Identification of specific features of inhibition of PKCβII and its potential lead by shape-based virtual screening and molecular docking studies
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Updated: May 21, 2026

A Bilingual Computational Workflow for Identifying Potential PLK1 Inhibitors in American Sign Language and English
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Baljinder K Grewal1, M Elizabeth Sobhia
1Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research (NIPER), Sector 67, S.A.S. Nagar, Punjab 160062, India.
Abstract:
Protein kinase C βII (PKCβII) is preferentially expressed during hyperglycemic state resulting in diabetic complications, particularly, diabetic cardiomyopathy. An effective inhibition of PKCβII is a potential option to directly treat the diabetic cardiomyopathy; however, till date no efficient drug targeting PKCβII is available and all the reported PKCβII ligands are maleimide derivatives. The purpose of the present work is to study the importance of the maleimide moiety in PKCβII inhibition and the effects that follow after replacing the maleimide with similar moiety on PKCβII inhibition. For this, an in-house database of maleimide analogues was prepared and shape based screening of commercial databases viz. Specs2009, NCI2003 was performed, followed by filtration using virtual filters. The binding features of reported PKCβII inhibitors, and high scoring hits were analyzed with the help of molecular docking studies. The features identified from the above studies were used for the rational design of new PKCβII inhibitors. The molecular dynamics simulation and ligand-receptor binding affinity studies of the designed molecules has been reported. The toxicity of all the shortlisted and designed molecules was predicted.
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