Protein Kinase C βII (PKCβII) overexpression has been linked to various diabetic microvascular complications
viz. retinopathy, neuropathy, and cardiomyopathy. Novel and potent small molecules with preferential selective inhibitory
property of PKCβII will be helpful in treatment as well as understanding insight of PKCβII involvement in these
complications. Robust 3D hypotheses were developed using both the crystal structure and available PKCβII ligands, and
were validated by feature mapping and screening in-house database of reported PKCβII compounds. The best hypothesis
from both methods consists of six features viz. one hydrogen bond donor (D), two hydrogen bond acceptors (A1, A2), two
hydrophobic-aromatics (H1, H2) and one ring aromatic (R). A synergistic approach of virtual screening using both ligand
and receptor based pharmacophore model was used for the flexible search of ligands from chemical databases. The hits
obtained were screened by molecular docking and their binding affinity was predicted using MMPBSA calculations. The
first receptor based query of PKCβII and new scaffold of its inhibitors with good estimated activities, favorable binding
interactions, and high docking score were identified.
Keywords: Molecular docking, molecular dynamics, pharmacophore modeling, PKCβII inhibitors, scaffold, virtual screening.
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