QSAR modeling of GPCR ligands: methodologies and examples of applications.

A Tropsha, S X Wang
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引用次数: 15

Abstract

GPCR ligands represent not only one of the major classes of current drugs but the major continuing source of novel potent pharmaceutical agents. Because 3D structures of GPCRs as determined by experimental techniques are still unavailable, ligand-based drug discovery methods remain the major computational molecular modeling approaches to the analysis of growing data sets of tested GPCR ligands. This paper presents an overview of modern Quantitative Structure Activity Relationship (QSAR) modeling. We discuss the critical issue of model validation and the strategy for applying the successfully validated QSAR models to virtual screening of available chemical databases. We present several examples of applications of validated QSAR modeling approaches to GPCR ligands. We conclude with the comments on exciting developments in the QSAR modeling of GPCR ligands that focus on the study of emerging data sets of compounds with dual or even multiple activities against two or more of GPCRs.

GPCR配体的QSAR建模:方法和应用实例。
GPCR配体不仅代表了当前药物的主要类别之一,而且是新型强效药物的主要持续来源。由于通过实验技术确定的GPCR的3D结构仍然不可用,基于配体的药物发现方法仍然是主要的计算分子建模方法,用于分析已测试GPCR配体的增长数据集。本文介绍了现代定量结构活动关系(QSAR)模型的研究概况。我们讨论了模型验证的关键问题,以及将成功验证的QSAR模型应用于可用化学数据库的虚拟筛选的策略。我们提出了几个应用验证的QSAR建模方法对GPCR配体的例子。最后,我们对GPCR配体的QSAR建模的令人兴奋的发展进行了评论,这些研究集中在对两种或两种以上GPCR具有双重甚至多重活性的化合物的新兴数据集的研究上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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