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作为人类多药转运体 ABCG2 抑制剂的潜在药物候选物:一种计算机药物发现研究。

Prospective Drug Candidates as Human Multidrug Transporter ABCG2 Inhibitors: an In Silico Drug Discovery Study.

机构信息

Computational Chemistry Laboratory, Chemistry Department, Faculty of Science, Minia University, Minia, Egypt.

Department of Biology, College of Science, University of Hafr Al Batin, Hafr Al Batin, Saudi Arabia.

出版信息

Cell Biochem Biophys. 2021 Jun;79(2):189-200. doi: 10.1007/s12013-021-00985-y. Epub 2021 May 5.

Abstract

Breast cancer resistance protein (ABCG2) is a human ATP-binding cassette (ABC) that plays a paramount role in multidrug resistance (MDR) in cancer therapy. The discovery of ABCG2 inhibitors could assist in designing unprecedented therapeutic strategies for cancer treatment. There is as yet no approved drug targeting ABCG2, although a large number of drug candidates have been clinically investigated. In this work, binding affinities of 181 drug candidates in clinical-trial or investigational stages as ABCG2 inhibitors were inspected using in silico techniques. Based on available experimental data, the performance of AutoDock4.2.6 software was first validated to predict the inhibitor-ABCG2 binding mode and affinity. Combined molecular docking calculations and molecular dynamics (MD) simulations, followed by molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations, were then performed to filter out the studied drug candidates. From the estimated docking scores and MM-GBSA binding energies, six auspicious drug candidates-namely, pibrentasvir, venetoclax, ledipasvir, avatrombopag, cobicistat, and revefenacin-exhibited auspicious binding energies with value < -70.0 kcal/mol. Interestingly, pibrentasvir, venetoclax, and ledipasvir were observed to show even higher binding affinities with the ABCG2 transporter with binding energies of < -80.0 kcal/mol over long MD simulations of 100 ns. The stabilities of these three promising candidates in complex with ABCG2 transporter were demonstrated by their energetics and structural analyses throughout the 100 ns MD simulations. The current study throws new light on pibrentasvir, venetoclax, and ledipasvir as curative options for multidrug resistant cancers by inhibiting ABCG2 transporter.

摘要

乳腺癌耐药蛋白(ABCG2)是一种人类三磷酸腺苷(ATP)结合盒(ABC),在癌症治疗中的多药耐药(MDR)中起着至关重要的作用。发现 ABCG2 抑制剂可以帮助设计用于癌症治疗的前所未有的治疗策略。虽然已经有大量的候选药物在临床上进行了研究,但还没有针对 ABCG2 的批准药物。在这项工作中,使用计算机技术检查了 181 种处于临床试验或研究阶段的候选药物作为 ABCG2 抑制剂的结合亲和力。根据现有实验数据,首先验证了 AutoDock4.2.6 软件预测抑制剂-ABCG2 结合模式和亲和力的性能。然后进行了组合分子对接计算和分子动力学(MD)模拟,以及分子力学-广义 Born 表面面积(MM-GBSA)结合能计算,以筛选出研究中的候选药物。从估计的对接评分和 MM-GBSA 结合能来看,有六种有希望的候选药物——吡非尼酮、维奈托克、来迪派韦、阿伐曲泊帕、考比司他和瑞福替尼——表现出了良好的结合能,值小于-70.0 kcal/mol。有趣的是,吡非尼酮、维奈托克和来迪派韦在 100 ns 的 MD 模拟中,与 ABCG2 转运体的结合能甚至更高,值小于-80.0 kcal/mol。通过对这三种有前途的候选药物与 ABCG2 转运体复合物的能量和结构分析,证明了它们在整个 100 ns MD 模拟过程中的稳定性。本研究为抑制 ABCG2 转运体的多药耐药性癌症提供了吡非尼酮、维奈托克和来迪派韦作为治疗选择的新途径。

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