Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/102709
Title: | QuickVina : accelerating AutoDock Vina using gradient-based heuristics for global optimization | Authors: | Handoko, Stephanus Daniel Ouyang, Xuchang Su, Chinh Tran To Kwoh, Chee Keong Ong, Yew Soon |
Keywords: | DRNTU::Engineering::Computer science and engineering::Software | Issue Date: | 2012 | Source: | Handoko, S. D., Ouyang, X., Su, C. T. T., Kwoh, C. K., & Ong, Y. S. (2012). QuickVina : accelerating AutoDock Vina using gradient-based heuristics for global optimization. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 9(5), 1266-1272 . | Series/Report no.: | IEEE/ACM Transactions on Computational Biology and Bioinformatics | Abstract: | Predicting binding between macromolecule and small molecule is a crucial phase in the field of rational drug design. AutoDock Vina, one of the most widely used docking software released in 2009, uses an empirical scoring function to evaluate the binding affinity between the molecules and employs the iterated local search global optimizer for global optimization, achieving a significantly improved speed and better accuracy of the binding mode prediction compared its predecessor, AutoDock 4. In this paper, we propose further improvement in the local search algorithm of Vina by heuristically preventing some intermediate points from undergoing local search. Our improved version of Vina-dubbed QVina-achieved a maximum acceleration of about 25 times with the average speed-up of 8.34 times compared to the original Vina when tested on a set of 231 protein-ligand complexes while maintaining the optimal scores mostly identical. Using our heuristics, larger number of different ligands can be quickly screened against a given receptor within the same time frame. | URI: | https://hdl.handle.net/10356/102709 http://hdl.handle.net/10220/16520 |
ISSN: | 1545-5963 | DOI: | 10.1109/TCBB.2012.82 | Schools: | School of Computer Engineering | Research Centres: | Bioinformatics Research Centre Centre for Computational Intelligence |
Rights: | © 2012 IEEE | Fulltext Permission: | none | Fulltext Availability: | No Fulltext |
Appears in Collections: | SCSE Journal Articles |
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