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

Xiang Qun Xie, Lirong Wang, Junmei Wang, Zhaojun Xie, Peng Yang, Qin Ouyang

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationNeuropathology of Drug Addictions and Substance Misuse Volume 3
Subtitle of host publicationGeneral Processes and Mechanisms, Prescription Medications, Caffeine and Areca, Polydrug Misuse, Emerging Addictions and Non-Drug Addictions
PublisherElsevier
Pages183-195
Number of pages13
Volume3
ISBN (Electronic)9780128006771
ISBN (Print)9780128006344
DOIs
StatePublished - Jan 1 2016

Keywords

  • Cannabinoid drug abuse
  • Chemogenomics knowledgebase
  • Molecular docking
  • Systems pharmacology
  • TargetHunter

ASJC Scopus subject areas

  • General Neuroscience
  • General Medicine

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