@article{4b011e9caee642faa45fcdac0d8be2c3,
title = "Constant-pH Molecular Dynamics Simulations for Large Biomolecular Systems",
abstract = "An increasingly important endeavor is to develop computational strategies that enable molecular dynamics (MD) simulations of biomolecular systems with spontaneous changes in protonation states under conditions of constant pH. The present work describes our efforts to implement the powerful constant-pH MD simulation method, based on a hybrid nonequilibrium MD/Monte Carlo (neMD/MC) technique within the highly scalable program NAMD. The constant-pH hybrid neMD/MC method has several appealing features; it samples the correct semigrand canonical ensemble rigorously, the computational cost increases linearly with the number of titratable sites, and it is applicable to explicit solvent simulations. The present implementation of the constant-pH hybrid neMD/MC in NAMD is designed to handle a wide range of biomolecular systems with no constraints on the choice of force field. Furthermore, the sampling efficiency can be adaptively improved on-the-fly by adjusting algorithmic parameters during the simulation. Illustrative examples emphasizing medium- and large-scale applications on next-generation supercomputing architectures are provided.",
author = "Radak, {Brian K.} and Christophe Chipot and Donghyuk Suh and Sunhwan Jo and Wei Jiang and Phillips, {James C.} and Klaus Schulten and Beno{\^i}t Roux",
note = "Funding Information: This research was performed with the resources of the Argonne Leadership Computing Facility (ALCF) supported by the U.S. Department of Energy, Office of Science under Contract No. DE-AC02-06CH11357. The work was also supported in part by the National Institutes of Health (NIH) through grants U54-GM087519 and P41-RR005969 (K.S.), by the National Science Foundation (NSF) through grant MCB 16-16590 (K.S.), and by the France and Chicago Collaborating in The Sciences (FACCTS) program (to B.R and C.C.). Computational resources were provided by the University of Chicago Research Computing Center, the Argonne Leadership Computing Facility (ALCF), the National Center for Supercomputing Applications through the Great Lakes Consortium for Petascale Computation (NCSA-GLCPC, to B.R.), and the Grand Equipement National de Calcul Intensif−Centre Informatique National de l{\textquoteright}Enseignement Superieur (GENCI-CINES) at Montpelier, France (to C.C.). Funding Information: This research was performed with the resources of the Argonne Leadership Computing Facility (ALCF) supported by the U.S. Department of Energy, Office of Science under Contract No. DE-AC02-06CH11357. The work was also supported in part by the National Institutes of Health (NIH) through grants U54-GM087519 and P41-RR005969 (K.S.), by the National Science Foundation (NSF) through grant MCB 16-16590 (K.S.), and by the France and Chicago Collaborating in The Sciences (FACCTS) program (to B.R and C.C.). Computational resources were provided by the University of Chicago Research Computing Center, the Argonne Leadership Computing Facility (ALCF), the National Center for Supercomputing Applications through the Great Lakes Consortium for Petascale Computation (NCSA-GLCPC, to B.R.), and the Grand Equipement National de Calcul Intensif-Centre Informatique National de l'Enseignement Superieur (GENCICINES) at Montpelier, France (to C.C.). Publisher Copyright: {\textcopyright} 2017 American Chemical Society.",
year = "2017",
month = dec,
day = "12",
doi = "10.1021/acs.jctc.7b00875",
language = "English (US)",
volume = "13",
pages = "5933--5944",
journal = "Journal of Chemical Theory and Computation",
issn = "1549-9618",
publisher = "American Chemical Society",
number = "12",
}