3 research outputs found
QSAR analysis of coumarin-based benzamides as histone deacetylase inhibitors using CoMFA, CoMSIA and HQSAR methods
Histone deacetylases (HDACs) as the promising therapeutic targets for the treatment of cancer and other
diseases, modify chromatin structure and contribute to aberrant gene expression in cancer. Inhibition of
HDACs is emerging as an important strategy in human cancer therapy and HDAC inhibitors (HDACIs)
enable histone to maintain a high degree of acetylation. In this work, molecular modeling studies,
including CoMFA, CoMFA-RF, CoMSIA and HQSAR and molecular docking were performed on a series of
coumarin-based benzamides as HDAC inhibitors. The statistical qualities of generated models were
justified by internal and external validation, i.e., cross-validated correlation coefficient (q2), non-crossvalidated
correlation coefficient (r2
ncv) and predicted correlation coefficient (r2
pred), respectively. The
CoMFA (q2, 0.728; r2
ncv, 0.982; r2
pred; 0.685), CoMFA-RF (q2, 0.764; r2
ncv, 0.960; r2
pred; 0.552), CoMSIA (q2,
0.671; r2
ncv, 0.977; r2
pred; 0.721) and HQSAR models (q2, 0.811; r2
ncv, 0.986; r2
pred; 0.613) for training and test
set of HDAC inhibition of HCT116 cell line yielded significant statistical results. Therefore, these QSAR
models were excellent, robust and had better predictive capability. Contour maps of the QSAR models
were generated and validated by molecular docking study. The final QSAR models could be useful for the
design and development of novel potent HDAC inhibitors in cancer treatment. The amido and amine
groups of benzamide part as scaffold and the bulk groups as a hydrophobic part were key factors to
improve inhibitory activity of HDACIs