QSAR Analysis of HDAC6 Inhibitors

Abstract

Histone deacetylase inhibitors are the most important class of drugs for the treatment of oncology and other diseases due to their effect on cell growth, differentiation, and apoptosis. Among the known 18 histone deacetylases, histone deacetylase 6 (HDAC6) that is involved in oncogenesis, cell survival, and cancer cell metastasis is most important. A number of adequate classification models of the quantitative structure–activity relationship (QSAR) are proposed using 2D RDKit molecular descriptors and simplex descriptors, as well as methods of random forest (RF), gradient boosting (GBM), and support vectors (SVM). A structural interpretation is carried out for the models constructed using simplex descriptors which makes it possible to describe the molecular fragments that increase and decrease the activity of HDAC6 inhibitors. The results of the structural interpretation are used for the rational molecular design of potential HDAC6 inhibitors, for which the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties are also evaluated. The models constructed using 2D RDKit descriptors are free to access on the GitHub platform at the following URL: https://github.com/ovttiras/HDAC6-inhibitors.