74 citations · 140 across the 7 of their papers we have counts for
10 papers
LiveCoMS Roundtable: Discussing Markov state models after two decades of development v1.0
Daniel M. Zuckerman, Gregory R. Bowman, Amedeo Caflisch +14
Markov state models (MSMs) play a central role in the analysis of molecular dynamics (MD) simulations for biomolecules, and MSM methodologies have been under continual development…
Deep Generative Markov State Models with Experimental Restraints
Robert M. Raddi, Vincent A. Voelz
A central challenge in molecular modeling is reconciling simulations with experimental observables, as force-field inaccuracies can distort equilibrium populations and long-timesca…
Automatic Forward Model Parameterization with Bayesian Inference of Conformational Populations
Robert M. Raddi, Tim Marshall, Vincent A. Voelz
To quantify how well theoretical predictions of structural ensembles agree with experimental measurements, we depend on the accuracy of forward models. These models are computation…
Automated optimization of force field parameters against ensemble-averaged measurements with Bayesian Inference of Conformational Populations
Robert M. Raddi, Vincent A. Voelz
Accurate force fields are essential for reliable molecular simulations. These models are refined against quantum mechanical calculations and experimental measurements, which are su…
Folding@home: achievements from over twenty years of citizen science herald the exascale era
Vincent A. Voelz, Vijay S. Pande, Gregory R. Bowman
Simulations of biomolecules have enormous potential to inform our understanding of biology but require extremely demanding calculations. For over twenty years, the Folding@home dis…
Structure-Based Experimental Datasets for Benchmarking Protein Simulation Force Fields
Chapin E. Cavender, David A. Case, Julian C. -H. Chen +11
This review article provides an overview of structurally oriented experimental datasets that can be used to benchmark protein force fields, focusing on data generated by nuclear ma…
Assigning Confidence to Molecular Property Prediction
AkshatKumar Nigam, Robert Pollice, Matthew F. D. Hurley +6
Introduction: Computational modeling has rapidly advanced over the last decades, especially to predict molecular properties for chemistry, material science and drug design. Recentl…
Adaptive Markov State Model estimation using short reseeding trajectories
Hongbin Wan, Vincent A. Voelz
In the last decade, advances in molecular dynamics (MD) and Markov State Model (MSM) methodologies have made possible accurate and efficient estimation of kinetic rates and reactiv…
Is the free energy landscape informative about transition rates? Lessons from the kinetic Ising model
Daniel Sigg, Vincent A. Voelz, Vincenzo Carnevale
An oft-used concept in modeling macromolecules is the free energy landscape, obtained by coarse-graining a vast number of microstates into a low-dimensional mesh of mesostates. If…
A maximum-caliber approach to predicting perturbed folding kinetics due to mutations
Vincent A. Voelz, Guangfeng Zhou, Hongbin Wan
We present a maximum-caliber method for inferring transition rates of a Markov State Model (MSM) with perturbed equilibrium populations, given estimates of state populations and ra…