Computational Studies in Drug Design Against Cancer

Abstract

Background: The application of in silico tools in the development of anti cancer drugs.

Objective: The summing of different computer aided drug design approaches that have been applied in the development of anti cancer drugs.

Methods: Structure based, ligand based, hybrid protein-ligand pharmacophore methods, Homology modeling, molecular docking aids in different steps of drug discovery pipeline with considerable saving in time and expenditure. In silico tools also find applications in the domain of cancer drug development.

Results: Structure-based pharmacophore modeling aided in the identification of PUMA inhibitors, structure based approach with high throughput screening for the development of Bcl-2 inhibitors, to derive the most relevant protein-protein interactions, anti mitotic agents; I-Kappa-B Kinase β (IKK- β) inhibitor, screening of new class of aromatase inhibitors that can be important targets in cancer therapy.

Conclusion: Application of computational methods in the design of anti cancer drugs was found to be effective.

Keywords: Anticancer; PUMA inhibitors; aromatase inhibitors; computational; molecular docking; pharmacophore modeling..