In Silico Chemogenomics Knowledgebase and Computational System Neuropharmacology Approach for Cannabinoid Drug Research

Polypharmacological effect is a prevalent problem for abused substances and is a challenge for research on drug abuse (DA). In silico technologies have emerged as effective approaches to study the interactions between small molecules and their potential targets. We focus on the contemporary resources and computational tools for polypharmacology research on DA. Specifically, we review current in silico techniques for pharmacology profiling of chemical compound(s). As an illustration, we used our developed and implemented chemical genomics tools to explore polydrug addiction networks. Our established cannabinoid molecular information database (CBID or CBLigand), a chemogenomics platform for cannabinoid research, was used to demonstrate the detailed application of these technologies. We also provide our perspective on the challenges in polypharmacology research and possible solutions. The in silico technologies for polypharmacology research can predict possible off-targets to avoid adverse effects, to suggest new targets of approved drugs for drug repurposing, and even to evaluate in silico affinity and selectivity among protein families.