Constructing interpretable computational models of protein dynamics using information theory and variance minimization
AMER CHEMICAL SOC. 2018
View details for Web of Science ID 000447609106319
A Minimum Variance Clustering Approach Produces Robust and Interpretable Coarse-Grained Models
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
2018; 14 (2): 1071–82
Markov state models (MSMs) are a powerful framework for the analysis of molecular dynamics data sets, such as protein folding simulations, because of their straightforward construction and statistical rigor. The coarse-graining of MSMs into an interpretable number of macrostates is a crucial step for connecting theoretical results with experimental observables. Here we present the minimum variance clustering approach (MVCA) for the coarse-graining of MSMs into macrostate models. The method utilizes agglomerative clustering with Ward's minimum variance objective function, and the similarity of the microstate dynamics is determined using the Jensen-Shannon divergence between the corresponding rows in the MSM transition probability matrix. We first show that MVCA produces intuitive results for a simple tripeptide system and is robust toward long-duration statistical artifacts. MVCA is then applied to two protein folding simulations of the same protein in different force fields to demonstrate that a different number of macrostates is appropriate for each model, revealing a misfolded state present in only one of the simulations. Finally, we show that the same method can be used to analyze a data set containing many MSMs from simulations in different force fields by aggregating them into groups and quantifying their dynamical similarity in the context of force field parameter choices. The minimum variance clustering approach with the Jensen-Shannon divergence provides a powerful tool to group dynamics by similarity, both among model states and among dynamical models themselves.
View details for PubMedID 29253336
Building a More Predictive Protein Force Field: A Systematic and Reproducible Route to AMBER-FB15
JOURNAL OF PHYSICAL CHEMISTRY B
2017; 121 (16): 4023-4039
The increasing availability of high-quality experimental data and first-principles calculations creates opportunities for developing more accurate empirical force fields for simulation of proteins. We developed the AMBER-FB15 protein force field by building a high-quality quantum chemical data set consisting of comprehensive potential energy scans and employing the ForceBalance software package for parameter optimization. The optimized potential surface allows for more significant thermodynamic fluctuations away from local minima. In validation studies where simulation results are compared to experimental measurements, AMBER-FB15 in combination with the updated TIP3P-FB water model predicts equilibrium properties with equivalent accuracy, and temperature dependent properties with significantly improved accuracy, in comparison with published models. We also discuss the effect of changing the protein force field and water model on the simulation results.
View details for DOI 10.1021/acs.jpcb.7b02320
View details for Web of Science ID 000400534200012
View details for PubMedID 28306259
Markov modeling reveals novel intracellular modulation of the human TREK-2 selectivity filter
Two-pore domain potassium (K2P) channel ion conductance is regulated by diverse stimuli that directly or indirectly gate the channel selectivity filter (SF). Recent crystal structures for the TREK-2 member of the K2P family reveal distinct "up" and "down" states assumed during activation via mechanical stretch. We performed 195 μs of all-atom, unbiased molecular dynamics simulations of the TREK-2 channel to probe how membrane stretch regulates the SF gate. Markov modeling reveals a novel "pinched" SF configuration that stretch activation rapidly destabilizes. Free-energy barrier heights calculated for critical steps in the conduction pathway indicate that this pinched state impairs ion conduction. Our simulations predict that this low-conductance state is accessed exclusively in the compressed, "down" conformation in which the intracellular helix arrangement allosterically pinches the SF. By explicitly relating structure to function, we contribute a critical piece of understanding to the evolving K2P puzzle.
View details for DOI 10.1038/s41598-017-00256-y
View details for Web of Science ID 000398162600008
View details for PubMedID 28377596
Modeling the mechanism of CLN025 beta-hairpin formation.
The Journal of chemical physics
2017; 147 (10): 104107
Beta-hairpins are substructures found in proteins that can lend insight into more complex systems. Furthermore, the folding of beta-hairpins is a valuable test case for benchmarking experimental and theoretical methods. Here, we simulate the folding of CLN025, a miniprotein with a beta-hairpin structure, at its experimental melting temperature using a range of state-of-the-art protein force fields. We construct Markov state models in order to examine the thermodynamics, kinetics, mechanism, and rate-determining step of folding. Mechanistically, we find the folding process is rate-limited by the formation of the turn region hydrogen bonds, which occurs following the downhill hydrophobic collapse of the extended denatured protein. These results are presented in the context of established and contradictory theories of the beta-hairpin folding process. Furthermore, our analysis suggests that the AMBER-FB15 force field, at this temperature, best describes the characteristics of the full experimental CLN025 conformational ensemble, while the AMBER ff99SB-ILDN and CHARMM22* force fields display a tendency to overstabilize the native state.
View details for PubMedID 28915754
View details for PubMedCentralID PMC5597441
Training and Validation of a Liquid-Crystalline Phospholipid Bilayer Force Field
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
2016; 12 (12): 5960-5967
We present a united-atom model (gb-fb15) for the molecular dynamics simulation of hydrated liquid-crystalline dipalmitoylphosphatidylcholine (DPPC) phospholipid bilayers. This model was constructed through the parameter-space minimization of a regularized least-squares objective function via the ForceBalance method. The objective function was computed using a training set of experimental bilayer area per lipid and deuterium order parameter. This model was validated by comparison to experimental volume per lipid, X-ray scattering form factor, thermal area expansivity, area compressibility modulus, and lipid lateral diffusion coefficient. These comparisons demonstrate that gb-fb15 is robust to temperature variation and an improvement over the original model for both the training and validation properties.
View details for DOI 10.1021/acs.jctc.6b00801
View details for Web of Science ID 000389866500025
View details for PubMedID 27786477
Non-invasive determination of the complete elastic moduli of spider silks
2013; 12 (3): 262-267
Spider silks possess nature's most exceptional mechanical properties, with unrivalled extensibility and high tensile strength. Unfortunately, our understanding of silks is limited because the complete elastic response has never been measured-leaving a stark lack of essential fundamental information. Using non-invasive, non-destructive Brillouin light scattering, we obtain the entire stiffness tensors (revealing negative Poisson's ratios), refractive indices, and longitudinal and transverse sound velocities for major and minor ampullate spider silks: Argiope aurantia, Latrodectus hesperus, Nephila clavipes, Peucetia viridans. These results completely quantify the linear elastic response for all possible deformation modes, information unobtainable with traditional stress-strain tests. For completeness, we apply the principles of Brillouin imaging to spatially map the elastic stiffnesses on a spider web without deforming or disrupting the web in a non-invasive, non-contact measurement, finding variation among discrete fibres, junctions and glue spots. Finally, we provide the stiffness changes that occur with supercontraction.
View details for DOI 10.1038/NMAT3549
View details for Web of Science ID 000315707200026
View details for PubMedID 23353627
- Shear-induced rigidity in spider silk glands APPLIED PHYSICS LETTERS 2012; 101 (10)