Evaluating molecular-docking methods for pose prediction and enrichment factors

被引:200
作者
Chen, HM [1 ]
Lyne, PD
Giordanetto, F
Lovell, T
Li, J
机构
[1] AstraZeneca R&D, GDECS Computat Chem, Molndal, Sweden
[2] AstraZeneca R&D, Canc Discovery, Boston, MA USA
[3] AstraZeneca R&D, Med Chem, Molndal, Sweden
关键词
D O I
10.1021/ci0503255
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
Four of the most well-known, commercially available docking programs, FlexX, GOLD, GLIDE, and ICM, have been examined for their ligand-docking and virtual-screening capabilities. The relative performance of the programs in reproducing the native ligand conformation from starting SMILES strings for 164 high-resolution protein-ligand complexes is presented and compared. Applying only the native scoring functions, the latest versions of these four docking programs were also used to conduct virtual screening for 12 protein targets of therapeutic interest, involving both publicly available structures and AstraZeneca in-house structures. The capability of the four programs to correctly rank-order target-specific active compounds over alternative binders and nonbinders (decoys plus randomly selected compounds) and thereby enrich a small subset of a screening library is compared. Enrichments from the virtual-screening experiments are contrasted with those obtained with alternative 3D shape-matching and 2D similarity database-search methods.
引用
收藏
页码:401 / 415
页数:15
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