Abstract
MotivationDrug 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.ResultsThe 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.Availabilityhttps://smartgraph.ncats.io/.
Highlights
The path to successful drug discovery frequently demands understanding the complex network-pharmacology (NP) landscape [1]
Knowledge base of SmartGraph The knowledgebase of the framework was implemented in Neo4j graph-database which contains 1,732,553 unique compounds and 4583 protein targets
Targets and scaffolds is stored in the Neo4j graph-database
Summary
The path to successful drug discovery frequently demands understanding the complex network-pharmacology (NP) landscape [1]. A rational design workflow that integrates NP needs to consider multiple interactions between a drug molecule and its intended (target, or “on-target”) and not-intended (“off-target”) interaction partners. Due to the existence of multiple pathways between proteins, the effects of a drug molecule might ripple to proteins not in direct contact with the drug in question. Such perturbations may alter gene-expression profiles of cells. The complex nature of this interaction-landscape demands novel and integrated target-chemistry-bioactivity approaches [3] in drug discovery and facilitates the devising of new therapeutic strategies, e.g., multitarget therapies.
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