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G protein-coupled receptors that influence lifespan of human and animal models.

ABSTRACT: Humanity has always sought to live longer and for this, multiple strategies have been tried with varying results. In this sense, G protein-coupled receptors (GPCRs) may be a good option to try to prolong our life while maintaining good health since they have a substantial participation in a wide variety of processes of human pathophysiology and are one of the main therapeutic targets. In this way, we present the analysis of a series of GPCRs whose activity has been shown to affect the lifespan of animal and human models, and in which we put a special interest in describing the molecular mechanisms involved. Our compilation of data revealed that the mechanisms most involved in the role of GPCRs in lifespan are those that mimic dietary restriction, those related to insulin signaling and the AMPK and TOR pathways, and those that alter oxidative homeostasis and severe and/or chronic inflammation. We also discuss the possibility of using agonist or antagonist drugs, depending on the beneficial or harmful effects of each GPCR, in order to prolong people's lifespan and healthspan.

SUBMITTER: Lagunas-Rangel FA

PROVIDER: S-EPMC8888397 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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G protein-coupled receptors that influence lifespan of human and animal models.

Lagunas-Rangel Francisco Alejandro FA

Biogerontology 20211203 1

Humanity has always sought to live longer and for this, multiple strategies have been tried with varying results. In this sense, G protein-coupled receptors (GPCRs) may be a good option to try to prolong our life while maintaining good health since they have a substantial participation in a wide variety of processes of human pathophysiology and are one of the main therapeutic targets. In this way, we present the analysis of a series of GPCRs whose activity has been shown to affect the lifespan o ...[more]

PMID: 34860303

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Project description:BackgroundOlfactory receptors (ORs) constitute a large family of sensory proteins that enable us to recognize a wide range of chemical volatiles in the environment. By contrast to the extensive information about human olfactory thresholds for thousands of odorants, studies of the genetic influence on olfaction are limited to a few examples. To annotate on a broad scale the impact of mutations at the structural level, here we analyzed a compendium of 119,069 natural variants in human ORs collected from the public domain.ResultsOR mutations were categorized depending on their genomic and protein contexts, as well as their frequency of occurrence in several human populations. Functional interpretation of the natural changes was estimated from the increasing knowledge of the structure and function of the G protein-coupled receptor (GPCR) family, to which ORs belong. Our analysis reveals an extraordinary diversity of natural variations in the olfactory gene repertoire between individuals and populations, with a significant number of changes occurring at the structurally conserved regions. A particular attention is paid to mutations in positions linked to the conserved GPCR activation mechanism that could imply phenotypic variation in the olfactory perception. An interactive web application (hORMdb, Human Olfactory Receptor Mutation Database) was developed for the management and visualization of this mutational dataset.ConclusionWe performed topological annotations and population analysis of natural variants of human olfactory receptors and provide an interactive application to explore human OR mutation data. We envisage that the utility of this information will increase as the amount of available pharmacological data for these receptors grow. This effort, together with ongoing research in the study of genetic changes in other sensory receptors could shape an emerging sensegenomics field of knowledge, which should be considered by food and cosmetic consumer product manufacturers for the benefit of the general population.

Project description:The rapidly increasing number of high-resolution X-ray structures of G-protein coupled receptors (GPCRs) creates a unique opportunity to employ comparative modeling and docking to provide valuable insight into the function and ligand binding determinants of novel receptors, to assist in virtual screening and to design and optimize drug candidates. However, low sequence identity between receptors, conformational flexibility, and chemical diversity of ligands present an enormous challenge to molecular modeling approaches. It is our hypothesis that rapid Monte-Carlo sampling of protein backbone and side-chain conformational space with Rosetta can be leveraged to meet this challenge. This study performs unbiased comparative modeling and docking methodologies using 14 distinct high-resolution GPCRs and proposes knowledge-based filtering methods for improvement of sampling performance and identification of correct ligand-receptor interactions. On average, top ranked receptor models built on template structures over 50% sequence identity are within 2.9 Å of the experimental structure, with an average root mean square deviation (RMSD) of 2.2 Å for the transmembrane region and 5 Å for the second extracellular loop. Furthermore, these models are consistently correlated with low Rosetta energy score. To predict their binding modes, ligand conformers of the 14 ligands co-crystalized with the GPCRs were docked against the top ranked comparative models. In contrast to the comparative models themselves, however, it remains difficult to unambiguously identify correct binding modes by score alone. On average, sampling performance was improved by 10(3) fold over random using knowledge-based and energy-based filters. In assessing the applicability of experimental constraints, we found that sampling performance is increased by one order of magnitude for every 10 residues known to contact the ligand. Additionally, in the case of DOR, knowledge of a single specific ligand-protein contact improved sampling efficiency 7 fold. These findings offer specific guidelines which may lead to increased success in determining receptor-ligand complexes.

Dataset Information

G protein-coupled receptors that influence lifespan of human and animal models.

Publications

G protein-coupled receptors that influence lifespan of human and animal models.

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