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基质金属蛋白酶抑制剂的虚拟高通量筛选

Virtual High-Throughput Screening for Matrix Metalloproteinase Inhibitors.

作者信息

Choi Jun Yong, Fuerst Rita

机构信息

Department of Chemistry, The Scripps Research Institute, Jupiter, FL, 33458, USA.

出版信息

Methods Mol Biol. 2017;1579:259-271. doi: 10.1007/978-1-4939-6863-3_14.

Abstract

Structure-based virtual screening (SBVS) is a common method for the fast identification of hit structures at the beginning of a medicinal chemistry program in drug discovery. The SBVS, described in this manuscript, is focused on finding small molecule hits that can be further utilized as a starting point for the development of inhibitors of matrix metalloproteinase 13 (MMP-13) via structure-based molecular design. We intended to identify a set of structurally diverse hits, which occupy all subsites (S1'-S3', S2, and S3) centering the zinc containing binding site of MMP-13, by the virtual screening of a chemical library comprising more than ten million commercially available compounds. In total, 23 compounds were found as potential MMP-13 inhibitors using Glide docking followed by the analysis of the structural interaction fingerprints (SIFt) of the docked structures.

摘要

基于结构的虚拟筛选(SBVS)是药物发现中药物化学项目初期快速鉴定活性结构的常用方法。本手稿中描述的SBVS专注于寻找小分子活性物质,这些物质可通过基于结构的分子设计进一步用作开发基质金属蛋白酶13(MMP - 13)抑制剂的起点。我们旨在通过对包含超过一千万种市售化合物的化学文库进行虚拟筛选,鉴定出一组结构多样的活性物质,这些活性物质占据以MMP - 13含锌结合位点为中心的所有亚位点(S1'-S3'、S2和S3)。使用Glide对接并随后分析对接结构的结构相互作用指纹(SIFt),总共发现了23种化合物作为潜在的MMP - 13抑制剂。

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