Protein kinase C inhibitors have been rendered as attractive targets for therapeutic agents. Recent studies have been shown that PKC epsilon isozyme is a valid new therapeutic target for treating alcoholism, anxiety and pain related to inflammation and alcoholic polyneuropathy. However, there is no selective inhibitor of PKC epsilon that can be administered systematically and cross the blood-brain barrier. Recently, we have been developing new algorithms and technology platform of computational modeling, optimization and virtual screen to parallel select novel small molecule drug leads with balanced potency and ADMET (absorption, distribution, metabolism, excretion, toxicity) properties. We have performed preliminary studies both in modeling of known inhibitors of PKC isozymes as well as in experimental in-vitro screening. The key pharmacophoric and structural features and their differences, for example, between inhibitions of PKC epsilon and beta2 isozymes have been successfully identified. The convergence of in-vitro and in-silcio (computer-based) studies will allow us to not only better understand the structural and pharmacophoric requirements for discover novel, potent, selective PKC epsilon inhibitors, but also to optimize and select them with balanced ADMET properties in a shorter time and less resources. Our proposed research project will involve further studies to improve and fine-tune these technologies and in-vitro/in-silico iterative processes and explore the utility of them in discovering new, selective, oral- and brain-active PKC epsilon inhibitors for treatment of alcoholism, anxiety and pain.
Thesaurus Terms: alcoholism antagonist, analgesic, chemical structure function, computational biology, drug design /synthesis /production, isozyme, neuropharmacology, protein kinase C, protein kinase inhibitor alcoholism /alcohol abuse, chemical registry /resource, mathematical model, tranquilizer fluorescence polarization, protein purification