In silico Analysis of 3D-QSAR and Molecular Docking for Bcl-2 Inhibitors to Potential Anticancer Drug Development

Apoptosis control is characterized by a delicate balance between homo and hetero dimerization of pro- and anti-apoptosis members of the protein family. Inhibiting this protein protein interaction is one viable approach to cancer therapy. Anti-apoptosis the prosurvival family members Bcl-2, Mcl-1, and Bcl-XL are current targets for anti-cancer drug design. The chemotherapy has aroused many researchers’ interests and a great deal of current efforts has been focusing on the design and development of various anticancer drugs. Ligand-based drug designing methods approaches through pharmacophore mapping and Three Dimention- Quantitative Structure Activity Relationship (3D-QSAR) are used in drug discovery as well as molecular docking to seek potential binding sites of the Bcl-2 protein and its inhibitors interactions. Dynamically predictive 3D-QSAR model with Pearson-r value (0.74), F (62.5), Standard Deviation (0.285) of the regression and Root Mean Square Deviation RMSE (0.321), Q2(0.514) that was obtained for binding affinity of Bcl-2 protein respectively. The bioinformatics techniques were proved that the development of good potential activity drug compound to cancer. To our knowledge the results describes anti-tumour activity of HEQ-1 drug compound promising to convey anti-tumour drug development.