Discovery of novel inhibitors for c-Met by virtual screening and pharmacophore analysis

Calvin Yu-Chian Chen
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引用次数: 36

Abstract

The overexpression of human c-Met tyrosine kinase induces the tumor proliferation and migration. Commercial drug is still not available for inhibiting this target. The structure of human c-Met was simulated and validated by molecular modeling. Compounds from our laboratory database, including natural products and anticancer agents, were employed for the docking analysis. De Novo drug design was further performed for three compounds with highest DockScore value to discover the novel inhibitors. Through the adsorption, distribution, metabolism, excretion and toxicity (ADMET) descriptor, only compounds A2, B3, C2 and C5 were selected. Through the pharmacophore analysis, ARG1086, HIS1088, ARG1208, ASN1209, ALA1226, ARG1227, ASP1228, TYR1230, and GLU1233 were suggested as the key residues because of strong pharmacophore features. In addition, the pharmacophore features of candidates consisted with the active site properties. The added fragments produced the strong interaction with the surrounding residues and yielded hydrogen bonds (HBs). Thus, the interaction energy between the ligand and the receptor was enhanced. Besides, the values of several scoring functions (PLP1, PLP2, and DockScore) of candidates were comparatively higher than compounds A, B, C, and Kirin. According to the aforementioned analyses, compounds A, A2, B, B3, C, C2 and C5 were suggested as the potent c-Met inhibitors. Besides, the scaffolds of compounds A, B, and C provided the direction for further drug design.

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通过虚拟筛选和药效团分析发现新的c-Met抑制剂
人c-Met酪氨酸激酶过表达可诱导肿瘤的增殖和迁移。目前还没有抑制这一靶点的商业药物。通过分子模型模拟并验证了人体c-Met的结构。从我们的实验室数据库中提取化合物,包括天然产物和抗癌药物,用于对接分析。进一步对DockScore值最高的3个化合物进行从头药物设计,以发现新的抑制剂。通过吸附、分布、代谢、排泄和毒性(ADMET)描述符,只选择了化合物A2、B3、C2和C5。通过药效团分析,认为ARG1086、HIS1088、ARG1208、ASN1209、ALA1226、ARG1227、ASP1228、TYR1230和GLU1233是具有较强药效团特征的关键残基。此外,候选药物的药效团特征与活性位点性质一致。添加的片段与周围残基产生强相互作用,生成氢键(HBs)。从而提高了配体与受体之间的相互作用能。候选药物的多个评分函数(PLP1、PLP2、DockScore)值均高于化合物A、B、C和麒麟。根据上述分析,化合物A、A2、B、B3、C、C2和C5被认为是有效的C - met抑制剂。此外,化合物A、B和C的支架为进一步的药物设计提供了方向。
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