QSAR ANALYSIS OF HDAC6 INHIBITORS

OLEG V. TINKOV, VENIAMIN YU. GRIGOREV, LYUDMILA D. GRIGOREVA
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Abstract

Histone deacetylase inhibitors are the most important class of drugs for the treatment of oncologies and other diseases due to their effect on cell growth, differentiation and apoptosis. Among the known eighteen histone deacetylases, Histone deacetylase 6 (HDAC6), which is involved in oncogenesis, cell survival, and cancer cell metastasis, is of high importance. Using 2D molecular descriptors RDKit, simplex descriptors, as well as methods of Random Forest (RF), Gradient Boosting (GBM), Support vectors (SVM), a number of adequate classi cation models of Quantitative Structure-Activity Relationship (QSAR) are proposed. For the models constructed using simplex descriptors, a structural interpretation was carried out, which made it possible to describe molecular fragments that increase and decrease the activity of HDAC6 inhibitors. The results of the structural interpretation were used for the rational molecular design of potential HDAC6 inhibitors, for which ADMET properties were also evaluated. Models built using 2D RDKit descriptors are freely available on the github platform (https://github.com/ovttiras/HDAC6-inhibitors).
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hdac6抑制剂的Qsar分析
组蛋白去乙酰化酶抑制剂因其对细胞生长、分化和凋亡的影响而成为治疗肿瘤和其他疾病的最重要的一类药物。在已知的18种组蛋白去乙酰化酶中,组蛋白去乙酰化酶6 (histone deacetylase 6, HDAC6)在肿瘤发生、细胞存活和癌细胞转移过程中发挥着重要作用。利用二维分子描述符RDKit、单纯形描述符,以及随机森林(RF)、梯度增强(GBM)、支持向量机(SVM)等方法,提出了一系列合适的定量构效关系(QSAR)分类模型。对于使用单纯形描述符构建的模型,进行了结构解释,这使得描述增加和降低HDAC6抑制剂活性的分子片段成为可能。结构解释的结果用于合理的分子设计潜在的HDAC6抑制剂,并对其ADMET性质进行了评估。使用2D RDKit描述符构建的模型可以在github平台上免费获得(https://github.com/ovttiras/HDAC6-inhibitors)。
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