Prediction of the binding affinity of compounds with diverse scaffolds by MP-CAFEE

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• 作者：Okimasa Okada ; Hiroshi Yamashita ; Kei Takedomi ; Satoshi Ono ; Shinji Sunada ; Hideo Kubodera
• 关键词：MP-CAFEE ; massively parallel computation of absolute binding free energy with a well-equilibrated system
• 刊名：Biophysical Chemistry
• 出版年：2013
• 出版时间：October-November, 2013
• 年：2013
• 卷：180-181
• 期：Complete
• 页码：119-126
• 全文大小：587 K

文摘

Accurate methods to predict the binding affinities of compounds for target molecules are powerful tools in structure-based drug design (SBDD). A recently developed method called massively parallel computation of absolute binding free energy with a well-equilibrated system (MP-CAFEE) successfully predicted the binding affinities of compounds with relatively similar scaffolds. We investigate the applicability of MP-CAFEE for predicting the affinity of compounds having more diverse scaffolds for the target p38¦Á, a mitogen-activated protein kinase. The calculated and experimental binding affinities correlate well, showing that MP-CAFEE can accurately rank the compounds with diverse scaffolds. We propose a method to determine the optimal number of sampling runs with respect to a predefined level of accuracy, which is established according to the stage in the SBDD process being considered. The optimal number of sampling runs for two key stages¡ªlead identification and lead optimization¡ªis estimated to be five and eight or more, respectively, in our model system using Cochrans sample size formula.