首页> 外文期刊>Journal of combinatorial chemistry >Structure-based rational quest for potential novel inhibitors of human HMG-CoA reductase by combining CoMFA 3D QSAR modeling and virtual screening
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Structure-based rational quest for potential novel inhibitors of human HMG-CoA reductase by combining CoMFA 3D QSAR modeling and virtual screening

机译:结合CoMFA 3D QSAR建模和虚拟筛选对人HMG-CoA还原酶的潜在新型抑制剂进行基于结构的合理探索

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3-Hydroxy-3-methylglutaryl-coenzyme A reductase (HMGR) catalyzes the formation of mevalonate. In many classes of organisms, this is the committed step leading to the synthesis of essential compounds, such as cholesterol. However, a high level of cholesterol is an important risk factor for coronary heart disease, for which an effective clinical treatment is to block HMGR using inhibitors like statins. Recently the structures of catalytic portion of human HMGR complexed with six different statins have been determined by a delicate crystallography study (Istvan and Deisenhofer Science 2001, 292, 1160-1164), which established a solid basis of structure and mechanism for the rational design, optimization, and development of even better HMGR inhibitors. In this study, three-dimensional quantitative structure-activity relationship (3D QSAR) with comparative molecular field analysis (CoMFA) was performed on a training set of up to 35 statins and statin-like compounds. Predictive models were established by using two different ways: (1) Models-fit, obtained by SYBYL conventional fit-atom molecular alignment rule, has cross-validated coefficients (q(2)) up to 0.652 and regression coefficients (r(2)) up to 0.977. (2) Models-dock, obtained by FlexE by docking compounds into the HMGR active site, has cross-validated coefficients (q(2)) up to 0.731 and regression coefficients (r(2)) up to 0.947. These models were further validated by an external testing set of 12 statins and statin-like compounds. Integrated with CoMFA 3D QSAR predictive models, molecular surface property (electrostatic and steric) mapping and structure-based (both ligand and receptor) virtual screening have been employed to explore potential novel hits for the HMGR inhibitors. A representative set of eight new compounds of non-statin-like structures but with high pIC(50) values were sorted out in the present study.
机译:3-羟基-3-甲基戊二酰辅酶A还原酶(HMGR)催化甲羟戊酸的形成。在许多类型的生物中,这是导致必需化合物(例如胆固醇)合成的重要步骤。但是,高水平的胆固醇是冠心病的重要危险因素,对此有效的临床治疗方法是使用他汀类药物等抑制剂来阻断HMGR。最近,通过精细的晶体学研究(Istvan和Deisenhofer Science 2001,292,1160-1164)确定了人类HMGR与六种他汀类药物复合的催化部分的结构,该结构为合理设计奠定了坚实的结构和机理基础,优化和开发更好的HMGR抑制剂。在这项研究中,对多达35种他汀类药物和他汀类化合物的训练集进行了三维定量构效关系(3D QSAR)和比较分子场分析(CoMFA)。通过两种不同的方法建立了预测模型:(1)通过SYBYL常规拟合原子分子比对规则获得的模型拟合具有交叉验证系数(q(2))高达0.652和回归系数(r(2) )达到0.977。 (2)通过FlexE通过将化合物对接到HMGR活性位点而获得的Models-dock具有交叉验证系数(q(2))最高为0.731,回归系数(r(2))最高为0.947。通过12种他汀类药物和他汀类化合物的外部测试,进一步验证了这些模型。与CoMFA 3D QSAR预测模型相结合,分子表面性质(静电和空间)作图和基于结构的(配体和受体)虚拟筛选已被用于探索HMGR抑制剂的潜在新技术。在本研究中,选出了一组具有代表性的八种非他汀类结构但具有高pIC(50)值的新化合物。

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