Explicit Drug Re-positioning: Predicting Novel Drug-Target Interactions of the Shelved Molecules with QM/MM Based...

With the demand to enhance the speed of the drug discovery process there has been an increased usage of computational approaches in drug discovery studies. However because of their probabilistic outcomes, the challenge is to exactly mimic the natural environment which can provide the exact charge polarization effect while estimating the binding energy between protein and ligand. There has been a large number of scoring functions from simple one to the complex one available for estimating binding energy. The quantum mechanics/molecular mechanics (QM/MM) hybrid approach has been the preferred choice of interest since last decade for modeling reactions in biomolecular systems. The application of QM/MM approach has been expanded right from rescoring the already known complexes and depicting the correct position of some novel molecule to ranking a large number of molecules. It is expected that the application of QM/MM-based scoring will grow in all areas of drug discovery. However, the most promising area will be its application in repositioning, that is, assigning novel functions or targets to the already existing drugs, as this would stop the rising attrition rates as well as reduce the overall time and cost of drug discovery procedure.