Multiple target-based pharmacophore design from active site structures^$

Health care systems have benefitted from rational drug discovery processes like vHTS, virtual high throughput screening pharmacophores and quantitative structure–activity relationships, and many challenges have been explored using such techniques: decisions on specificity and selectivity are made after screening millions of molecules for multiple targets. Recent challenges in drug research emphasize the design of drugs that bind with more than one target of interest (multi-target) and do not bind with undesirable targets. This work attempts to use a three-dimensional interaction profile of the active site of a class of proteins, identify selective positions for the binding of functional groups, called features, and develop ensembles of multi-targeted pharmacophores that retain specificity and selectivity. The goal of this study is to develop multi-target pharmacophores by computational methods using protein structures alone to guide the discovery of novel inhibitors of plasmepsins, displaying selectivity over their human homologs, cathepsin D and pepsin. The development of such novel tools is attempted using a combination of different approaches such as the molecular interaction field, clique graph and inductive logic programming to identify and compare specific and selective complementary features. The identification of selective combinations of features has resulted in the design of multi-featured specific and selective pharmacophores that are validated using antimalarial compounds in ChEMBL that are known for their anti-plasmepsin II activity. This novel method is computationally less intensive and is applicable to any known class of target structures for finding specific and selective binders simultaneously.