A successful drug candidate will not only need to overcome ADME, physical and safety properties, but also often need to achieve a selectivity profile against related targets.The approach we present here combines a de novo design method with powerful ligand-based scoring function that consists of three different 3D QSAR models for different targets to generate selective inhibitors.A training set was developed with literature and public information where 50 molecules with activities for FactorXa, Trypsin and Thrombin were selected. Three different Topomer CoMFA models were built using the training set. By combining predictions of the activity profile with different weights and penalty score, a scoring function was created that can drive the invention of new and selective compounds. 

Multicriteria drug discovery: Using CoMFA models to drive target specificity

248th National Meeting (2014)

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