Rapid and Reliable Binding Affinity Prediction of Bromodomain Inhibitors: A Computational Study

详细信息    查看全文

• 作者：Shunzhou Wan ; Agastya P. Bhati ; Stefan J. Zasada ; Ian Wall ; Darren Green ; Paul Bamborough ; Peter V. Coveney
• 刊名：Journal of Chemical Theory and Computation
• 出版年：2017
• 出版时间：February 14, 2017
• 年：2017
• 卷：13
• 期：2
• 页码：784-795
• 全文大小：676K
• ISSN：1549-9626

文摘

Binding free energies of bromodomain inhibitors are calculated with recently formulated approaches, namely ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration with enhanced sampling). A set of compounds is provided by GlaxoSmithKline, which represents a range of chemical functionality and binding affinities. The predicted binding free energies exhibit a good Spearman correlation of 0.78 with the experimental data from the 3-trajectory ESMACS, and an excellent correlation of 0.92 from the TIES approach where applicable. Given access to suitable high end computing resources and a high degree of automation, we can compute individual binding affinities in a few hours with precisions no greater than 0.2 kcal/mol for TIES, and no larger than 0.34 and 1.71 kcal/mol for the 1- and 3-trajectory ESMACS approaches.