CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field

Jumin Lee, Xi Cheng, Jason M. Swails, Min Sun Yeom, Peter K. Eastman, Justin A. Lemkul, Shuai Wei, Joshua Buckner, Jong Cheol Jeong, Yifei Qi, Sunhwan Jo, Vijay S. Pande, David A. Case, Charles L. Brooks, Alexander D. MacKerell, Jeffery B. Klauda, Wonpil Im

Research output: Contribution to journalArticlepeer-review

2357 Scopus citations

Abstract

Proper treatment of nonbonded interactions is essential for the accuracy of molecular dynamics (MD) simulations, especially in studies of lipid bilayers. The use of the CHARMM36 force field (C36 FF) in different MD simulation programs can result in disagreements with published simulations performed with CHARMM due to differences in the protocols used to treat the long-range and 1-4 nonbonded interactions. In this study, we systematically test the use of the C36 lipid FF in NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM. A wide range of Lennard-Jones (LJ) cutoff schemes and integrator algorithms were tested to find the optimal simulation protocol to best match bilayer properties of six lipids with varying acyl chain saturation and head groups. MD simulations of a 1,2-dipalmitoyl-sn-phosphatidylcholine (DPPC) bilayer were used to obtain the optimal protocol for each program. MD simulations with all programs were found to reasonably match the DPPC bilayer properties (surface area per lipid, chain order parameters, and area compressibility modulus) obtained using the standard protocol used in CHARMM as well as from experiments. The optimal simulation protocol was then applied to the other five lipid simulations and resulted in excellent agreement between results from most simulation programs as well as with experimental data. AMBER compared least favorably with the expected membrane properties, which appears to be due to its use of the hard-truncation in the LJ potential versus a force-based switching function used to smooth the LJ potential as it approaches the cutoff distance. The optimal simulation protocol for each program has been implemented in CHARMM-GUI. This protocol is expected to be applicable to the remainder of the additive C36 FF including the proteins, nucleic acids, carbohydrates, and small molecules.

Original languageEnglish
Pages (from-to)405-413
Number of pages9
JournalJournal of Chemical Theory and Computation
Volume12
Issue number1
DOIs
StatePublished - Jan 12 2016

Bibliographical note

Publisher Copyright:
© 2015 American Chemical Society.

Funding

This work was supported by NSF DBI-1145987, NSF MCB-1157677, NIH U54GM087519, XSEDE MCB070009 (to W.I.), NIH R01GM072558, GM051501, GM070855 (A.D.M.), NSF MCB-1149187, NSF DBI-1145652 (J.B.K.), NIH F32GM109632 (J.A.L.), NIH GM103695, GM037554 (C.L.B.), and the National Institute of Supercomputing and Networking/Korea Institute of Science and Technology Information with supercomputing resources including technical support [KSC-2015-C3-004] (M.S.Y.).

FundersFunder number
National Institute of Supercomputing and Networking
National Science Foundation Arctic Social Science ProgramMCB-1157677, DBI-1145987
National Institutes of Health (NIH)F32GM109632, GM037554, MCB-1149187, GM103695, XSEDE MCB070009, DBI-1145652, GM070855, R01GM072558, GM051501
National Institute of General Medical SciencesU54GM087519
Korea Institute of Science and Technology InformationKSC-2015-C3-004

    ASJC Scopus subject areas

    • Computer Science Applications
    • Physical and Theoretical Chemistry

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