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采用配体和基于结构的虚拟筛选技术,针对癌症治疗,发现具有抗增殖活性的新型αβ-微管蛋白调节剂。

Identification of novel αβ-tubulin modulators with antiproliferative activity directed to cancer therapy using ligand and structure-based virtual screening.

机构信息

Computational Laboratory of Pharmaceutical Chemistry, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Av. do Café, s/n, Ribeirão Preto, SP 14040-903, Brazil.

Departamento de Química, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, 14040-901 Ribeirão Preto, SP, Brazil.

出版信息

Int J Biol Macromol. 2020 Dec 15;165(Pt B):3040-3050. doi: 10.1016/j.ijbiomac.2020.10.136. Epub 2020 Oct 22.

Abstract

Among several strategies related to cancer therapy targeting the modulation of αβ-tubulin has shown encouraging findings, more specifically when this is achieved by inhibitors located at the colchicine binding site. In this work, we aim to fish new αβ-tubulin modulators through a diverse and rational VS study, and thus, exhibiting the development of two VS pipelines. This allowed us to identify two compounds 5 and 9 that showed IC values of 19.69 and 21.97 μM, respectively, towards possible modulation of αβ-tubulin, such as assessed by in vitro assays in C6 glioma and HEPG2 cell lines. We also evaluated possible mechanisms of action of obtained hits towards the colchicine binding site of αβ-tubulin by using docking approaches. In addition, assessment of the stability of the active (5 and 9) and inactive compounds (3 and 13) within the colchicine binding site was carried out by molecular dynamics (MD) simulations, highlighting the solvent effect and revealing the compound 5 as the most stable in the complex. At last, deep analysis of these results provided some valuable insights on the importance of using mixed ligand- and structure-based strategies in VS campaigns, in order to achieve higher chemical diversity and biological effect as well.

摘要

在几种与癌症治疗相关的策略中,靶向调节 αβ-微管蛋白的策略显示出了令人鼓舞的结果,特别是当这种策略通过位于秋水仙碱结合位点的抑制剂来实现时。在这项工作中,我们旨在通过多样化和合理的虚拟筛选研究来寻找新的 αβ-微管蛋白调节剂,并因此展示了两个虚拟筛选管道的开发。这使我们能够识别出两种化合物 5 和 9,它们对 αβ-微管蛋白的可能调节作用的 IC 值分别为 19.69 和 21.97μM,如通过体外测定在 C6 神经胶质瘤和 HEPG2 细胞系中评估。我们还通过对接方法评估了获得的命中化合物对 αβ-微管蛋白秋水仙碱结合位点的可能作用机制。此外,通过分子动力学 (MD) 模拟对活性 (5 和 9) 和非活性化合物 (3 和 13) 在秋水仙碱结合位点内的稳定性进行了评估,突出了溶剂效应,并揭示了化合物 5 在复合物中最稳定。最后,对这些结果进行深入分析,为在虚拟筛选活动中使用混合配体和基于结构的策略提供了一些有价值的见解,以实现更高的化学多样性和生物学效果。

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