基于片段组合方法的新型蛋白激酶CK2抑制剂设计、合成及抗癌活性研究

CK2 has been considered as a valuable drug target of cancer therapy. However, most of its ATP competitive inhibitors recognize a part of sub-sites in the ATP-binding pocket (named the sectional recognition mechanism), and have the low selectivity and high side-effect defects, and the compounds targeting all sub-sites of the binding pocket (named the holistic recognition mechanism) are ideal CK2 inhibitors. Up to date, although the high-throughput screening has produced few inhibitors with the holistic recognition mechanism, this traditional method has the shortcomings of lower hit rate and blindness for hit or lead discovery. Consequently, design of the rational screening strategy with higher successes rates is very crucial for the ideal CK2 inhibitors development. In the previous study, we have firstly elucidated the diverse recognition mechanisms of different type inhibitors with binding pocket, and built the pharmacophoric groups library. By assembling and optimizing pharmacophoric functional groups into courmarin scaffold, we also identify a series of novel potent CK2 inhibitors, which form the holistic recognition mechanism with the binding pocket. Here, this project aims to further design new CK2 inhibitors with the holistic recognition mechanism by pharmacophoric fragment-based assembling strategies into the bio-active scaffold, improve their original sectional recognition mechanisms，evaluate their biological inhibitory activity at both molecular and cellular levels, unveil the mechanism of them with CK2 binding pocket, and finally discovery the novel lead compounds with high anti-cancer activity and good drug-likeness. This study will provide the theoretical basis and guidance for the development of anti-cancer drugs by targeting CK2.

蛋白激酶CK2是重要的抗癌药物研发靶点。但其多数抑制剂与ATP结合口袋部分亚位点形成局部性识别机制，且存在选择性低及毒副作用大等缺陷，设计靶向整体性识别结合口袋所有亚位点的化合物成为CK2抑制剂研究的目标。目前形成整体性识别机制的抑制剂是通过具有盲目性且命中率低的高通量筛选而获得，因此，设计合理且成功率高的化合物筛选策略是该类抑制剂研发的关键。前期工作中，我们首次基于已有抑制剂与结合口袋的多样化识别机制构建了药效基团片段库，并针对香豆素骨架进行药效基团片段的组合优化，得到具有整体性识别机制的新型高活性CK2抑制剂。本课题拟在此基础上，进一步针对活性分子骨架开展基于药效基团片段和整体性识别机制的抑制剂设计，改进其原有的局部性识别机制，评价其在分子及细胞水平上的生物抑制活性，并阐明其与CK2的作用机制，以获得活性高且类药性优的抗癌先导化合物，为靶向CK2新型抗癌药物研发提供理论基础和指导依据。

蛋白激酶CK2因具有促细胞增长且抗细胞凋亡的特性而成为重要的抗癌靶标，因此，其新型抑制剂的设计与优化可为抗癌药物研发提供重要理论参考。本课题的研究成果主要体现在三个方面：第一、基于抑制剂多样化识别机制的药效碎片库构建。运用计算机辅助药物设计及分子模拟方法，率先阐述了CK2α抑制剂的多样化识别机制（局部性和整体性），揭示了关键药效基团羧酸及2,6-N杂萘环影响三环喹啉类抑制剂活性的结构机制。在此基础上，优化了兼顾化合物骨架多样性及靶标结构特征的药效碎片拆分策略，构建了靶向CK2活性口袋的关键药效碎片库。第二、新型直链骨架丙烯酮类CK2α抑制剂的靶向筛选、设计与活性评价。综合运用药效团模型、分子对接、类药性预测及生物活性评价等方法，针对天然产物数据库进行逐层虚拟筛选，筛选到CK2α抑制活性IC50为11.92µM的直链骨架丙烯酮类化合物CP6。并基于已构建的药效碎片库，采用整体性识别机制为导向的组合集中库设计策略，针对该苗头骨架进行进一步片段组合优化，获得了最优激酶抑制活性IC50为0.75µM的抗癌先导化合物。第三、靶向CK2α铰链区且具有整体性识别机制的氟代香豆素类化合物优化与活性评价。针对具有局部性识别机制（未与铰链区形成作用）的香豆素活性骨架，运用靶向铰链区的药效碎片筛选与生长设计策略，获得了新型氟代香豆素类抑制剂(抑制活性C50为0.4µM)，该化合物也对肺癌细胞表现出抗细胞增殖的能力。以上研究结果，可为靶向CK2新型抗癌药物的研发提供了重要的理论依据和指导思路。