Mathematical programming assisted drug design for nonclassical antifolates

A concept from optimization theory, specifically, mathematical programming, is proposed for designing drugs with desired properties. The mathematical programming formulation is solved to obtain the optimal descriptor values, which are employed in the Cerius(2) modeling environment to infer the optim al lead candidates, in the sense that they exhibit both high selectivity an d activity while ensuring low toxicity. It has been observed that unique su bstituent groups and their molecular conformations are responsible for atta ining the goal of simultaneous high selectivity and activity. Both linear a nd nonlinear quantitative structure activity relationships (QSARs) have bee n developed for use in the proposed approach. A comparative study of these models is done, and it is shown that the QSARs are well represented by nonl inear models. The proposed mathematical programming strategy has been demon strated for a class of nonclassical antifolates for Pneumocistis carinii an d Tooxplasma gondii dihydofolate reductase. Some of the potential leads fou nd in this study have biological properties similar to those in the open li terature. We believe the technique proposed is general and can be applied t o other structure based drug design.