Literature DB >> 29532496

Fast and flexible gpu accelerated binding free energy calculations within the amber molecular dynamics package.

Daniel J Mermelstein1, Charles Lin1,2, Gard Nelson3, Rachael Kretsch1,4, J Andrew McCammon1, Ross C Walker1,2.   

Abstract

Alchemical free energy (AFE) calculations based on molecular dynamics (MD) simulations are key tools in both improving our understanding of a wide variety of biological processes and accelerating the design and optimization of therapeutics for numerous diseases. Computing power and theory have, however, long been insufficient to enable AFE calculations to be routinely applied in early stage drug discovery. One of the major difficulties in performing AFE calculations is the length of time required for calculations to converge to an ensemble average. CPU implementations of MD-based free energy algorithms can effectively only reach tens of nanoseconds per day for systems on the order of 50,000 atoms, even running on massively parallel supercomputers. Therefore, converged free energy calculations on large numbers of potential lead compounds are often untenable, preventing researchers from gaining crucial insight into molecular recognition, potential druggability and other crucial areas of interest. Graphics Processing Units (GPUs) can help address this. We present here a seamless GPU implementation, within the PMEMD module of the AMBER molecular dynamics package, of thermodynamic integration (TI) capable of reaching speeds of >140 ns/day for a 44,907-atom system, with accuracy equivalent to the existing CPU implementation in AMBER. The implementation described here is currently part of the AMBER 18 beta code and will be an integral part of the upcoming version 18 release of AMBER.
© 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Entities:  

Keywords:  AMBER; GPU accelerated; binding free energy; drug design; molecular dynamics

Mesh:

Substances:

Year:  2018        PMID: 29532496     DOI: 10.1002/jcc.25187

Source DB:  PubMed          Journal:  J Comput Chem        ISSN: 0192-8651            Impact factor:   3.376


  15 in total

1.  Simulating Water Exchange to Buried Binding Sites.

Authors:  Ido Y Ben-Shalom; Charles Lin; Tom Kurtzman; Ross C Walker; Michael K Gilson
Journal:  J Chem Theory Comput       Date:  2019-03-13       Impact factor: 6.006

2.  Alchemical Binding Free Energy Calculations in AMBER20: Advances and Best Practices for Drug Discovery.

Authors:  Tai-Sung Lee; Bryce K Allen; Timothy J Giese; Zhenyu Guo; Pengfei Li; Charles Lin; T Dwight McGee; David A Pearlman; Brian K Radak; Yujun Tao; Hsu-Chun Tsai; Huafeng Xu; Woody Sherman; Darrin M York
Journal:  J Chem Inf Model       Date:  2020-09-16       Impact factor: 4.956

3.  Fast Equilibration of Water between Buried Sites and the Bulk by Molecular Dynamics with Parallel Monte Carlo Water Moves on Graphical Processing Units.

Authors:  Ido Y Ben-Shalom; Charles Lin; Brian K Radak; Woody Sherman; Michael K Gilson
Journal:  J Chem Theory Comput       Date:  2021-11-11       Impact factor: 6.006

4.  Accelerating AutoDock Vina with GPUs.

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5.  Accounting for the Central Role of Interfacial Water in Protein-Ligand Binding Free Energy Calculations.

Authors:  Ido Y Ben-Shalom; Zhixiong Lin; Brian K Radak; Charles Lin; Woody Sherman; Michael K Gilson
Journal:  J Chem Theory Comput       Date:  2020-11-18       Impact factor: 6.006

Review 6.  Thermodynamics and Kinetics of Drug-Target Binding by Molecular Simulation.

Authors:  Sergio Decherchi; Andrea Cavalli
Journal:  Chem Rev       Date:  2020-10-02       Impact factor: 60.622

7.  Accelerating AutoDock4 with GPUs and Gradient-Based Local Search.

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Journal:  J Chem Theory Comput       Date:  2021-01-06       Impact factor: 6.006

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Authors:  Edoardo L M Gelardi; Giorgia Colombo; Francesca Picarazzi; Davide M Ferraris; Andrea Mangione; Giovanni Petrarolo; Eleonora Aronica; Menico Rizzi; Mattia Mori; Concettina La Motta; Silvia Garavaglia
Journal:  Cancers (Basel)       Date:  2021-01-19       Impact factor: 6.639

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Authors:  Zheng Zheng; Oleg Y Borbulevych; Hao Liu; Jianpeng Deng; Roger I Martin; Lance M Westerhoff
Journal:  J Chem Inf Model       Date:  2020-09-11       Impact factor: 4.956

Review 10.  How Computational Chemistry and Drug Delivery Techniques Can Support the Development of New Anticancer Drugs.

Authors:  Mariangela Garofalo; Giovanni Grazioso; Andrea Cavalli; Jacopo Sgrignani
Journal:  Molecules       Date:  2020-04-10       Impact factor: 4.411

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