictions based on their fit into the experimental density. The fit-based ranking was found to correlate well with the CASP assessment scores. Overall, the evaluation against the density map indicated that the models are of high accuracy, and occasionally even better than the reference structure in some regions of the model. Local assessment of predicted side chains in a 1.52A resolution map showed that side-chains are sometimes poorly positioned. Additionally, the top 118 predictions associated with 9 protein target reference structures were selected for automated refinement, in addition to the top 40 predictions for 11 RNA targets. For both proteins and RNA, the refinement of CASP15 predictions resulted in structures that are close to the reference target structure. This refinement was successful despite large conformational changes often being required, showing that predictions from CASP-assessed methods could serve as a good starting point for building atomic models in cryo-EM maps for both proteins and RNA. Loop modeling continued to pose a challenge for predictors, and together with the lack of consensus amongst models in these regions suggests that modeling, in combination with model-fit to the density, holds the potential for identifying more flexible regions within the structure.
View details for DOI 10.1002/prot.26644
View details for PubMedID 37994556
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Tertiary folds of the SL5 RNA from the 5' proximal region of SARS-CoV-2 and related coronaviruses.
bioRxiv : the preprint server for biology
2023
Abstract
Coronavirus genomes sequester their start codons within stem-loop 5 (SL5), a structured, 5' genomic RNA element. In most alpha- and betacoronaviruses, the secondary structure of SL5 is predicted to contain a four-way junction of helical stems, some of which are capped with UUYYGU hexaloops. Here, using cryogenic electron microscopy (cryo-EM) and computational modeling with biochemically-determined secondary structures, we present three-dimensional structures of SL5 from six coronaviruses. The SL5 domain of betacoronavirus SARS-CoV-2, resolved at 4.7 A resolution, exhibits a T-shaped structure, with its UUYYGU hexaloops at opposing ends of a coaxial stack, the T's "arms." Further analysis of SL5 domains from SARS-CoV-1 and MERS (7.1 and 6.4-6.9 A resolution, respectively) indicate that the junction geometry and inter-hexaloop distances are conserved features across the studied human-infecting betacoronaviruses. The MERS SL5 domain displays an additional tertiary interaction, which is also observed in the non-human-infecting betacoronavirus BtCoV-HKU5 (5.9-8.0 A resolution). SL5s from human-infecting alphacoronaviruses, HCoV-229E and HCoV-NL63 (6.5 and 8.4-9.0 A resolution, respectively), exhibit the same coaxial stacks, including the UUYYGU-capped arms, but with a phylogenetically distinct crossing angle, an X-shape. As such, all SL5 domains studied herein fold into stable tertiary structures with cross-genus similarities, with implications for potential protein-binding modes and therapeutic targets.Significance: The three-dimensional structures of viral RNAs are of interest to the study of viral pathogenesis and therapeutic design, but the three-dimensional structures of viral RNAs remain poorly characterized. Here, we provide the first 3D structures of the SL5 domain (124-160 nt, 40.0-51.4 kDa) from the majority of human-infecting coronaviruses. All studied SL5s exhibit a similar 4-way junction, with their crossing angles grouped along phylogenetic boundaries. Further, across all species studied, conserved UUYYGU hexaloop pairs are located at opposing ends of a coaxial stack, suggesting that their three-dimensional arrangement is important for their as-of-yet defined function. These conserved tertiary features support the relevance of SL5 for pan-coronavirus fitness and highlight new routes in understanding its molecular and virological roles and in developing SL5-based antivirals. Classification: Biological Sciences, Biophysics and Computational Biology.
View details for DOI 10.1101/2023.11.22.567964
View details for PubMedID 38076883
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Assessment of three-dimensional RNA structure prediction in CASP15.
Proteins
2023
Abstract
The prediction of RNA three-dimensional structures remains an unsolved problem. Here, we report assessments of RNA structure predictions in CASP15, the first CASP exercise that involved RNA structure modeling. Forty-two predictor groups submitted models for at least one of twelve RNA-containing targets. These models were evaluated by the RNA-Puzzles organizers and, separately, by a CASP-recruited team using metrics (GDT, lDDT) and approaches (Z-score rankings) initially developed for assessment of proteins and generalized here for RNA assessment. The two assessments independently ranked the same predictor groups as first (AIchemy_RNA2), second (Chen), and third (RNAPolis and GeneSilico, tied); predictions from deep learning approaches were significantly worse than these top ranked groups, which did not use deep learning. Further analyses based on direct comparison of predicted models to cryogenic electron microscopy (cryo-EM) maps and x-ray diffraction data support these rankings. With the exception of two RNA-protein complexes, models submitted by CASP15 groups correctly predicted the global fold of the RNA targets. Comparisons of CASP15 submissions to designed RNA nanostructures as well as molecular replacement trials highlight the potential utility of current RNA modeling approaches for RNA nanotechnology and structural biology, respectively. Nevertheless, challenges remain in modeling fine details such as noncanonical pairs, in ranking among submitted models, and in prediction of multiple structures resolved by cryo-EM or crystallography.
View details for DOI 10.1002/prot.26602
View details for PubMedID 37876231
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RNA target highlights in CASP15: Evaluation of predicted models by structure providers.
