DFT based Computational Methodology of IC50 Prediction
Arijit Bag · Current Computer - Aided Drug Design · 2020
Background: IC 50 is one of the most important parameters of a drug. But, it is very difficult to predict this value of a new compound without experiment. There are only a few QSAR based methods available for IC 50 prediction, which is also highly dependable on a huge number of known data. Thus, there is an immense demand for a sophisticated computational method of IC 50 prediction in the field of in silico drug designing. Objective: Recently developed quantum computation based method of IC 50 prediction by Bag and Ghorai requires an affordable known data. In present research work, further development of this method is carried out such that the requisite number of known data being minimal. Methods: To retrench the cardinal data span and shrink the effects of variant biological parameters on the computed value of IC 50 , a relative approach of IC 50 computation is pursued in the present method. To predict an approximate value of IC 50 of a small molecule, only the IC 50 of a similar kind of molecule is required for this method. Results: The present method of IC 50 computation is tested for both organic and organometallic compounds as HIV-1 capsid A inhibitor and cancer drugs. Computed results match very well with the experiment. Conclusion: This method is easily applicable to both organic and organometallic compounds with acceptable accuracy. Since this method requires only the dipole moments of an unknown compound and the reference compound, IC 50 based drug search is possible with this method. An algorithm is proposed here for IC 50 based drug search.