Cargando…

Homology modelling of CB1 receptor and selection of potential inhibitor against Obesity

Obesity and patient morbidity has become a health concern worldwide. Obesity is associated with over activity of the endocannabinoid system, which is involved in the regulation of appetite, lipogenesis and insulin resistance. Hypothalamic cannabinoid-1 receptor (CB1R) inverse agonists reduce body we...

Descripción completa

Detalles Bibliográficos
Autores principales: Shrinivasan, Mahesh, Skariyachan, Sinosh, Aparna, Vaka, Kolte, Vinod Rama
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Biomedical Informatics 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3398776/
https://www.ncbi.nlm.nih.gov/pubmed/22829723
http://dx.doi.org/10.6026/97320630008523
_version_ 1782238320021995520
author Shrinivasan, Mahesh
Skariyachan, Sinosh
Aparna, Vaka
Kolte, Vinod Rama
author_facet Shrinivasan, Mahesh
Skariyachan, Sinosh
Aparna, Vaka
Kolte, Vinod Rama
author_sort Shrinivasan, Mahesh
collection PubMed
description Obesity and patient morbidity has become a health concern worldwide. Obesity is associated with over activity of the endocannabinoid system, which is involved in the regulation of appetite, lipogenesis and insulin resistance. Hypothalamic cannabinoid-1 receptor (CB1R) inverse agonists reduce body weight and improve cardiometabolic abnormalities in experimental and human obesity but displayed neuropsychiatric side effects. Hence, there is a need to develop therapeutics which employs blocking peripheral CB1 receptors and still achieve substantial weight loss. In view of the same, adipose tissue CB1 receptors are employed for this study since it is more specific in reducing visceral fat. Computer aided structure based virtual screening finds application to screen novel inhibitors and develop highly selective and potential drug. The rational drug design requires crystal structure for the CB1 receptor. However, the structure for the CB1 receptor is not available in its native form. Thus, we modelled the crystal structure using a lipid G-Protein coupled receptor (PDB: 3V2W, chain A) as template. Furthermore, we have screened a herbal ligand Quercetin [- 2- (3, 4-dihydroxyphenyl) - 3, 5, 7-trihydroxychromen-4-one] a flavonol present in Mimosa pudica based on its better pharmacokinetics and bioavailability profile. This ligand was selected as an ideal lead molecule. The docking of quercetin with CB1 receptor showed a binding energy of -6.56 Kcal/mol with 4 hydrogen bonds, in comparison to the known drug Rimonabant. This data finds application in proposing antagonism of CB1 receptor with Quercetin, for controlling obesity.
format Online
Article
Text
id pubmed-3398776
institution National Center for Biotechnology Information
language English
publishDate 2012
publisher Biomedical Informatics
record_format MEDLINE/PubMed
spelling pubmed-33987762012-07-24 Homology modelling of CB1 receptor and selection of potential inhibitor against Obesity Shrinivasan, Mahesh Skariyachan, Sinosh Aparna, Vaka Kolte, Vinod Rama Bioinformation Hypothesis Obesity and patient morbidity has become a health concern worldwide. Obesity is associated with over activity of the endocannabinoid system, which is involved in the regulation of appetite, lipogenesis and insulin resistance. Hypothalamic cannabinoid-1 receptor (CB1R) inverse agonists reduce body weight and improve cardiometabolic abnormalities in experimental and human obesity but displayed neuropsychiatric side effects. Hence, there is a need to develop therapeutics which employs blocking peripheral CB1 receptors and still achieve substantial weight loss. In view of the same, adipose tissue CB1 receptors are employed for this study since it is more specific in reducing visceral fat. Computer aided structure based virtual screening finds application to screen novel inhibitors and develop highly selective and potential drug. The rational drug design requires crystal structure for the CB1 receptor. However, the structure for the CB1 receptor is not available in its native form. Thus, we modelled the crystal structure using a lipid G-Protein coupled receptor (PDB: 3V2W, chain A) as template. Furthermore, we have screened a herbal ligand Quercetin [- 2- (3, 4-dihydroxyphenyl) - 3, 5, 7-trihydroxychromen-4-one] a flavonol present in Mimosa pudica based on its better pharmacokinetics and bioavailability profile. This ligand was selected as an ideal lead molecule. The docking of quercetin with CB1 receptor showed a binding energy of -6.56 Kcal/mol with 4 hydrogen bonds, in comparison to the known drug Rimonabant. This data finds application in proposing antagonism of CB1 receptor with Quercetin, for controlling obesity. Biomedical Informatics 2012-06-16 /pmc/articles/PMC3398776/ /pubmed/22829723 http://dx.doi.org/10.6026/97320630008523 Text en © 2012 Biomedical Informatics This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited.
spellingShingle Hypothesis
Shrinivasan, Mahesh
Skariyachan, Sinosh
Aparna, Vaka
Kolte, Vinod Rama
Homology modelling of CB1 receptor and selection of potential inhibitor against Obesity
title Homology modelling of CB1 receptor and selection of potential inhibitor against Obesity
title_full Homology modelling of CB1 receptor and selection of potential inhibitor against Obesity
title_fullStr Homology modelling of CB1 receptor and selection of potential inhibitor against Obesity
title_full_unstemmed Homology modelling of CB1 receptor and selection of potential inhibitor against Obesity
title_short Homology modelling of CB1 receptor and selection of potential inhibitor against Obesity
title_sort homology modelling of cb1 receptor and selection of potential inhibitor against obesity
topic Hypothesis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3398776/
https://www.ncbi.nlm.nih.gov/pubmed/22829723
http://dx.doi.org/10.6026/97320630008523
work_keys_str_mv AT shrinivasanmahesh homologymodellingofcb1receptorandselectionofpotentialinhibitoragainstobesity
AT skariyachansinosh homologymodellingofcb1receptorandselectionofpotentialinhibitoragainstobesity
AT aparnavaka homologymodellingofcb1receptorandselectionofpotentialinhibitoragainstobesity
AT koltevinodrama homologymodellingofcb1receptorandselectionofpotentialinhibitoragainstobesity