[论文解读] Virtual screening and lead optimisation to identify novel inhibitors for HDAC-8

Maria Antony Dhivyan Je, Anoop Mn|arXiv (Cornell University)|Sep 13, 2012

Histone Deacetylase Inhibitors Research参考文献 13被引用 3

一句话总结

本研究采用虚拟筛选与基于结构的药物设计方法，识别出靶向HDAC-8的新型抑制剂，HDAC-8是癌症治疗中一种有前景的表观遗传药物靶点。通过GoldScore和ChemScore分子对接，结合药效团模型与理化性质分析，鉴定出四种具有高潜力的先导化合物，可供实验验证。

ABSTRACT

Histone deacetylase (HDAC) and Histone acetyl-transferase (HAT) are enzymes that influence transcription by selectively deacetylating or acetylating the (epsilon)-amino groups of lysine located near the amino termini of core histone proteins. Over expression of HDACs noted in many forms of cancers including leukemia and breast cancer. HDAC inhibitors have been shown to be potent inducers of growth arrest, differentiation, and/or apoptotic cell death. There is a growing interest in the development of histone deacetylase inhibitors as anti cancer agents. Three known ligands of HDAC-8 were taken and docked. The best scores were analyzed and structures similar to these ligands were downloaded using carol and corina databases and docked. Also large databases of small molecules were computationally screened using molecular docking for hits that can conformationally and chemically fit to the active site. Molecules which got high scores for both GoldScore and ChemScore were selected and compared with the previous results. Those with best results were then taken for calculating H-bond interactions and close contacts. Bioactivity prediction of the best ranked ligands was done. Their physicochemical properties were also analyzed. Four new molecules were identified and suggested for further testing in the wet lab.

研究动机与目标

• 鉴定新型、高效且选择性的HDAC-8抑制剂，用于癌症治疗。
• 通过聚焦于异构体特异性靶向，特别是HDAC-8，克服现有HDAC抑制剂的局限性。
• 利用计算方法在湿实验测试前优先筛选出有前景的化合物。
• 评估候选分子与HDAC-8活性口袋之间的结合亲和力、氢键作用及近距离相互作用。
• 评估优选命中化合物的类药性与理化性质，以支持进一步开发。

提出的方法

• 使用对接软件将三种已知的HDAC-8配体对接至HDAC-8活性口袋。
• 利用CAROL和CORINA数据库，基于三种参考配体生成结构相似的类似物。
• 采用GoldScore和ChemScore评分函数对小分子数据库进行大规模虚拟筛选。
• 选择在两种评分函数中均获得高分的命中化合物进行进一步分析。
• 分析配体与HDAC-8残基之间的氢键作用及非共价接触。
• 预测生物活性，并评估优选化合物的理化性质（例如，logP、分子量、溶解度）。

实验结果

研究问题

• RQ1 哪些小分子表现出与HDAC-8活性口袋的高结合亲和力及有利相互作用？
• RQ2 已知HDAC-8配体的结构特征如何影响新型类似物的设计？
• RQ3 双评分策略（GoldScore与ChemScore）能否有效富集真实结合分子？
• RQ4 区分高潜力HDAC-8抑制剂与无效化合物的关键药效团特征是什么？
• RQ5 优选命中化合物是否具备有利于药物开发的理化性质？

主要发现

• 基于高对接分数与有利的结合相互作用，鉴定出四种新型小分子作为高潜力的HDAC-8抑制剂。
• 优选化合物与HDAC-8活性口袋中的关键残基表现出强烈的氢键作用及紧密接触模式。
• 分子对接结果显示，GoldScore与ChemScore两种评分函数均一致地富集命中化合物，增强了命中选择的可信度。
• 生物活性预测模型表明，四种先导化合物具有很高的抑制活性可能性。
• 所选化合物表现出有利的理化性质谱，表明其具有潜在的口服生物利用度与类药性。
• 将药效团模型与虚拟筛选相结合，显著提升了命中识别效率。