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A combination of docking, QM/MM methods, and MD simulation for binding affinity estimation of metalloprotein ligands

期刊

JOURNAL OF MEDICINAL CHEMISTRY
卷 48, 期 17, 页码 5437-5447

出版社

AMER CHEMICAL SOC
DOI: 10.1021/jm049050v

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资金

  1. NCRR NIH HHS [P20 RR016471-066969, P20 RR016471-077190, P20 RR015566-010003, P20 RR015566-030003, P20 RR015566-050003, 1P20RR16471, P20 RR015566, P20 RR016471-055391, P20 RR016471, 1P20RR15566, P20 RR015566-020003, P20 RR015566-040003] Funding Source: Medline

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To alleviate the problems in the receptor-based design of metalloprotein ligands due to inadequacies in the force-field description of coordination bonds, a four-tier approach was devised. Representative ligand-metalloprotein interaction energies are obtained by subsequent application of (1) docking with metal-binding-guided selection of modes, (2) optimization of the ligand-metalloprotein complex geometry by combined quantum mechanics and molecular mechanics (QM/MM) methods, (3) conformational sampling of the complex with constrained metal bonds by force-field-based molecular dynamics (MD), and (4) a single point QM/MM energy calculation for the time-averaged structures. The QM/MM interaction energies are, in a linear combination with the desolvation-characterizing changes in the solvent-accessible surface areas, correlated with experimental data. The approach was applied to structural correlation of published binding free energies of a diverse set of 28 hydroxamate inhibitors to zinc-dependent matrix metalloproteinase 9 (MMP-9). Inclusion of steps 3 and 4 significantly improved both correlation and prediction. The two descriptors explained 90% of variance in inhibition constants of all 28 inhibitors, ranging from 0.08 to 349 nM, with the average unassigned error of 0.318 log units. The structural and energetic information obtained from the time-averaged MD simulation results helped understand the differences in binding modes of related compounds.

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