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针对临床药物针对多种癌症激酶靶点进行药物重新利用的综合分子对接和动态模拟。

Comprehensive molecular docking and dynamic simulations for drug repurposing of clinical drugs against multiple cancer kinase targets.

作者信息

Shaikh Nilofer, Linthoi R K, Swamy K V, Karthikeyan Muthukumarasamy, Vyas Renu

机构信息

MIT School of Bioengineering Sciences & Research, MIT Art, Design and Technology University, Pune, Maharashtra, India.

CEPD CSIR-National Chemical Laboratory, Pune, Maharashtra, India.

出版信息

J Biomol Struct Dyn. 2023 Sep-Oct;41(16):7735-7743. doi: 10.1080/07391102.2022.2124453. Epub 2022 Sep 22.

DOI:10.1080/07391102.2022.2124453
PMID:36134605
Abstract

Drug repurposing is a method to identify novel therapeutic agents from the existing drugs and clinical compounds. In the present comprehensive work, molecular docking, virtual screening and dynamics simulations were carried out for ten cancer types viz breast, colon, central nervous system, leukaemia, melanoma, ovarian, prostate, renal and lung (non-small and small cell) against validated eighteen kinase targets. The study aims to understand the action of chemotherapy drugs mechanism through binding interactions against selected targets via comparative docking simulations with the state-art molecular modelling suits such as MOE, Cresset-Flare, AutoDock Vina, GOLD and GLIDE. Chemotherapeutic drugs ( = 112) were shortlisted from standard drug databases with appropriate chemoinformatic filters. Based on docking studies it was revealed that leucovorin, nilotinib, ellence, thalomid and carfilzomib drugs possessed potential against other cancer targets. A library was built to enumerate novel molecules based on the scaffold and functional groups extracted from known drugs and clinical compounds. Twenty novel molecules were prioritised further based on drug-like attributes. These were cross docked against 1MQ4 Aurora-A Protein Kinase for prostate cancer and 4UYA Mitogen-activated protein kinase for renal cancer. All docking programs yielded similar results but interestingly AutoDock Vina yielded the lowest RMSD with the native ligand. To further validate the final docking results at atomistic level, molecular dynamics simulations were performed to ascertain the stability of the protein-ligand complex. The study enables repurposing of drugs and lead identification by employing a host of structure and ligand based virtual screening tools and techniques.Communicated by Ramaswamy H. Sarma.

摘要

药物重新利用是一种从现有药物和临床化合物中识别新型治疗药物的方法。在当前这项全面的研究中,针对乳腺癌、结肠癌、中枢神经系统癌、白血病、黑色素瘤、卵巢癌、前列腺癌、肾癌以及肺癌(非小细胞肺癌和小细胞肺癌)这十种癌症类型,针对经验证的18种激酶靶点进行了分子对接、虚拟筛选和动力学模拟。该研究旨在通过与诸如MOE、Cresset - Flare、AutoDock Vina、GOLD和GLIDE等先进的分子建模软件进行比较对接模拟,来了解化疗药物通过与选定靶点的结合相互作用的作用机制。通过适当的化学信息学筛选,从标准药物数据库中筛选出了112种化疗药物。基于对接研究发现,亚叶酸钙、尼洛替尼、埃罗替尼、沙利度胺和卡非佐米等药物对其他癌症靶点具有潜在活性。基于从已知药物和临床化合物中提取的支架和官能团构建了一个文库,以枚举新型分子。基于类药物属性进一步筛选出了20种新型分子。这些分子与用于前列腺癌的1MQ4极光激酶A蛋白和用于肾癌的4UYA丝裂原活化蛋白激酶进行了交叉对接。所有对接程序都产生了相似的结果,但有趣的是,AutoDock Vina与天然配体产生的均方根偏差(RMSD)最低。为了在原子水平上进一步验证最终的对接结果,进行了分子动力学模拟以确定蛋白质 - 配体复合物的稳定性。该研究通过使用一系列基于结构和配体的虚拟筛选工具和技术,实现了药物的重新利用和先导化合物的识别。由拉马斯瓦米·H·萨尔马传达。

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