Lill Markus A
Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, IN 47907, USA.
Drug Discov Today. 2007 Dec;12(23-24):1013-7. doi: 10.1016/j.drudis.2007.08.004. Epub 2007 Sep 19.
Quantitative structure-activity relationships (QSAR) is an area of computational research that builds virtual models to predict quantities such as the binding affinity or the toxic potential of existing or hypothetical molecules. Although a wealth of experimental data emphasizes the active role of the target protein in the binding process, QSAR studies are frequently restricted to the properties of the small-molecule ligand. This review aims at discussing recent QSAR concepts exploring higher dimensions (simulation of induced fit, simultaneous exploration of alternative binding modes, and solvation scenarios), and their benefit for the drug-discovery process.
定量构效关系（QSAR）是计算研究的一个领域，它构建虚拟模型来预测诸如现有或假设分子的结合亲和力或潜在毒性等数量。尽管大量实验数据强调了靶蛋白在结合过程中的积极作用，但QSAR研究通常仅限于小分子配体的性质。本综述旨在讨论探索更高维度的最新QSAR概念（诱导契合模拟、替代结合模式的同时探索和溶剂化情景）及其对药物发现过程的益处。