Proteins
2023
Abstract
The first RNA category of the Critical Assessment of Techniques for Structure Prediction competition was only made possible because of the scientists who provided experimental structures to challenge the predictors. In this article, these scientists offer a unique and valuable analysis of both the successes and areas for improvement in the predicted models. All 10 RNA-only targets yielded predictions topologically similar to experimentally determined structures. For one target, experimentalists were able to phase their x-ray diffraction data by molecular replacement, showing a potential application of structure predictions for RNA structural biologists. Recommended areas for improvement include: enhancing the accuracy in local interaction predictions and increased consideration of the experimental conditions such as multimerization, structure determination method, and time along folding pathways. The prediction of RNA-protein complexes remains the most significant challenge. Finally, given the intrinsic flexibility of many RNAs, we propose the consideration of ensemble models.
View details for DOI 10.1002/prot.26550
View details for PubMedID 37466021
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New prediction categories in CASP15.
Proteins
2023
Abstract
Prediction categories in the Critical Assessment of Structure Prediction (CASP) experiments change with the need to address specific problems in structure modeling. In CASP15, four new prediction categories were introduced: RNA structure, ligand-protein complexes, accuracy of oligomeric structures and their interfaces, and ensembles of alternative conformations. This paper lists technical specifications for these categories and describes their integration in the CASP data management system.
View details for DOI 10.1002/prot.26515
View details for PubMedID 37306011
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Assessment of three-dimensional RNA structure prediction in CASP15.
bioRxiv : the preprint server for biology
2023
Abstract
The prediction of RNA three-dimensional structures remains an unsolved problem. Here, we report double-blind assessments of RNA structure predictions in CASP15, the first CASP exercise in which RNA modeling was assessed. Forty two predictor groups submitted models for at least one of twelve RNA-containing targets. These models were evaluated by the RNA-Puzzles organizers and, separately, by a CASP-recruited team using metrics (GDT, lDDT) and approaches (Z-score rankings) initially developed for assessment of proteins and generalized here for RNA assessment. The two assessments independently ranked the same predictor groups as first (AIchemy_RNA2), second (Chen), and third (RNAPolis and GeneSilico, tied); predictions from deep learning approaches were significantly worse than these top ranked groups, who did not use deep learning. Further analyses based on direct comparison of predicted models to cryogenic electron microscopy (cryo-EM) maps and X-ray diffraction data support these rankings. With the exception of two RNA-protein complexes, models submitted by CASP15 groups correctly predicted the global topology of the RNA targets. Comparisons of CASP15 submissions to designed RNA nanostructures as well as molecular replacement trials highlight the potential utility of current RNA modeling approaches for RNA nanotechnology and structural biology, respectively. Nevertheless, challenges remain in modeling fine details such as non-canonical pairs, in ranking among submitted models, and in prediction of multiple structures resolved by cryo-EM or crystallography.
View details for DOI 10.1101/2023.04.25.538330
View details for PubMedID 37162955
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Ensemble-function relationships to connect structure to mechanism: application of EnsemblePDB to the serine protease reaction coordinate and its catalytic features
CELL PRESS. 2022: 441A
View details for Web of Science ID 000759523002687
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Cryo-EM and antisense targeting of the 28-kDa frameshift stimulation element from the SARS-CoV-2 RNA genome.
Nature structural & molecular biology
2021
Abstract
Drug discovery campaigns against COVID-19 are beginning to target the SARS-CoV-2 RNA genome. The highly conserved frameshift stimulation element (FSE), required for balanced expression of viral proteins, is a particularly attractive SARS-CoV-2 RNA target. Here we present a 6.9A resolution cryo-EM structure of the FSE (88nucleotides, ~28kDa), validated through an RNA nanostructure tagging method. The tertiary structure presents a topologically complex fold in which the 5' end is threaded through a ring formed inside a three-stem pseudoknot. Guided by this structure, we develop antisense oligonucleotides that impair FSE function in frameshifting assays and knock down SARS-CoV-2 virus replication in A549-ACE2 cells at 100nM concentration.
View details for DOI 10.1038/s41594-021-00653-y
View details for PubMedID 34426697
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Interpretation of RNA cryo-EM maps of various resolutions
INT UNION CRYSTALLOGRAPHY. 2021: A217
View details for DOI 10.1107/S0108767321097828
View details for Web of Science ID 000720840500218
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De novo 3D models of SARS-CoV-2 RNA elements from consensus experimental secondary structures.
Nucleic acids research
2021
Abstract
The rapid spread of COVID-19 is motivating development of antivirals targeting conserved SARS-CoV-2 molecular machinery. The SARS-CoV-2 genome includes conserved RNA elements that offer potential small-molecule drug targets, but most of their 3D structures have not been experimentally characterized. Here, we provide a compilation of chemical mapping data from our and other labs, secondary structure models, and 3D model ensembles based on Rosetta's FARFAR2 algorithm for SARS-CoV-2 RNA regions including the individual stems SL1-8 in the extended 5' UTR; the reverse complement of the 5' UTR SL1-4; the frameshift stimulating element (FSE); and the extended pseudoknot, hypervariable region, and s2m of the 3' UTR. For eleven of these elements (the stems in SL1-8, reverse complement of SL1-4, FSE, s2m and 3' UTR pseudoknot), modeling convergence supports the accuracy of predicted low energy states; subsequent cryo-EM characterization of the FSE confirms modeling accuracy. To aid efforts to discover small molecule RNA binders guided by computational models, we provide a second set of similarly prepared models for RNA riboswitches that bind small molecules. Both datasets ('FARFAR2-SARS-CoV-2', https://github.com/DasLab/FARFAR2-SARS-CoV-2; and 'FARFAR2-Apo-Riboswitch', at https://github.com/DasLab/FARFAR2-Apo-Riboswitch') include up to 400 models for each RNA element, which may facilitate drug discovery approaches targeting dynamic ensembles of RNA molecules.
View details for DOI 10.1093/nar/gkab119
View details for PubMedID 33693814
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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