Tinker‐OpenMM: Absolute and relative alchemical free energies using AMOEBA on GPUs. Issue 23 (10th June 2017)

• Record Type: Journal Article
• Authors: Harger, Matthew; Li, Daniel; Wang, Zhi; Dalby, Kevin; Lagardère, Louis; Piquemal, Jean‐Philip; Ponder, Jay; Ren, Pengyu
• Is Part Of: Journal of computational chemistry. Volume 38:Issue 23(2017)
• Page Start: 2047
• Page End: 2055
• Publication Date: 2017-06-10
• Subjects: AMOEBA -- free energy calculation -- graphics processing units -- Tinker -- OpenMM; Chemistry -- Data processing -- Periodicals; 542.85
• DOI: 10.1002/jcc.24853
• Languages: English
• ISSNs: 0192-8651

Abstract

Abstract : The capabilities of the polarizable force fields for alchemical free energy calculations have been limited by the high computational cost and complexity of the underlying potential energy functions. In this work, we present a GPU‐based general alchemical free energy simulation platform for polarizable potential AMOEBA. Tinker‐OpenMM, the OpenMM implementation of the AMOEBA simulation engine has been modified to enable both absolute and relative alchemical simulations on GPUs, which leads to a ∼200‐fold improvement in simulation speed over a single CPU core. We show that free energy values calculated using this platform agree with the results of Tinker simulations for the hydration of organic compounds and binding of host–guest systems within the statistical errors. In addition to absolute binding, we designed a relative alchemical approach for computing relative binding affinities of ligands to the same host, where a special path was applied to avoid numerical instability due to polarization between the different ligands that bind to the same site. This scheme is general and does not require ligands to have similar scaffolds. We show that relative hydration and binding free energy calculated using this approach match those computed from the absolute free energy approach. © 2017 Wiley Periodicals, Inc. Abstract : We have developed Tinker‐OpenMM‐ a computational platform for the calculation of free energies on graphics processing units. This allows for free energy simulations to be run 200 times faster than is possible on a single CPU core. In addition, we have developed a platform for the calculation of relative free energies.