Journal
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
Volume 10, Issue 3, Pages 1341-1352Publisher
AMER CHEMICAL SOC
DOI: 10.1021/ct401042b
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Funding
- National Science Foundation (NSF)
- NCSA Blue Waters
- University of Florida High Performance Computing center
- Extreme Science and Engineering Discovery Environment (XSEDE)
- National Science Foundation [OCI-10.53575]
- NSF [ACI-1147910, ACI-1036208]
- National Institutes of Health (NIH) [GM62248]
- Office of Advanced Cyberinfrastructure (OAC)
- Direct For Computer & Info Scie & Enginr [1147910] Funding Source: National Science Foundation
- Office of Advanced Cyberinfrastructure (OAC)
- Direct For Computer & Info Scie & Enginr [1036208] Funding Source: National Science Foundation
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By utilizing Graphics Processing Units, we show that constant pH molecular dynamics simulations (CpHMD) run in Generalized Born (GB) implicit solvent for long time scales can yield poor plc predictions as a result of sampling unrealistic conformations. To address this shortcoming, we present a method for performing constant pH molecular dynamics simulations (CpHMD) in explicit solvent using a discrete protonation state model. The method involves standard molecular dynamics (MD) being propagated in explicit solvent followed by protonation state changes being attempted in GB implicit solvent at fixed intervals. Replica exchange along the pH-dimension (pH-REMD) helps to obtain acceptable titration behavior with the proposed method. We analyzed the effects of various parameters and settings on the CpH_MD and pH-REMD in explicit solvent, including the size of the simulation unit cell and the length of the relaxation dynamics following protonation state changes. We tested the method with the amino acid model compounds, a small pentapeptide with two titratable sites, and hen egg white lysozyme (HEWL). The proposed method yields superior predicted pK(a) values for HEWL over hundreds of nanoseconds of simulation relative to corresponding predicted values from simulations run in implicit solvent.
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