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Yaribeygi H, Maleki M, Jamialahmadi T, Sahebkar A. Anti-inflammatory benefits of semaglutide: State of the art. J Clin Transl Endocrinol 2024; 36:100340. [PMID: 38576822 PMCID: PMC10992717 DOI: 10.1016/j.jcte.2024.100340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 03/06/2024] [Accepted: 03/20/2024] [Indexed: 04/06/2024] Open
Abstract
Individuals with diabetes often have chronic inflammation and high levels of inflammatory cytokines, leading to insulin resistance and complications. Anti-inflammatory agents are proposed to prevent these issues, including using antidiabetic medications with anti-inflammatory properties like semaglutide, a GLP-1 analogue. Semaglutide not only lowers glucose but also shows potential anti-inflammatory effects. Studies suggest it can modulate inflammatory responses and benefit those with diabetes. However, the exact mechanisms of its anti-inflammatory effects are not fully understood. This review aims to discuss the latest findings on semaglutide's anti-inflammatory effects and the potential pathways involved.
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Affiliation(s)
- Habib Yaribeygi
- Research Center of Physiology, Semnan University of Medical Sciences, Semnan, Iran
| | - Mina Maleki
- Urology and Nephrology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Tannaz Jamialahmadi
- Medical Toxicology Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
- Pharmaceutical Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Amirhossein Sahebkar
- Applied Biomedical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
- Biotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran
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Tong M, Liu Z, Li J, Wei X, Shi W, Liang C, Yu C, Huang R, Lin Y, Wang X, Wang S, Wang Y, Huang J, Wang Y, Li T, Qin J, Zhan D, Ji ZL. PhosMap: An ensemble bioinformatic platform to empower interactive analysis of quantitative phosphoproteomics. Comput Biol Med 2024; 174:108391. [PMID: 38613887 DOI: 10.1016/j.compbiomed.2024.108391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 03/18/2024] [Accepted: 04/01/2024] [Indexed: 04/15/2024]
Abstract
BACKGROUND Liquid chromatography-mass spectrometry (LC-MS)-based quantitative phosphoproteomics has been widely used to detect thousands of protein phosphorylation modifications simultaneously from the biological specimens. However, the complicated procedures for analyzing phosphoproteomics data has become a bottleneck to widening its application. METHODS Here, we develop PhosMap, a versatile and scalable tool to accomplish phosphoproteomics data analysis. A standardized phosphorylation data format was created for data analyses, from data preprocessing to downstream bioinformatic analyses such as dimension reduction, differential phosphorylation analysis, kinase activity, survival analysis, and so on. For better usability, we distribute PhosMap as a Docker image for easy local deployment upon any of Windows, Linux, and Mac system. RESULTS The source code is deposited at https://github.com/BADD-XMU/PhosMap. A free PhosMap webserver (https://huggingface.co/spaces/Bio-Add/PhosMap), with easy-to-follow fashion of dashboards, is curated for interactive data analysis. CONCLUSIONS PhosMap fills the technical gap of large-scale phosphorylation research by empowering researchers to process their own phosphoproteomics data expediently and efficiently, and facilitates better data interpretation.
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Affiliation(s)
- Mengsha Tong
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, Fujian, 361102, China; National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, Fujian, 361102, China
| | - Zan Liu
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, Fujian, 361102, China; National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, Fujian, 361102, China
| | - Jiaao Li
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, Fujian, 361102, China
| | - Xin Wei
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China
| | - Wenhao Shi
- Analysis Center, Chemistry Department, Tsinghua University, Beijing, 100084, China
| | - Chenyu Liang
- National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, Fujian, 361102, China
| | - Chunyu Yu
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hangzhou Normal University, Hangzhou, 311121, China
| | - Rongting Huang
- Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, 100191, China
| | - Yuxiang Lin
- National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, Fujian, 361102, China
| | - Xinkang Wang
- National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, Fujian, 361102, China
| | - Shun Wang
- Departments of Pathology, National Cancer Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Yi Wang
- Beijing Pineal Diagnostics Co., Ltd., Beijing, 102206, China; State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China
| | - Jialiang Huang
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, Fujian, 361102, China; National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, Fujian, 361102, China
| | - Yini Wang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China
| | - Tingting Li
- Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, 100191, China.
