High‐throughput virtual molecular docking with AutoDockCloud. (13th September 2012)

• Record Type: Journal Article
• Authors: Ellingson, Sally R.; Baudry, Jerome; Qiu, Judy; Foster, Ian; Taylor, Ronald; Loidl, Hans‐Wolfgang; Singer, Jeremy
• Is Part Of: Concurrency and computation. Volume 26:Number 4(2014:Mar.)
• Page Start: 907
• Page End: 916
• Publication Date: 2012-09-13
• Subjects: Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.2926
• Languages: English
• ISSNs: 1532-0626

Abstract

<abstract abstract-type="main"> <title>ABSTRACT</title> <p>Virtual molecular docking is a computational method used in computer‐aided drug discovery that calculates the binding affinity of a small molecule drug candidate to a target protein. High‐throughput virtual screenings calculate the binding affinities for a large number of molecules at once and ranks potential drug candidates to greatly reduces the time and cost of suggesting new potential pharmaceuticals. This high‐throughput screening is a task parallel process and therefore well‐suited for distributed computing. In this study, we use the open source Hadoop framework implementing the MapReduce paradigm for distributed computing on a cloud platform and the widely used molecular docking program, AutoDock. The initial implementation of AutoDockCloud showed a speed‐up of 450 on Kandinsky, a cloud computer located at Oak Ridge National Laboratory. Further modifications show promise for a greater speed‐up of large chemical library screenings and also incorporates and distributes the pre‐docking procedures. Copyright © 2012 John Wiley &amp; Sons, Ltd.</p> </abstract>