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Identification of novel protein kinase C-βII inhibitors: virtual screening, molecular docking and molecular dynamics simulation studies.

Bharat Kumar Reddy SanapalliVidyasrilekha YeleLalji BaldaniyaVeera Venkata Satyanarayana Reddy Karri
Published in: Journal of molecular modeling (2022)
Diabetic wounds (DWs) are the major end-stage manifestation encountered in diabetic patients. The two major pathways involved in the pathogenesis of DW are impaired angiogenesis and unnecessary NETosis, which are regulated by a common enzyme called protein kinase C (PKC)-βII. PKC-βII is a conventional isoform of PKC family that can be activated by calcium and diacylglycerol. PKC-βII possesses a specific expression profile and plays a distinct role in various cellular and molecular functions. The pathogenic role of PKC-βII and its involvement in the impairment of wound healing suggested that PKC-βII plays a potential role in DW progression. Hence, there is a renewed interest in developing specific inhibitors of PKC-βII. In the present study, receptor-based virtual screening was performed for the identification of potential PKC-βII inhibitors using TimTec, Enamine, Zinc and Specs databases. A total of 595 candidate compounds were evaluated based on absorption, distribution, metabolism, excretion and toxicity, standard precision docking. Further, extra-precision docking and binding free energy calculations were carried out for top-ranked compounds. Based on Glide score and protein-ligand interactions, we have identified compound 1 as a potential inhibitor. Finally, molecular dynamics (MD) simulation was performed for top compound 1 using the Desmond module (Schrödinger suite) to identify the structural stability of the protein-ligand complex. Gratifyingly, MD trajectory analysis demonstrated the stable binding conformation of compound 1 with PKC-βII enzyme. In silico approaches incorporated in this study provide a set of new putative PKC-βII inhibitors which could be potential leads to develop DW therapeutics.
Keyphrases
  • molecular dynamics
  • protein kinase
  • molecular dynamics simulations
  • molecular docking
  • wound healing
  • type diabetes
  • risk assessment
  • oxidative stress
  • transcription factor
  • endothelial cells
  • big data
  • single molecule