Systematic Data Mining Reveals Synergistic H3R/MCHR1 Ligands
| Autor: | David Schaller, Alexandra Naß, Holger Stark, Gina Alpert, Robert Schulz, Gerhard Wolber, Stefanie Hagenow, Marcel Bermudez |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Drug business.industry media_common.quotation_subject Organic Chemistry Pharmacology Biology computer.software_genre Biochemistry In vitro 03 medical and health sciences 030104 developmental biology 0302 clinical medicine Text mining Mechanism of action Hormone receptor 030220 oncology & carcinogenesis Drug Discovery medicine Data mining medicine.symptom Histamine H3 receptor business computer media_common |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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