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基于喹啉的衍生物作为潜在抗疟药的药物发现研究。

Drug discovery studies on quinoline-based derivatives as potential antimalarial agents.

作者信息

Sharma R, Patil S, Maurya P

机构信息

a School of Pharmacy , Devi Ahilya Vishwavidyalaya , Takshshila Campus, Madhya Pradesh , India.

出版信息

SAR QSAR Environ Res. 2014;25(3):189-203. doi: 10.1080/1062936X.2013.875484. Epub 2014 Mar 7.

DOI:10.1080/1062936X.2013.875484
PMID:24601770
Abstract

Molecular modelling studies were performed to identify the essential structural requirements of quinoline-based derivatives for improving their antimalarial activity. The developed CoMFA, CoMSIA and HQSAR models for a training set comprising 37 derivatives showed good statistical significance in terms of internal cross validation (q(2)) 0.70, 0.69 and 0.80 and non-cross validation (r(2)) 0.80, 0.79 and 0.80. Also, the predicted r(2) values (r(2)pred) of 0.63, 0.61 and 0.72 for a test set consisting of 12 compounds suggested significant predicting ability of the models. Structural features were correlated in terms of steric, electrostatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor interactions. Furthermore, the bioactive conformation was explored and explained by docking compounds #28, 32 and 40 into the active binding site of lactate dehydrogenase of Plasmodium falciparum. The QSAR models, contour map and docking binding affinity obtained could be successfully utilized as a guiding tool for the design and discovery of novel quinoline-based derivatives with potent antimalarial activity.

摘要

进行了分子建模研究,以确定喹啉基衍生物提高其抗疟活性的基本结构要求。针对包含37种衍生物的训练集开发的CoMFA、CoMSIA和HQSAR模型在内部交叉验证(q(2))分别为0.70、0.69和0.80以及非交叉验证(r(2))分别为0.80、0.79和0.80方面显示出良好的统计学意义。此外,由12种化合物组成的测试集的预测r(2)值(r(2)pred)分别为0.63、0.61和0.72,表明模型具有显著的预测能力。结构特征在空间、静电、疏水、氢键供体和氢键受体相互作用方面具有相关性。此外,通过将化合物#28、32和40对接至恶性疟原虫乳酸脱氢酶的活性结合位点,探索并解释了生物活性构象。所获得的QSAR模型、等高线图和对接结合亲和力可成功用作设计和发现具有强效抗疟活性的新型喹啉基衍生物的指导工具。

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