Konteatis Zenon D, Klon Anthony E, Zou Jinming, Meshkat Siavash
Department of Design, Ansaris, Four Valley Square, Blue Bell, Pennsylvania, USA.
Methods Enzymol. 2011;493:357-80. doi: 10.1016/B978-0-12-381274-2.00014-5.
In silico fragment-based drug discovery has become an integral component of the new fragment-based approach that has evolved over the past decade. Protein structure of high quality is essential in carrying out computational designs, and protein flexibility has been shown to impact prospective designs or docking experiments. Here we introduce methodology to calculate protein normal modes and protein molecular dynamics in torsion space which enable the development of multiple protein states to address the natural flexibility of proteins. We also present two fragment-based sampling methods, grand canonical Monte Carlo and systematic sampling, which are used to study protein-fragment interactions by generating fragment ensembles and we discuss the process by which these ensembles are linked to design ligands.
基于计算机模拟片段的药物发现已成为过去十年中发展起来的新的基于片段方法的一个不可或缺的组成部分。高质量的蛋白质结构对于进行计算设计至关重要，并且已经表明蛋白质的柔性会影响前瞻性设计或对接实验。在这里，我们介绍了在扭转空间中计算蛋白质正常模式和蛋白质分子动力学的方法，这些方法能够开发多种蛋白质状态以解决蛋白质的天然柔性问题。我们还提出了两种基于片段的采样方法，即巨正则蒙特卡罗方法和系统采样方法，它们通过生成片段系综来研究蛋白质与片段的相互作用，并且我们讨论了将这些系综与设计配体相联系的过程。
