Structural Models for the Design of PKMzeta Inhibitors with Neurobiological Indications

Abstract

An atypical protein kinase C, PKMzeta has become an attractive target for various neurological disorders including long term potentiation, cognition, neuropathic pain and cancer. Drug discovery efforts have been hindered due to the non-availability of the protein structure and hence in the present study we attempted to build the open and closed models of the protein PKMzeta using homology modeling. The models were then used to identify PKMzeta inhibitors utilizing a high-throughput virtual screening protocol from a large commercial chemical database. Compounds were selected based on the binding interactions and Glide score. Compounds were then subjected to in vitro luminescent based kinase assay for their inhibitory activity on targeted protein. Seven compounds exhibited IC50 s less than or equal to 10 µM. Cell based assays revealed that Lead C3 and Lead C6 exhibited selectivity towards methylmercury treated neuroblastoma growth inhibition and suppressed reactive oxygen species with IC50 s of 0.89 and 0.17 µM, respectively. Furthermore, Lead C3 exhibited attenuation of proinflammatory response with least energy in dynamic simulation studies and thus emerged as a prototypical lead for further development as novel inhibitor of PKMzeta for neurological implications.

Keywords: Cell-cycle analysis; Docking; High-throughput virtual screening; Homology modeling; Molecular dynamics; PKMzeta inhibitors; Proinflammatory response.