Ligand and structure-based computational designing of multi-target molecules directing FFAR-1, FFAR-4 and PPAR-G as modulators of insulin receptor activity.

Multi-agent therapies are an important treatment modality in many diseases based on the assumption that combining agents may result in increased therapeutic benefit by overcoming the mechanism of resistance and providing superior efficiency. Extensively validated 3D pharmacophore models for free fatty acid receptor-1 (FFAR-1), free fatty acid receptor-4 (FFAR-4), and peroxisome proliferator-activated receptor-G (PPAR-G) was developed. The pharmacophore model for FFAR-1 ( = 0.98, = 0.90) and PPAR-G ( = 0.89, = 0.88) suggested that one hydrogen bond acceptor, one hydrogen bond donor, three aromatic rings, and two hydrophobic groups arranged in 3D space are essential for the binding affinity of FFAR-1 and PPAR-G inhibitors. Similarly, the pharmacophore model for FFAR-4 ( = 0.92, = 0.87) suggested that the presence of a hydrogen bond acceptor, one negative atom, two aromatic rings, and three hydrophobic groups plays a vital role in the binding of an inhibitor of FFAR-4. These pharmacophore models allowed searches for novel FFAR-1, PPAR-G, and FFAR-4 triple inhibitors from multi-conformer 3D databases (Asinex). Finally, the twenty-five best hits were selected for molecular docking, to study the interaction of their complexes with all the proteins and final binding orientations of these molecules. After molecular docking, ten hits have been predicted to possess good binding affinity as per the Molecular Mechanics Generalized Born Surface Area (MM-GBSA) calculation for FFAR-1, FFAR-4, and PPAR-G which can be further investigated for its experimental / anti-diabetic activities.Communicated by Ramaswamy H. Sarma.