GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing.

Computational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targe...

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Main Authors: Ye Fang, Yun Ding, Wei P Feinstein, David M Koppelman, Juana Moreno, Mark Jarrell, J Ramanujam, Michal Brylinski
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4946785?pdf=render
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spelling doaj-30d37a33a48d4be3bda9c6973febbef42020-11-25T01:07:19ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-01117e015889810.1371/journal.pone.0158898GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing.Ye FangYun DingWei P FeinsteinDavid M KoppelmanJuana MorenoMark JarrellJ RamanujamMichal BrylinskiComputational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targets. Because of a large number of drug candidates to be evaluated, an accurate and fast docking engine is a critical element of virtual screening. Consequently, highly optimized docking codes are of paramount importance for the effectiveness of virtual screening methods. In this communication, we describe the implementation, tuning and performance characteristics of GeauxDock, a recently developed molecular docking program. GeauxDock is built upon the Monte Carlo algorithm and features a novel scoring function combining physics-based energy terms with statistical and knowledge-based potentials. Developed specifically for heterogeneous computing platforms, the current version of GeauxDock can be deployed on modern, multi-core Central Processing Units (CPUs) as well as massively parallel accelerators, Intel Xeon Phi and NVIDIA Graphics Processing Unit (GPU). First, we carried out a thorough performance tuning of the high-level framework and the docking kernel to produce a fast serial code, which was then ported to shared-memory multi-core CPUs yielding a near-ideal scaling. Further, using Xeon Phi gives 1.9× performance improvement over a dual 10-core Xeon CPU, whereas the best GPU accelerator, GeForce GTX 980, achieves a speedup as high as 3.5×. On that account, GeauxDock can take advantage of modern heterogeneous architectures to considerably accelerate structure-based virtual screening applications. GeauxDock is open-sourced and publicly available at www.brylinski.org/geauxdock and https://figshare.com/articles/geauxdock_tar_gz/3205249.http://europepmc.org/articles/PMC4946785?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Ye Fang
Yun Ding
Wei P Feinstein
David M Koppelman
Juana Moreno
Mark Jarrell
J Ramanujam
Michal Brylinski
spellingShingle Ye Fang
Yun Ding
Wei P Feinstein
David M Koppelman
Juana Moreno
Mark Jarrell
J Ramanujam
Michal Brylinski
GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing.
PLoS ONE
author_facet Ye Fang
Yun Ding
Wei P Feinstein
David M Koppelman
Juana Moreno
Mark Jarrell
J Ramanujam
Michal Brylinski
author_sort Ye Fang
title GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing.
title_short GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing.
title_full GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing.
title_fullStr GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing.
title_full_unstemmed GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing.
title_sort geauxdock: accelerating structure-based virtual screening with heterogeneous computing.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2016-01-01
description Computational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targets. Because of a large number of drug candidates to be evaluated, an accurate and fast docking engine is a critical element of virtual screening. Consequently, highly optimized docking codes are of paramount importance for the effectiveness of virtual screening methods. In this communication, we describe the implementation, tuning and performance characteristics of GeauxDock, a recently developed molecular docking program. GeauxDock is built upon the Monte Carlo algorithm and features a novel scoring function combining physics-based energy terms with statistical and knowledge-based potentials. Developed specifically for heterogeneous computing platforms, the current version of GeauxDock can be deployed on modern, multi-core Central Processing Units (CPUs) as well as massively parallel accelerators, Intel Xeon Phi and NVIDIA Graphics Processing Unit (GPU). First, we carried out a thorough performance tuning of the high-level framework and the docking kernel to produce a fast serial code, which was then ported to shared-memory multi-core CPUs yielding a near-ideal scaling. Further, using Xeon Phi gives 1.9× performance improvement over a dual 10-core Xeon CPU, whereas the best GPU accelerator, GeForce GTX 980, achieves a speedup as high as 3.5×. On that account, GeauxDock can take advantage of modern heterogeneous architectures to considerably accelerate structure-based virtual screening applications. GeauxDock is open-sourced and publicly available at www.brylinski.org/geauxdock and https://figshare.com/articles/geauxdock_tar_gz/3205249.
url http://europepmc.org/articles/PMC4946785?pdf=render
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