Schmidt Tobias, Bergner Andreas, Schwede Torsten
Biozentrum, University of Basel, Klingelbergstrasse 50-70, 4056 Basel, Switzerland; SIB Swiss Institute of Bioinformatics, 4056 Basel, Switzerland.
Biozentrum, University of Basel, Klingelbergstrasse 50-70, 4056 Basel, Switzerland; SIB Swiss Institute of Bioinformatics, 4056 Basel, Switzerland.
Drug Discov Today. 2014 Jul;19(7):890-7. doi: 10.1016/j.drudis.2013.10.027. Epub 2013 Nov 8.
A structural perspective of drug target and anti-target proteins, and their molecular interactions with biologically active molecules, largely advances many areas of drug discovery, including target validation, hit and lead finding and lead optimisation. In the absence of experimental 3D structures, protein structure prediction often offers a suitable alternative to facilitate structure-based studies. This review outlines recent methodical advances in homology modelling, with a focus on those techniques that necessitate consideration of ligand binding. In this context, model quality estimation deserves special attention because the accuracy and reliability of different structure prediction techniques vary considerably, and the quality of a model ultimately determines its usefulness for structure-based drug discovery. Examples of G-protein-coupled receptors (GPCRs) and ADMET-related proteins were selected to illustrate recent progress and current limitations of protein structure prediction. Basic guidelines for good modelling practice are also provided.
药物靶标和反靶标蛋白的结构视角,以及它们与生物活性分子的分子相互作用,在很大程度上推动了药物发现的许多领域,包括靶标验证、先导化合物发现和先导化合物优化。在缺乏实验性三维结构的情况下,蛋白质结构预测通常提供了一种合适的替代方法,以促进基于结构的研究。本综述概述了同源建模的最新方法进展,重点关注那些需要考虑配体结合的技术。在这种情况下,模型质量评估值得特别关注,因为不同结构预测技术的准确性和可靠性差异很大,而模型的质量最终决定了其在基于结构的药物发现中的有用性。选择G蛋白偶联受体(GPCR)和ADMET相关蛋白的例子来说明蛋白质结构预测的最新进展和当前局限性。还提供了良好建模实践的基本指南。