Toward Fast and Accurate Binding Affinity Prediction with pmemdGTI: An Efficient Implementation of GPU-Accelerated Thermodynamic Integration

Tai Sung Lee, Yuan Hu, Brad Sherborne, Zhuyan Guo, Darrin M. York

Research output: Contribution to journalArticlepeer-review

82 Scopus citations

Abstract

We report the implementation of the thermodynamic integration method on the pmemd module of the AMBER 16 package on GPUs (pmemdGTI). The pmemdGTI code typically delivers over 2 orders of magnitude of speed-up relative to a single CPU core for the calculation of ligand-protein binding affinities with no statistically significant numerical differences and thus provides a powerful new tool for drug discovery applications.

Original languageEnglish (US)
Pages (from-to)3077-3084
Number of pages8
JournalJournal of Chemical Theory and Computation
Volume13
Issue number7
DOIs
StatePublished - Jul 11 2017

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Physical and Theoretical Chemistry

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