Shabani Sadr, Narjes Khatoun, Mirzaei, Mahsa, Behmanesh, Mehrdad (2025). Computational Analysis of GPCR Networks in Opioid Use Disorder: From Transcriptomics to Drug Discovery. , 28(2), 35-49.
Narjes Khatoun Shabani Sadr; Mahsa Mirzaei; Mehrdad Behmanesh. "Computational Analysis of GPCR Networks in Opioid Use Disorder: From Transcriptomics to Drug Discovery". , 28, 2, 2025, 35-49.
Shabani Sadr, Narjes Khatoun, Mirzaei, Mahsa, Behmanesh, Mehrdad (2025). 'Computational Analysis of GPCR Networks in Opioid Use Disorder: From Transcriptomics to Drug Discovery', , 28(2), pp. 35-49.
Shabani Sadr, Narjes Khatoun, Mirzaei, Mahsa, Behmanesh, Mehrdad Computational Analysis of GPCR Networks in Opioid Use Disorder: From Transcriptomics to Drug Discovery. , 2025; 28(2): 35-49.

Computational Analysis of GPCR Networks in Opioid Use Disorder: From Transcriptomics to Drug Discovery

Pathobiology Reserach
Article 4, Volume 28, Issue 2, 2025, Pages 35-49    PDF (1.28 M)
Document Type: Original Research
Authors
Narjes Khatoun Shabani Sadr1; Mahsa Mirzaei1; Mehrdad Behmanesh* 2
1Department of Genetics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran
2Department of Genetics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, IranInstitute for Brain and Cognition, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
Abstract
Introduction: Opioid Use Disorder (OUD) is a chronic neuropsychiatric condition driven by persistent neuroadaptive changes in reward, motivation, and stress-related circuits. While opioid receptors are central to OUD, the broader role of G protein-coupled receptors (GPCRs) in opioid-induced neuroplasticity remains underexplored. This study systematically characterizes GPCR dysregulation in OUD to identify potential pharmacological targets. Methods: We performed transcriptomic analysis of RNA sequencing (RNA-seq) datasets from addiction-related brain regions, including the dorsolateral prefrontal cortex (DLPFC) and nucleus accumbens (GSE174409), Brodmann area 9 (GSE182321), and central amygdala (GSE194368). A curated set of ~900 GPCR genes was analyzed for differentially expressed genes (DEG), principal component analysis (PCA), and hierarchical clustering. Drug-targetable GPCRs were identified via DrugBank and ChEMBL, and their behavioral and stress-related roles were determined. Protein-protein interaction (PPI) networks were constructed using STRING. Results: We identified 58 GPCRs consistently dysregulated across brain regions, reflecting common molecular adaptations in OUD. PCA revealed a clear separation between OUD and control groups, indicating distinct receptor remodeling. Hierarchical clustering identified functional subgroups, including drug-targetable GPCRs and orphan GPCRs. Notably, 17 GPCRs—including DRD1, DRD3, DRD4, HTR1A, HTR2A, OXTR, and CNR1—are involved in behavioral regulation and addiction vulnerability. Network analysis highlighted key receptor hubs, suggesting novel therapeutic targets. Conclusion: The present study provides a receptor-centric framework for drug repurposing and precision medicine in OUD. Integrating transcriptomic and pharmacological data, we highlight GPCRs with translational potential. Further validation through functional assays and single-cell studies is warranted.
Keywords
Opioid Use Disorder; GPCR; Bioinformatics; RNA-seq; Drug Repurposing; Addiction Therapy
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