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SmartGraph: a network pharmacology investigation platform

Journal article
Authors G. Zahoranszky-Kohalmi
T. Sheils
Tudor I Oprea
Published in Journal of Cheminformatics
Volume 12
Issue 1
ISSN 1758-2946
Publication year 2020
Published at Institute of Medicine, Department of Rheumatology and Inflammation Research
Language en
Links dx.doi.org/10.1186/s13321-020-0409-...
Keywords Network pharmacology, Pathway analysis, Target deconvolution, Network, perturbation, Protein-protein interactions (PPIs), Bioactivity, prediction, Potent chemical pattern, Scaffold, neo4j, Network, visualization, drugs, Chemistry, Computer Science
Subject categories Computer and Information Science, Pharmacology

Abstract

Motivation Drug discovery investigations need to incorporate network pharmacology concepts while navigating the complex landscape of drug-target and target-target interactions. This task requires solutions that integrate high-quality biomedical data, combined with analytic and predictive workflows as well as efficient visualization. SmartGraph is an innovative platform that utilizes state-of-the-art technologies such as a Neo4j graph-database, Angular web framework, RxJS asynchronous event library and D3 visualization to accomplish these goals. Results The SmartGraph framework integrates high quality bioactivity data and biological pathway information resulting in a knowledgebase comprised of 420,526 unique compound-target interactions defined between 271,098 unique compounds and 2018 targets. SmartGraph then performs bioactivity predictions based on the 63,783 Bemis-Murcko scaffolds extracted from these compounds. Through several use-cases, we illustrate the use of SmartGraph to generate hypotheses for elucidating mechanism-of-action, drug-repurposing and off-target prediction. Availability: https://smartgraph.ncats.io/. .

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