Fast, accurate, and reliable molecular docking with QuickVina 2

• Main Authors: ALHOSSARY, Amr, HANDOKO, Stephanus Daniel, MU, Yuguang, KWOH, Chee-Keong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2015
• Subjects: Bioinformatics; Biostatistics
• Online Access: https://ink.library.smu.edu.sg/sis_research/3255; https://ink.library.smu.edu.sg/context/sis_research/article/4257/viewcontent/Fast__accurate__and_reliable_molecular_docking.pdf
• Institution: Singapore Management University

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%.