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通过三维定量构效关系、分子对接和分子动力学模拟对耐甲氧西林金黄色葡萄球菌抑制剂进行合理设计。

Rational design of methicillin resistance staphylococcus aureus inhibitors through 3D-QSAR, molecular docking and molecular dynamics simulations.

作者信息

Ballu Srilata, Itteboina Ramesh, Sivan Sree Kanth, Manga Vijjulatha

机构信息

Molecular Modeling and Medicinal Chemistry Group, Department of Chemistry, University College of Science, Osmania University, Hyderabad 07, India.

Molecular Modeling and Medicinal Chemistry Group, Department of Chemistry, University College of Science, Osmania University, Hyderabad 07, India.

出版信息

Comput Biol Chem. 2018 Apr;73:95-104. doi: 10.1016/j.compbiolchem.2017.12.007. Epub 2017 Dec 20.

Abstract

Staphylococcus aureus is a gram positive bacterium. It is the leading cause of skin and respiratory infections, osteomyelitis, Ritter's disease, endocarditis, and bacteraemia in the developed world. We employed combined studies of 3D QSAR, molecular docking which are validated by molecular dynamics simulations and in silico ADME prediction have been performed on Isothiazoloquinolones inhibitors against methicillin resistance Staphylococcus aureus. Three-dimensional quantitative structure-activity relationship (3D-QSAR) study was applied using comparative molecular field analysis (CoMFA) with Q of 0.578, R of 0.988, and comparative molecular similarity indices analysis (CoMSIA) with Q of 0.554, R of 0.975. The predictive ability of these model was determined using a test set of molecules that gave acceptable predictive correlation (r Pred) values 0.55 and 0.57 of CoMFA and CoMSIA respectively. Docking, simulations were employed to position the inhibitors into protein active site to find out the most probable binding mode and most reliable conformations. Developed models and Docking methods provide guidance to design molecules with enhanced activity.

摘要

金黄色葡萄球菌是一种革兰氏阳性细菌。在发达国家,它是皮肤和呼吸道感染、骨髓炎、 Ritter 病、心内膜炎及菌血症的主要病因。我们采用了 3D QSAR(三维定量构效关系)与分子对接相结合的研究方法,这些方法通过分子动力学模拟进行了验证,并对异噻唑并喹啉酮类抗甲氧西林耐药金黄色葡萄球菌抑制剂进行了计算机辅助药物代谢动力学预测。应用比较分子场分析(CoMFA)进行三维定量构效关系(3D-QSAR)研究,Q 值为 0.578,R 值为 0.988;应用比较分子相似性指数分析(CoMSIA),Q 值为 0.554,R 值为 0.975。使用一组测试分子来确定这些模型的预测能力,CoMFA 和 CoMSIA 的预测相关(r Pred)值分别为 0.55 和 0.57,结果令人满意。采用对接和模拟方法将抑制剂定位到蛋白质活性位点,以找出最可能的结合模式和最可靠的构象。所建立的模型和对接方法为设计活性增强的分子提供了指导。

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