Development and evaluation of a new statistical model for structure-based high-throughput virtual screening
Source: International Journal of Bioinformatics Research and Applications, Volume 5, Number 3, 11 June 2009 , pp. 269-279(11)
Publisher: Inderscience Publishers
Abstract:We have developed a High-Performance Computing (HPC)-based molecular docking scheme, termed HiPCDock, for drug discovery and development. To improve the statistical significance of our screening results, a bioinformatics approach, motivated by a sequence alignment package BLAST, was implemented. The statistical model was validated with ten known Thymidine Kinase (TK) binders and the real inhibitors showed significant statistics, in terms of low probabilities and expectation values. Our HiPCDock has been implemented to be used by both computational experts and experimental scientists. Thus it is an automated, easy-to-use, and efficient package for molecular docking-based high-throughput virtual screening in drug discovery.
Keywords: TECHNICAL JOURNALS; Biosciences and Bioinformatics; COMPUTING AND MATHEMATICS JOURNALS; Computing Science, Applications and Software; HEALTHCARE AND LEISURE JOURNALS; Healthcare and Medical Engineering
Document Type: Research article
Affiliations: 1: Department of Experimental Therapeutics, The University of Texas M. D. Anderson Cancer Center, Unit 36, Houston, TX 77030, USA. 2: Department of Experimental Therapeutics, The University of Texas M. D. Anderson Cancer Center, Unit 36, Houston, TX 77030, USA
Publication date: 2009-06-11
- The International Journal of Bioinformatics Research and Applications addresses the most innovative developments, research issues and solutions in bioinformatics and computational biology and their applications.
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