Ligand Aligning Method for Molecular Docking: Alignment of Property-Weighted Vectors
- Authors
- Joung, Jong Young; Nam, Ky-Youb; Cho, Kwang-Hwi; No, Kyoung Tai
- Issue Date
- Apr-2012
- Publisher
- AMER CHEMICAL SOC
- Citation
- JOURNAL OF CHEMICAL INFORMATION AND MODELING, v.52, no.4, pp.984 - 995
- Journal Title
- JOURNAL OF CHEMICAL INFORMATION AND MODELING
- Volume
- 52
- Number
- 4
- Start Page
- 984
- End Page
- 995
- URI
- http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/12468
- DOI
- 10.1021/ci200501p
- ISSN
- 1549-9596
- Abstract
- To reduce searching effort in conformational space of ligand docking positions, we propose an algorithm that generates initial binding positions of the ligand in a target protein, based on the property-weighted vector (P-weiV), the three-dimensional orthogonal vector determined by the molecular property of hydration-free energy density. The alignment of individual P-weiVs calculated separately for the ligand and the protein gives the initial orientation of a given ligand conformation relative to an active site; these initial orientations are then ranked by simple energy functions, including solvation, Because we are using three-dimensional orthogonal vectors to be aligned, only four orientations of ligand positions are possible for each ligand conformation, which reduces the search space dramatically. We found that the performance of P-weiV compared favorably to the use of principle moment of inertia (PMI) as implemented in LigandFit when we tested the abilities of the two approaches to correctly predict 205 protein-ligand complex data sets from the PDBBind database. P-weiV correctly predicted the alignment of ligands (within rmsd of 2.5 angstrom) with 57.6% reliability (118/205) for the top 10 ranked conformations and with 74.1% reliability (152/205) for the top 50 ranked conformations of Catalyst-generated conformers, as compared to 22.9% (47/205) and 31.2% (64/205), respectively, in the case of PMI with the same conformer set.
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Collections - College of Natural Sciences > School of Systems and Biomedical Science > 1. Journal Articles
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