| | - Jun Qin
- Beijing Pineal Diagnostics Co., Ltd., Beijing, 102206, China; State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China.
| | - Dongdong Zhan
- Beijing Pineal Diagnostics Co., Ltd., Beijing, 102206, China.
| | - Zhi-Liang Ji
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, Fujian, 361102, China; National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, Fujian, 361102, China.
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Rosenkilde MM, Lindquist P, Kizilkaya HS, Gasbjerg LS. GIP-derived GIP receptor antagonists - a review of their role in GIP receptor pharmacology. Peptides 2024; 177:171212. [PMID: 38608836 DOI: 10.1016/j.peptides.2024.171212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2024] [Revised: 04/01/2024] [Accepted: 04/08/2024] [Indexed: 04/14/2024]
Abstract
Surprisingly, agonists, as well as antagonists of the glucose-dependent insulinotropic polypeptide receptor (GIPR), are currently being used or investigated as treatment options for type 2 diabetes and obesity - and both, when combined with glucagon-like peptide 1 receptor (GLP-1R) agonism, enhance GLP-1-induced glycemia and weight loss further. This paradox raises several questions regarding not only the mechanisms of actions of GIP but also the processes engaged during the activation of both the GIP and GLP-1 receptors. Here, we provide an overview of studies of the properties and actions of peptide-derived GIPR antagonists, focusing on GIP(3-30)NH2, a naturally occurring N- and C-terminal truncation of GIP(1-42). GIP(3-30)NH2 was the first GIPR antagonist administered to humans. GIP(3-30)NH2 and a few additional antagonists, like Pro3-GIP, have been used in both in vitro and in vivo studies to elucidate the molecular and cellular consequences of GIPR inhibition, desensitization, and internalization and, at a larger scale, the role of the GIP system in health and disease. We provide an overview of these studies combined with recent knowledge regarding the effects of naturally occurring variants of the GIPR system and species differences within the GIP system to enhance our understanding of the GIPR as a drug target.
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Affiliation(s)
- Mette Marie Rosenkilde
- Molecular and Translational Pharmacology, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - Peter Lindquist
- Molecular and Translational Pharmacology, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Hüsün Sheyma Kizilkaya
- Molecular and Translational Pharmacology, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Lærke Smidt Gasbjerg
- Molecular and Translational Pharmacology, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark.
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Kotliar IB, Bendes A, Dahl L, Chen Y, Saarinen M, Ceraudo E, Dodig-Crnković T, Uhlén M, Svenningsson P, Schwenk JM, Sakmar TP. Expanding the GPCR-RAMP interactome. bioRxiv 2023:2023.11.22.568247. [PMID: 38045268 PMCID: PMC10690247 DOI: 10.1101/2023.11.22.568247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Receptor activity-modifying proteins (RAMPs) can form complexes with G protein-coupled receptors (GPCRs) and regulate their cellular trafficking and pharmacology. RAMP interactions have been identified for about 50 GPCRs, but only a few GPCR-RAMP complexes have been studied in detail. To elucidate a complete interactome between GPCRs and the three RAMPs, we developed a customized library of 215 Dual Epitope-Tagged (DuET) GPCRs representing all GPCR subfamilies. Using a multiplexed suspension bead array (SBA) assay, we identified 122 GPCRs that showed strong evidence for interaction with at least one RAMP. We screened for native interactions in three cell lines and found 23 GPCRs that formed complexes with RAMPs. Mapping the GPCR-RAMP interactome expands the current system-wide functional characterization of RAMP-interacting GPCRs to inform the design of selective GPCR-targeted therapeutics. One-Sentence Summary Novel complexes between G protein-coupled receptors and interacting proteins point to a system-wide regulation of GPCR function.
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