Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/9682
Full metadata record
DC FieldValueLanguage
dc.contributor.authorDesai, Kathan K.-
dc.date.accessioned2021-01-29T11:49:27Z-
dc.date.available2021-01-29T11:49:27Z-
dc.date.issued2020-04-
dc.identifier.urihttp://10.1.7.192:80/jspui/handle/123456789/9682-
dc.descriptionGuided by Dr. Jigna Shah & Co-guide Dr. Hardik Bhatten_US
dc.description.abstractAs indicated by the documented report of world health organization on diabetes that 422 million people who are suffering from diabetes today worldwide. Out of 4 person 1 is overweight and out of 10 adults 1 is obese person that is having capacity to develop the disease. Insulin hormone is a key to prevent diabetes but, if production of insulin is not as per the requirement then different drugs and mechanisms are needed to produce more insulin and prevent the disease. Despite the use of different drugs which act on different mechanism, PPAR gamma is exceedingly show its effect on diabetes. Under the class of Thiazolidinediones PPAR gamma receptors which act as nuclear receptors helps to prevent the disease by gene transcription process. Rosiglitazone and Pioglitazone are the drugs that act under these PPAR gamma receptor mechanism. For the proper arrangements of ligands various computational techniques are used. Pharmacophore model generation is one of the computational techniques is used for the generation of features and it is called as ligand-based pharmacophore method. After generation of pharmacophore model, molecules are refined and best features are selected for the further process like virtual screening, molecular docking. Compounds having different EC50 values are taken from highest to lowest and from that Pharmacophore model is generated. By using GASP module and DISCOTECH module in the SYBYL software these features are generated. After performing virtual screening, several compounds are generated from that top 10 structures are selected having best QFIT value.en_US
dc.publisherInstitute of Pharmacy, Nirma University, A'baden_US
dc.relation.ispartofseriesPPR00962;-
dc.subjectPPR00962en_US
dc.subjectB. Pharm Project Reporten_US
dc.subjectDiabetesen_US
dc.subjectPPAR gammaen_US
dc.subjectPharmacophore Modelen_US
dc.titlePharmacophore Modelling and Virtual Screening of PPAR Gamma Agonist for the Treatment of Diabetesen_US
dc.typeProject Reporten_US
Appears in Collections:B. Pharm Project Reports

Files in This Item:
File Description SizeFormat 
PPR00962.pdfPPR009621.19 MBAdobe PDFThumbnail
View/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.