基于化学信息学的新型HDAC3亚型选择性抑制剂的发现及抗糖尿病活性评价

Histone Deacetylases (HDACs) are a class of important proteins for posttranslational deacetylation in mammals, which play a pivotal role in the regulation of gene transcription. Growing evidence indicates that HDAC3-selective inhibition protects pancreatic β-cells and increases insulin secretion, while pan-HDAC inhibition may result in toxicity to β-cells. Our group has been working on the design of novel HDACs inhibitors (HDACIs) for HDACs-related diseases and discovered a series of HDACIs. Recently, we not only identified critical structural differences among HDACs though structural alignment and molecular docking, but also developed Maximal Unbiased Benchmarking Datasets for HDACs (MUBD-HDACs) for better assessment of ligand enrichment in high-throughput virtual screening (HTVS). In this study, we will apply computer-aided drug design to identify highly potent and selective HDAC3 inhibitors for the treatment of diabetes. To be specific, both HDAC3/SMRT interface and the catalytic site of HDAC3 will become targets for drug design. We will evaluate a multitude of HTVS strategies for ligand enrichment and develop QSAR models for selectivity prediction. Then the high-enrichment strategy and robust QSAR models will be used to screen against commercial chemical libraries and in-house focused library. The promising hits will be purchased or synthesized and tested for their HDAC1/2/3/8 inhibition and anti-diabetic effects. This study may bring about lead compounds for developing a new generation of anti-diabetic drugs as well as high-quality probes specifically for studying HDAC3 and diabetes.

HDACs（组蛋白去乙酰化酶）是哺乳动物蛋白翻译后去乙酰化修饰的重要蛋白，在基因转录调控中起着关键作用。研究表明，选择性抑制HDAC3可以保护胰岛β细胞和促进胰岛素分泌，而非选择性的HDACs抑制可能产生细胞毒性。课题组前期已积累了一系列HDACs抑制剂，获得了HDACs各亚型的结构差异信息，并且通过开展HDACs评价数据集的研究优化了虚拟筛选技术。在此基础上，本项目拟分别针对HDAC3/SMRT交界面和HDAC3传统催化位点开展计算机辅助药物设计，旨在发现具有明确抗糖尿病活性、骨架新颖的HDAC3亚型选择性抑制剂。内容将涉及评价和优选最佳虚拟筛选方案、建立选择性预测方法，建立聚焦型化合物库，合成及购买目标化合物，进行HDAC1/2/3/8的酶抑制活性测试和初步的糖尿病药效学评价。本课题将为研发低毒高效的糖尿病治疗创新药物提供先导结构，同时为研究HDAC3与糖尿病的关系提供有效的工具分子。

本项目提出通过化学信息学方法发现HDAC3靶向胰岛β细胞保护剂作为潜在的抗糖尿病药物。为此，我们分别针对HDAC3/SMRT交界面和HDAC3催化位点开展了虚拟筛选，发现了两种不同类型的苗头化合物XJ0253和HHB24。在HHB24的基础上，课题组开展了基于结构的药物设计、药物合成与生物活性评价，进一步发现衍生物HBS53具有胰岛β细胞保护作用。该研究为糖尿病治疗提供了一种全新作用机制的先导化合物。同时，我们致力于化学信息学新方法发展，在本研究中我们推出了升级版的最大无偏好性基准数据集计算程序MUBD-DecoyMaker2.0以及新发展了基于多复合物晶体结构的自动化药效构象识别工具PFEBuilder。上述工具有助于提高计算机辅助药物发现的成功率。