{"title":"Dynamic properties of the growth hormone releasing hormone receptor (GHRHR) and molecular determinants of GHRH binding†","authors":"M.-T. Matsoukas and G. A. Spyroulias","doi":"10.1039/C7MB00130D","DOIUrl":null,"url":null,"abstract":"<p >The growth hormone-releasing hormone receptor (GHRHR) is a member of the class B GPCR subfamily. GHRH, a 44-residue neuropeptide produced in the hypothalamus, regulates the secretion of growth hormone through its binding to GHRHR. It has recently been associated with several types of cancer such as prostate, breast, pancreatic and ovarian cancer. Family B GPCR peptides bind in a two-step model, where first the C-terminal region of the peptide interacts with the extracellular domain (ECD) of the receptor and subsequently, the N-terminal interacts with the seven transmembrane domain (TMD), resulting in activation. Structural information on family B GPCRs is limited; therefore, the use of computational methods may assist their efficient targeting towards new therapeutics. Here, we have utilized several computational tools, such as homology modelling, docking, large-scale molecular dynamics and principal component analysis (PCA), in order to: (a) gain information on the dynamic properties of the receptor domains and (b) propose a structural model for the interactions between GHRH and the ECD and TMD regions of GHRHR respectively. We conclude that PCA analysis can be used for studying such relative movements in family B GPCRs and provide a structural model, which may assist in the design of highly anticipated non-peptide antagonists against GHRHR.</p>","PeriodicalId":90,"journal":{"name":"Molecular BioSystems","volume":" 7","pages":" 1313-1322"},"PeriodicalIF":3.7430,"publicationDate":"2017-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1039/C7MB00130D","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular BioSystems","FirstCategoryId":"1085","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2017/mb/c7mb00130d","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
引用次数: 7
Abstract
The growth hormone-releasing hormone receptor (GHRHR) is a member of the class B GPCR subfamily. GHRH, a 44-residue neuropeptide produced in the hypothalamus, regulates the secretion of growth hormone through its binding to GHRHR. It has recently been associated with several types of cancer such as prostate, breast, pancreatic and ovarian cancer. Family B GPCR peptides bind in a two-step model, where first the C-terminal region of the peptide interacts with the extracellular domain (ECD) of the receptor and subsequently, the N-terminal interacts with the seven transmembrane domain (TMD), resulting in activation. Structural information on family B GPCRs is limited; therefore, the use of computational methods may assist their efficient targeting towards new therapeutics. Here, we have utilized several computational tools, such as homology modelling, docking, large-scale molecular dynamics and principal component analysis (PCA), in order to: (a) gain information on the dynamic properties of the receptor domains and (b) propose a structural model for the interactions between GHRH and the ECD and TMD regions of GHRHR respectively. We conclude that PCA analysis can be used for studying such relative movements in family B GPCRs and provide a structural model, which may assist in the design of highly anticipated non-peptide antagonists against GHRHR.
期刊介绍:
Molecular Omics publishes molecular level experimental and bioinformatics research in the -omics sciences, including genomics, proteomics, transcriptomics and metabolomics. We will also welcome multidisciplinary papers presenting studies combining different types of omics, or the interface of omics and other fields such as systems biology or chemical biology.