Background: IC50 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 IC50 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 IC50
prediction in the field of in silico drug designing.
Objective: Recently developed quantum computation based method of IC50 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 IC50, a relative approach of IC50 computation is pursued in the present
method. To predict an approximate value of IC50 of a small molecule, only the IC50 of a similar kind
of molecule is required for this method.
Results: The present method of IC50 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
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, IC50 based drug search is possible with this method. An algorithm is
proposed here for IC50 based drug search.