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Systematic Data Mining Reveals Synergistic H3R/MCHR1 Ligands.

ABSTRACT: In this study, we report a ligand-centric data mining approach that guided the identification of suitable target profiles for treating obesity. The newly developed method is based on identifying target pairs for synergistic positive effects and also encompasses the exclusion of compounds showing a detrimental effect on obesity treatment (off-targets). Ligands with known activity against obesity-relevant targets were compared using fingerprint representations. Similar compounds with activities to different targets were evaluated for the mechanism of action since activation or deactivation of drug targets determines the pharmacological effect. In vitro validation of the modeling results revealed that three known modulators of melanin-concentrating hormone receptor 1 (MCHR1) show a previously unknown submicromolar affinity to the histamine H3 receptor (H₃R). This synergistic activity may present a novel therapeutic option against obesity.

SUBMITTER: Schaller D

PROVIDER: S-EPMC5467185 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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Systematic Data Mining Reveals Synergistic H3R/MCHR1 Ligands.

Schaller David D Hagenow Stefanie S Alpert Gina G Naß Alexandra A Schulz Robert R Bermudez Marcel M Stark Holger H Wolber Gerhard G

ACS medicinal chemistry letters 20170504 6

In this study, we report a ligand-centric data mining approach that guided the identification of suitable target profiles for treating obesity. The newly developed method is based on identifying target pairs for synergistic positive effects and also encompasses the exclusion of compounds showing a detrimental effect on obesity treatment (off-targets). Ligands with known activity against obesity-relevant targets were compared using fingerprint representations. Similar compounds with activities to ...[more]

PMID: 28626527

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