Quantitative and systems pharmacology 2. In silico polypharmacology of G protein‐coupled receptor ligands via network‐based approaches

Graphical abstract Figure. No caption available. HighlightsWe proposed a network‐based systems pharmacology framework for comprehensive identification of new drug‐target interactions on GPCRs.An integrative network analysis reveals that ADRA2A, ADRA2C and CHRM2 are associated with cardiovascular complications of the approved GPCR drugs.We experimentally validated that two network‐predicted compounds (AM966 and Ki16425) showed high binding affinities on EP4. &NA; G protein‐coupled receptors (GPCRs) are the largest super family with more than 800 membrane receptors. Currently, over 30% of the approved drugs target human GPCRs. However, only approximately 30 human GPCRs have been resolved three‐dimensional crystal structures, which limits traditional structure‐based drug discovery. Recent advances in network‐based systems pharmacology approaches have demonstrated powerful strategies for identifying new targets of GPCR ligands. In this study, we proposed a network‐based systems pharmacology framework for comprehensive identification of new drug‐target interactions on GPCRs. Specifically, we reconstructed both global and local drug‐target interaction networks for human GPCRs. Network analysis on the known drug‐target networks showed rational strategies for designing new GPCR ligands and evaluating side effects of the approved GPCR drugs. We further built global and local network‐based models for predicting new targets of the known GPCR ligands. The area under the receiver operating characteristic curve of more than 0.96 was obtained for the best network‐based models in cross validation. In case studies, we identified that several network‐predicted GPCR off‐targets (e.g. ADRA2A, ADRA2C and CHRM2) were associated with cardiovascular complications (e.g. bradycardia and palpitations) of the approved GPCR drugs via an integrative analysis of drug‐target and off‐target‐adverse drug event networks. Importantly, we experimentally validated that two newly predicted compounds, AM966 and Ki16425, showed high binding affinities on prostaglandin E2 receptor EP4 subtype with IC50 = 2.67 &mgr;M and 6.34 &mgr;M, respectively. In summary, this study offers powerful network‐based tools for identifying polypharmacology of GPCR ligands in drug discovery and development.

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