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Identification of Allosteric Modulators of Metabotropic Glutamate 7 Receptor Using Proteochemometric Modeling

[Image: see text] Proteochemometric modeling (PCM) is a computational approach that can be considered an extension of quantitative structure–activity relationship (QSAR) modeling, where a single model incorporates information for a family of targets and all the associated ligands instead of modeling...

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Detalles Bibliográficos
Autores principales: Tresadern, Gary, Trabanco, Andres A., Pérez-Benito, Laura, Overington, John P., van Vlijmen, Herman W. T., van Westen, Gerard J. P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2017
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5755953/
https://www.ncbi.nlm.nih.gov/pubmed/29172488
http://dx.doi.org/10.1021/acs.jcim.7b00338
Descripción
Sumario:[Image: see text] Proteochemometric modeling (PCM) is a computational approach that can be considered an extension of quantitative structure–activity relationship (QSAR) modeling, where a single model incorporates information for a family of targets and all the associated ligands instead of modeling activity versus one target. This is especially useful for situations where bioactivity data exists for similar proteins but is scarce for the protein of interest. Here we demonstrate the application of PCM to identify allosteric modulators of metabotropic glutamate (mGlu) receptors. Given our long-running interest in modulating mGlu receptor function we compiled a matrix of compound-target bioactivity data. Some members of the mGlu family are well explored both internally and in the public domain, while there are much fewer examples of ligands for other targets such as the mGlu(7) receptor. Using a PCM approach mGlu(7) receptor hits were found. In comparison to conventional single target modeling the identified hits were more diverse, had a better confirmation rate, and provide starting points for further exploration. We conclude that the robust structure–activity relationship from well explored target family members translated to better quality hits for PCM compared to virtual screening (VS) based on a single target.