Nunthanavanit Patcharawee, Anthony Nahoum G, Johnston Blair F, Mackay Simon P, Ungwitayatorn Jiraporn
Faculty of Pharmacy, Srinakharinwirot University, Nakhon Nayok, Thailand.
Arch Pharm (Weinheim). 2008 Jun;341(6):357-64. doi: 10.1002/ardp.200700229.
Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed for chromone derivatives against HIV-1 protease using molecular field analysis (MFA) with genetic partial least square algorithms (G/PLS). Three different alignment methods: field fit, pharmacophore-based, and receptor-based were used to derive three MFA models. All models produced good predictive ability with high cross-validated r(2) (r(2) (cv)), conventional r(2), and predictive r(2)(r(2)(pred)) values. The receptor-based MFA showed the best statistical results with r(2) (cv) = 0.789, r(2)= 0.886, and r(2)(pred) = 0.995. The result obtained from the receptor-based model was compared with the docking simulation of the most active compound 21 in this chromone series to the binding pocket of HIV-1 protease (PDB entry 1AJX). It was shown that the MFA model related well with the binding structure of the complex and can provide guidelines to design more potent HIV-1 protease inhibitors.
使用遗传偏最小二乘算法（G/PLS）的分子场分析（MFA），针对色酮衍生物抗HIV-1蛋白酶构建了三维定量构效关系（3D-QSAR）模型。采用三种不同的比对方法：场拟合、基于药效团和基于受体，推导得到三个MFA模型。所有模型均具有良好的预测能力，具有较高的交叉验证r(2)（r(2) (cv)）、常规r(2)和预测r(2)（r(2)(pred)）值。基于受体的MFA显示出最佳的统计结果，r(2) (cv) = 0.789，r(2)= 0.886，r(2)(pred) = 0.995。将基于受体模型得到的结果与该色酮系列中活性最高的化合物21与HIV-1蛋白酶结合口袋（PDB编号1AJX）的对接模拟结果进行比较。结果表明，MFA模型与复合物的结合结构相关性良好，可为设计更有效的HIV-1蛋白酶抑制剂提供指导。
