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通过多种经过验证的建模技术,为苯并恶唑类潜在胆固醇酯转移蛋白(CETP)抑制剂的合理设计提供可靠的结构信息。

Reliable structural information for rational design of benzoxazole type potential cholesteryl ester transfer protein (CETP) inhibitors through multiple validated modeling techniques.

机构信息

Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University , Kolkata , West Bengal , India.

Laboratory of Drug Design and Discovery, Department of Pharmaceutical Sciences, Dr. Harisingh Gour University , Sagar , Madhya Pradesh , India.

出版信息

J Biomol Struct Dyn. 2019 Oct;37(17):4528-4541. doi: 10.1080/07391102.2018.1552895. Epub 2019 Jan 11.

DOI:10.1080/07391102.2018.1552895
PMID:30488780
Abstract

The drug design and discovery of lipid modulators is very demanding as no new molecule has entered into the market in the last 35 years. Cholesteryl ester transfer protein (CETP) is a promising target as lipid modulators. Inhibition of the CETP enzyme reduces the risk of cardiovascular events. The first CETP inhibitor torcetrapib and related drug candidates failed in the clinical trial due to the off-target effects leading to high toxicity. Thus, newer CETP inhibitors have now paramount importance to accelerate the drug discovery efforts in the field of cardiovascular disease (CVD). In the present study, 140 benzoxazole compounds were studied by using different chemometric techniques, for example, pharmacophore mapping, molecular docking, three-dimensional quantitative structure-activity relationship comparative molecular field analysis (3D-QSAR CoMFA), topomer CoMFA and Bayesian classification, in order to generate complete and reliable information regarding the structural requirements for the CETP inhibition. The best pharmacophore hypothesis was statistically significant (regression coefficient of 0.957 and a lower root mean square of 0.890). Molecular docking study revealed that cyano-substituted compounds form hydrogen bond with targeted macromolecule. The 3D-QSAR CoMFA model also produced a leave-one-out (LOO) cross-validated of 0.527, an of 0.853 and an of 0.603. Similarly, two topomer CoMFA models were also statistically significant and reliable in terms of their , and values. The Bayesian classification study also provided the excellent ROC values of 0.919 and 0.939 for training and test sets, respectively. Overall, this study may help in the rational design of newer benzoxazole type compounds with higher CETP inhibition. Communicated by Ramaswamy H. Sarma.

摘要

在过去的 35 年中,没有新的分子进入市场,因此设计和发现脂质调节剂的药物极具挑战性。胆固醇酯转移蛋白(CETP)是一种有前途的脂质调节剂靶点。抑制 CETP 酶可降低心血管事件的风险。第一个 CETP 抑制剂 torcetrapib 和相关药物候选物由于导致高毒性的脱靶效应而在临床试验中失败。因此,现在开发新型 CETP 抑制剂对于加速心血管疾病(CVD)领域的药物发现至关重要。在本研究中,使用不同的化学计量学技术(例如,药效团映射、分子对接、三维定量构效关系比较分子场分析(3D-QSAR CoMFA)、拓扑 CoMFA 和贝叶斯分类)研究了 140 种苯并恶唑化合物,以生成关于 CETP 抑制的结构要求的完整和可靠信息。最佳药效团假设具有统计学意义(回归系数为 0.957,较低的均方根为 0.890)。分子对接研究表明,氰基取代的化合物与靶大分子形成氢键。3D-QSAR CoMFA 模型还产生了 0.527 的交叉验证相关系数(LOO)、0.853 的相关系数和 0.603 的预测相关系数。同样,两个拓扑 CoMFA 模型在其、和值方面也具有统计学意义和可靠性。贝叶斯分类研究还为训练集和测试集分别提供了 0.919 和 0.939 的出色 ROC 值。总体而言,这项研究可能有助于合理设计具有更高 CETP 抑制作用的新型苯并恶唑类化合物。由 Ramaswamy H. Sarma 传达。

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