High Throughput Computing Validation for Drug Discovery Using the DOCK Program on a Massively Parallel System

This IBM® Redpaper publication presents a virtual screening study of the DOCK Version 6.0 molecular docking software package on a massively parallel system, the IBM System Blue Gene® supercomputer, Blue Gene/L.1 Virtual screening of very large libraries of small ligands requires not only efficient algorithms but an efficient implementation for docking thousands, if not millions, of compounds simultaneously in a reasonable amount of time.

This paper presents a series of receptor-ligand docking benchmarks using DOCK Version 6.0 to show performance improvements with better load balancing and file I/O improvements. In addition, a version was implemented to take advantage of the High Throughput Computing (HTC) feature on the Blue Gene supercomputer.

• IBM System Blue Gene Solution: Blue Gene/P Application Development, SG24-7287-03
• IBM System Blue Gene Solution: Blue Gene/P System Administration, SG24-7417-03
• IBM System Blue Gene Solution: Performance Analysis Tools, REDP-4256-01

Publish Date
16 April 2008

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Author(s)

P. Therese Lang is a postdoctoral scholar in the Alber Lab at the University of California, Berkeley. She recently received her Ph.D. degree from the Irwin D. Kuntz and Thomas L. James labs at the University of California, San Francisco, for assisting in developing DOCK Version 6 and exploring drug design for RNA targets. She has published several papers on the validation and application of docking programs for drug design.

• P. Therese Lang

Marcus E. Lundberg is currently a student in Scientific Computing at Uppsala University in Sweden. Marcus has a Bachelor of Science (BS) degree in Physics.

• Marcus E. Lundberg

Amanda Peters is an IBM Software Engineer for the Blue Gene supercomputers, in Rochester, Minnesota. She received a BS degree in both computer science and physics from Duke University in 2005. She is involved with the porting, validating, and optimizing of life science applications.

• Amanda Peters

Carlos P. Sosa is a Senior Technical Staff Member in the Blue Gene Development Group of IBM, where he has been the team lead of the Chemistry and Life Sciences high-performance effort since 2006. For the past 18 years, he has focused on scientific applications with emphasis in life sciences, parallel programming, benchmarking, and performance tuning. His areas of interest are future IBM POWER architectures, Blue Gene, Cell Broadband, and cellular molecular biology. He has authored or coauthored multiple papers and was a coauthor of two IBM Redbooks publications. He received a Ph.D. degree in Physical Chemistry from Wayne State University and completed his post-doctoral work at the Pacific Northwest National Laboratory. He is a member of the IEEE, the IEEE Computer Society, the American Chemical Society, and the International Society for Computational Biology.

• Carlos P. Sosa

IBM Form Number
REDP-4410-00

Number of pages

12