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Centrality of Drug Targets in Protein Networks by Ariele Viacava Follis is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

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## Abstract ## Background In the pharmaceutical industry, competing for few validated drug targets there is a drive to identify new ways of therapeutic intervention. Here, we attempted to define guidelines to evaluate a target’s ‘fitness’ based on its node characteristics within annotated protein functional networks to complement contingent therapeutic hypotheses. ## Results We observed that targets of approved, selective small molecule drugs exhibit high node centrality within protein networks relative to a broader set of investigational targets spanning various development stages. Targets of approved drugs also exhibit higher centrality than other proteins within their respective functional class. These findings expand on previous reports of drug targets’ network centrality by suggesting some centrality metrics such as low topological coefficient as inherent characteristics of a ‘good’ target, relative to other exploratory targets and regardless of its functional class. These centrality metrics could thus be indicators of an individual protein’s ‘fitness’ as potential drug target. Correlations between protein nodes’ network centrality and number of associated publications undersc

Who reads Centrality of Drug Targets in Protein Networks?

Author

Ariele Viacava Follis

Publisher

Springer Science and Business Media LLC

Published

2021

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)