Wang Huiwen, Guan Zeyu, Qiu Jiadi, Jia Ya, Zeng Chen, Zhao Yunjie
Department of Physics, Institute of Biophysics, Central China Normal University Wuhan 430079 China
Department of Physics, The George Washington University Washington DC 20052 USA.
RSC Adv. 2020 Jan 10;10(4):2004-2015. doi: 10.1039/c9ra07471f. eCollection 2020 Jan 8.
Kinase proteins have been intensively investigated as drug targets for decades because of their crucial involvement in many biological pathways. Most kinase drugs target the catalytic ATP pocket, which is highly conserved across the kinome, and as such often leads to potential side effects. It is thus highly desirable to develop non-ATP-competitive drugs that inhibit kinase activity allosteric interactions. However, to elucidate the complex allosteric mechanism, it is essential to build a novel method to characterize a comprehensive non-catalytic pocket for the structurally well-covered human kinome. In this work, we developed a hybrid approach of sequence, structure and network analysis on 168 representative kinases to identify group-specific non-catalytic pockets. The geometric analysis was performed to cluster these pockets and to identify group-specific non-catalytic pockets based on their shape and location characteristics. Subsequent sequence evolutionary analysis reveals the crucial residues of each pocket that will likely interact with inhibitors binding to the pocket. These residues thus serve as potential biomarkers of each pocket for inhibitor design. Moreover, the residue-residue interaction network analysis was performed to elucidate the complex allosteric mechanism of these non-catalytic pockets. The final list of 14 group-specific non-catalytic pockets and their characterized structural, sequence and network features can be an enabling dataset for drug design effort at the human kinome level. The developed hybrid approach is able to identify group-specific non-catalytic pockets and will benefit the research related to human kinome drug design.
几十年来，激酶蛋白一直作为药物靶点受到深入研究，因为它们在许多生物途径中起着关键作用。大多数激酶药物靶向催化性ATP口袋，该口袋在整个激酶组中高度保守，因此常常会导致潜在的副作用。因此，非常需要开发非ATP竞争性药物，通过变构相互作用抑制激酶活性。然而，为了阐明复杂的变构机制，必须建立一种新方法来表征结构上研究充分的人类激酶组的综合非催化口袋。在这项工作中，我们对168种代表性激酶开发了一种序列、结构和网络分析的混合方法，以识别特定组的非催化口袋。进行几何分析以对这些口袋进行聚类，并根据它们的形状和位置特征识别特定组的非催化口袋。随后的序列进化分析揭示了每个口袋中可能与结合到口袋的抑制剂相互作用的关键残基。因此，这些残基可作为每个口袋用于抑制剂设计的潜在生物标志物。此外，进行残基-残基相互作用网络分析以阐明这些非催化口袋的复杂变构机制。14个特定组非催化口袋的最终列表及其表征的结构、序列和网络特征可以成为人类激酶组水平药物设计工作的一个可行数据集。所开发的混合方法能够识别特定组的非催化口袋，并将有益于与人类激酶组药物设计相关的研究。
