Quantitative and systems pharmacology 2. In silico polypharmacology of G protein-coupled receptor ligands via network-based approaches. (March 2018)

• Record Type: Journal Article
• Authors: Wu, Zengrui; Lu, Weiqiang; Yu, Weiwei; Wang, Tianduanyi; Li, Weihua; Liu, Guixia; Zhang, Hankun; Pang, Xiufeng; Huang, Jin; Liu, Mingyao; Cheng, Feixiong; Tang, Yun
• Is Part Of: Pharmacological research. Volume 129(2018)
• Page Start: 400
• Page End: 413
• Publication Date: 2018-03
• Subjects: GPCR G protein-coupled receptor -- EP4 prostaglandin E2 receptor EP4 subtype -- LPAR lysophosphatidic acid receptor -- DTI drug-target interaction -- ADE adverse drug event -- MoA mechanism of action -- Ki inhibition constant -- Kd dissociation constant -- IC50 half-maximal inhibitory concentration -- EC50 half-maximal effective concentration -- NBI network-based inference -- SDTNBI substructure-drug-target network-based inference -- bSDTNBI balanced substructure-drug-target network-based inference -- TPR true positive rate -- FPR false positive rate -- ROC receiver operating characteristic -- AUC area under the receiver operating characteristic curve -- P precision -- R recall -- eP precision enhancement -- eR recall enhancement; AM966 (PubChem CID: 46240292) -- Ki16425 (PubChem CID: 10367662); Drug-target interaction -- G protein-coupled receptor -- Polypharmacology -- Network-based inference -- Systems pharmacology -- Computational approach; Pharmacology -- Periodicals; Pharmacology -- Periodicals; Research -- Periodicals; Médicaments -- Recherche -- Périodiques; Pharmacologie -- Périodiques; 615.105
• DOI: 10.1016/j.phrs.2017.11.005
• Languages: English
• ISSNs: 1043-6618

Abstract

Graphical abstract: Highlights: We 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. Abstract: 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 μM and 6.34 μM, respectively. In summary, this study offers powerful network-based tools for identifying polypharmacology of GPCR ligands in drug discovery and development.