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基于动力学的药效团模型用于筛选分枝杆菌环丙烷合酶的潜在抑制剂。

Dynamics based pharmacophore models for screening potential inhibitors of mycobacterial cyclopropane synthase.

作者信息

Choudhury Chinmayee, Priyakumar U Deva, Sastry G Narahari

机构信息

†Centre for Computational Natural Sciences and Bioinformatics, International Institute of Information and Technology, Hyderabad 500032, India.

‡Centre for Molecular Modeling, Indian Institute of Chemical Technology, Hyderabad 500007, India.

出版信息

J Chem Inf Model. 2015 Apr 27;55(4):848-60. doi: 10.1021/ci500737b. Epub 2015 Mar 16.

Abstract

The therapeutic challenges in the treatment of tuberculosis demand multidisciplinary approaches for the identification of potential drug targets as well as fast and accurate techniques to screen huge chemical libraries. Mycobacterial cyclopropane synthase (CmaA1) has been shown to be essential for the survival of the bacteria due to its critical role in the synthesis of mycolic acids. The present study proposes pharmacophore models based on the structure of CmaA1 taking into account its various states in the cyclopropanation process, and their dynamic nature as assessed using molecular dynamics (MD) simulations. The qualities of these pharmacophore models were validated by mapping 23 molecules that have been previously reported to exhibit inhibitory activities on CmaA1. Additionally, 1398 compounds that have been shown to be inactive for tuberculosis were collected from the ChEMBL database and were screened against the models for validation. The models were further validated by comparing the results from pharmacophore mapping with the results obtained from docking these molecules with the respective protein structures. The best models are suggested by validating all the models based on their screening abilities and by comparing with docking results. The models generated from the MD trajectories were found to perform better than the one generated based on the crystal structure demonstrating the importance of incorporating receptor flexibility in drug design.

摘要

结核病治疗中的治疗挑战需要多学科方法来识别潜在的药物靶点,以及快速准确的技术来筛选庞大的化学文库。分枝杆菌环丙烷合酶(CmaA1)已被证明因其在分枝菌酸合成中的关键作用而对细菌的存活至关重要。本研究基于CmaA1的结构提出了药效团模型,同时考虑了其在环丙烷化过程中的各种状态,以及使用分子动力学(MD)模拟评估的动态性质。通过绘制先前报道的对CmaA1具有抑制活性的23个分子,验证了这些药效团模型的质量。此外,从ChEMBL数据库中收集了1398种已被证明对结核病无活性的化合物,并针对这些模型进行筛选以进行验证。通过将药效团映射结果与将这些分子与各自蛋白质结构对接获得的结果进行比较,进一步验证了模型。通过基于筛选能力验证所有模型并与对接结果进行比较,提出了最佳模型。发现从MD轨迹生成的模型比基于晶体结构生成的模型表现更好,这表明在药物设计中纳入受体灵活性的重要性。

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