Executive Summary : | Epigenetics has important role in different cellular processes. It happens through the post-translational modulation in different proteins. This process creates the change of gene function without changing the sequences of the gene. Several processes including histone acetylation & deacetylation, DNA methylation, etc. can be grouped into the epigenetic modifications. Histone deacetylases (HDACs) together with histone acetyltransferase (HAT) are important in controlling the acetylation/deacetylation of lysine amino acids on histone/non-histone proteins. The HDAC enzymes constitute a large portion of total epigenetic targets (23%) after methyltransferases. In many human diseases there is a direct correlation with the abnormal expression of various HDACs, especially in cancer and neurodegenerative diseases, which makes them important therapeutic targets for these diseases. The majorities of all existing HDACs inhibitors as drugs are nonselective nature and are called as pan HDAC inhibitors (e.g. SAHA and TSA). Thus, it is essential to develop a selective HDAC inhibitor in order to address a particular disease more efficiently with reduced side effects. The isoform selective HDAC inhibitor would offer more meaningful chemotherapy with better therapeutic advantage than existing pan HDAC inhibitors. However, the design of selective HDAC inhibitor is challenging due to the fact that different isoforms of HDACs have high sequence similarity in their active sites. Moreover, the limited ligand bound crystal structures of HDACs makes it more difficult to design a particular ligand which can selectively inhibit an isoform of HDAC. Therefore, different ligand based modeling approach will be beneficial to address the selectivity of HDAC inhibitors. Quantitative structure-activity relationship (QSAR) and Quantitative activity-activity relationship (QAAR) approaches have shown its acceptability in many fields. QSAR mostly deals with the correlation of chemical descriptors with targeted biological end points. Different AI/ML techniques can be nicely used in QSAR/QAAR techniques. It reduces the development time and cost in the drug development process. Our group has already explored few derivatives with chemometric studies earlier in search of selective HDAC8 inhibitors. Now we want to address the selectivity of other HDAC isoform to help in the design of isoform selective HDAC inhibitors through the development of AI/ML based QSAR/QAAR models. The project will certainly benefit the drug discovery scientists to design selective HDAC inhibitor for the improved management of cancer and neurodegenerative diseases with reduced side effects. |