198 citations · 853 across the 15 of their papers we have counts for
4 papers · 1 filter
Navigating protein landscapes with a machine-learned transferable coarse-grained model
Nicholas E. Charron, Felix Musil, Andrea Guljas +18
The most popular and universally predictive protein simulation models employ all-atom molecular dynamics (MD), but they come at extreme computational cost. The development of a uni…
Machine Learning Coarse-Grained Potentials of Protein Thermodynamics
Maciej Majewski, Adrià Pérez, Philipp Thölke +7
A generalized understanding of protein dynamics is an unsolved scientific problem, the solution of which is critical to the interpretation of the structure-function relationships t…
Deflation reveals dynamical structure in nondominant reaction coordinates
Brooke E. Husic, Frank Noé
The output of molecular dynamics simulations is high-dimensional, and the degrees of freedom among the atoms are related in intricate ways. Therefore, a variety of analysis framewo…
MSM lag time cannot be used for variational model selection
Brooke E. Husic, Vijay S. Pande
The variational principle for conformational dynamics has enabled the systematic construction of Markov state models through the optimization of hyperparameters by approximating th…