Motivation: The need for efficient molecular docking tools for high-throughput screening is growing alongside the rapid growth of drug-fragment databases. AutoDock Vina ('Vina') is a widely used docking tool with parallelization for speed. QuickVina ('QVina 1') then further enhanced the speed via a heuristics, requiring high exhaustiveness. With low exhaustiveness, its accuracy was compromised. We present in this article the latest version of QuickVina ('QVina 2') that inherits both the speed of QVina 1 and the reliability of the original Vina.Results: We tested the efficacy of QVina 2 on the core set of PDBbind 2014. With the default exhaustiveness level of Vina (i.e. 8), a maximum of 20.49-fold and an average of 2.30-fold acceleration with a correlation coefficient of 0.967 for the first mode and 0.911 for the sum of all modes were attained over the original Vina. A tendency for higher acceleration with increased number of rotatable bonds as the design variables was observed. On the accuracy, Vina wins over QVina 2 on 30% of the data with average energy difference of only 0.58 kcal/mol. On the same dataset, GOLD produced RMSD smaller than 2 angstrom on 56.9% of the data while QVina 2 attained 63.1%.
Bioinformatics | Biostatistics
Oxford University Press (OUP): Policy B - Oxford Open Option B
ALHOSSARY, Amr; Stephanus Daniel, Handoko; MU, Yuguang; and KWOH, Chee-Keong.
Fast, accurate, and reliable molecular docking with QuickVina 2. (2015). Bioinformatics. 31, (13), 2214-2216. Research Collection School Of Information Systems.
Available at: https://ink.library.smu.edu.sg/sis_research/3255
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