Substructure mining of GPCR ligands reveals activity-class specific functional groups in an unbiased manner

E van der Horst, Y Okuno, A Bender… - Journal of chemical …, 2009 - ACS Publications
E van der Horst, Y Okuno, A Bender, AP Ijzerman
Journal of chemical information and modeling, 2009ACS Publications
In this study, we conducted frequent substructure mining to identify structural features that
discriminate between ligands that do bind to G protein-coupled receptors (GPCRs) and
those that do not. In most cases, particular chemical representations resulted in the most
significant substructures. Substructures found to be characteristic for the background control
set reflected reactions that may have been used to construct this library, eg for the
ChemBridge DIVERSet library employed these are ester and carboxamide moieties. Alkane …
In this study, we conducted frequent substructure mining to identify structural features that discriminate between ligands that do bind to G protein-coupled receptors (GPCRs) and those that do not. In most cases, particular chemical representations resulted in the most significant substructures. Substructures found to be characteristic for the background control set reflected reactions that may have been used to construct this library, e.g. for the ChemBridge DIVERSet library employed these are ester and carboxamide moieties. Alkane amine substructures were identified as most important for GPCR ligands, e.g. the butylamine substructure, often linked to an aromatic system. Hierarchical analysis of targeted GPCRs revealed well-known motives and new substructural features. One example is the imidazole-like substructure common for the histamine binding receptor ligands. Another example is the planar ring system consisting of a fused five- and six-membered ring (indole-like substucture) common for the serotonin receptor ligands.
ACS Publications
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