Rajamani Ramkumar, Good Andrew C
Computer-Assisted Drug Design, Bristol-Myers Squibb Co, 5 Research Parkway, Wallingford, CT 06492, USA.
Curr Opin Drug Discov Devel. 2007 May;10(3):308-15.
The ability to accurately predict the potency of ligand binding to its intended target prior to synthesis is of significant value in the drug-discovery paradigm. The protocols designed to this end follow a two-step process. First, ligands are docked into the active site of interest, and then the resulting interactions at the target are scored. Scoring functions form the key component in this process, providing a quantitative measure of fit quality. There is an abundance of new research in the field of scoring function design, from incorporation of novel descriptors (derived from first principles or empirical analysis) to function redesign based on improved data set handling. This article provides a brief overview on the state-of-the-art developments in the field, with particular reference to their performance in relation to expected outcomes.
在药物发现模式中,能够在合成之前准确预测配体与其预期靶点结合的效力具有重要价值。为此设计的方案遵循两步过程。首先,将配体对接至感兴趣的活性位点,然后对靶点处产生的相互作用进行评分。评分函数是此过程的关键组成部分,提供了拟合质量的定量度量。在评分函数设计领域有大量新研究,从纳入新描述符(源自第一原理或实证分析)到基于改进数据集处理的函数重新设计。本文简要概述了该领域的最新进展,特别提及了它们相对于预期结果的性能。