Biomedical Informatics, Children's Hospital Research Foundation, Cincinnati, OH 45229, USA.
Hum Genomics. 2011 Jul;5(5):497-505. doi: 10.1186/1479-7364-5-5-497.
Progress in functional genomics and structural studies on biological macromolecules are generating a growing number of potential targets for therapeutics, adding to the importance of computational approaches for small molecule docking and virtual screening of candidate compounds. In this review, recent improvements in several public domain packages that are widely used in the context of drug development, including DOCK, AutoDock, AutoDock Vina and Screening for Ligands by Induced-fit Docking Efficiently (SLIDE) are surveyed. The authors also survey methods for the analysis and visualisation of docking simulations, as an important step in the overall assessment of the results. In order to illustrate the performance and limitations of current docking programs, the authors used the National Center for Toxicological Research (NCTR) oestrogen receptor benchmark set of 232 oestrogenic compounds with experimentally measured strength of binding to oestrogen receptor alpha. The methods tested here yielded a correlation coefficient of up to 0.6 between the predicted and observed binding affinities for active compounds in this benchmark.
生物大分子的功能基因组学和结构研究的进展正在产生越来越多的治疗靶点,这使得小分子对接和候选化合物的虚拟筛选的计算方法变得更加重要。在这篇综述中,调查了在药物开发背景下广泛使用的几个公共领域软件包的最新进展,包括 DOCK、AutoDock、AutoDock Vina 和通过诱导契合对接有效筛选配体(SLIDE)。作者还调查了对接模拟分析和可视化的方法,这是整体评估结果的重要步骤。为了说明当前对接程序的性能和局限性,作者使用了国家毒理学研究中心(NCTR)的 232 种具有实验测量的与雌激素受体α结合强度的雌激素化合物的雌激素受体基准集。这里测试的方法在该基准测试的活性化合物的预测和观察结合亲和力之间产生了高达 0.6 的相关系数。