Comparative Modeling of CDK9 Inhibitors to Explore Selectivity and Structure-Activity Relationships

作者: Palani Kirubakaran , George Morton , Pingfeng Zhang , Hanghang Zhang , John Gordon

DOI: 10.1101/2020.06.08.138602

关键词: Computational biologyProtein Data Bank (RCSB PDB)Cyclin-dependent kinaseCyclin-dependent kinase 9Structure (mathematical logic)SelectivityProtein Data BankTranscription elongationEpigenetic silencingComputer science

摘要: Cyclin-dependent kinase 9 (CDK9) plays a key role in transcription elongation, and more recently it was also identified as the molecular target of series diaminothiazole compounds that reverse epigenetic silencing phenotypic assay. To better understand structural basis underlying these compounds9 activity selectivity, we developed comparative modeling approach describe herein. Briefly, this draws upon strong conservation across active conformation all protein kinases, their shared pattern interactions with Type I inhibitors. Because this, hypothesized large collection inhibitor/kinase structures available Protein Data Bank (PDB) would enable accurate complex each CDK family member. We apply new pipeline to build models, then demonstrate models provide retrospective rationale for structure-activity relationships ultimately guided optimization lead compound MC180295 (14e). solved crystal structure 14e/CDK9 complex, found resulting be excellent agreement our corresponding model. Finally, inspired by how changes 14e can used rationally tune compound9s selectivity profile. With emergence CDK9 promising therapeutic intervention cancer, anticipate valuable tool guide potency inhibitors targeting kinase.

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