Active site fingerprinting and pharmacophore screening strategies for the identification of dual inhibitors of protein kinase C (PKC β) and poly (ADP-ribose) polymerase-1 (PARP-1)

Current clinical studies have revealed that diabetic complications are multifactorial disorders that target two or more pathways. The majority of drugs in clinical trial target aldose reductase and protein kinase C (PKC β), while recent studies disclosed a significant role played by poly (ADP-ribose) polymerase-1 (PARP-1). In light of this, the current study was aimed to identify novel dual inhibitors of PKC β and PARP-1 using a pharmaco-informatics methodology. Pharmacophore-based 3D QSAR models for these two targets were generated using HypoGen and used to screen three commercially available chemical databases to identify dual inhibitors of PKC β and PARP-1. Overall, 18 hits were obtained from the screening process; the hits were filtered based on their drug-like properties and predicted binding affinities (docking analysis). Important amino acid residues were predicted by developing a fingerprint of the active site using alanine-scanning mutagenesis and molecular dynamics. The stability of the complexes (18 hits with both proteins) and their final binding orientations were investigated using molecular dynamics simulations. Thus, novel hits have been predicted to have good binding affinities for PKC β and PARP-1 proteins, which could be further investigated for in vitro/in vivo activity.