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Characterizing the binding region of GPCRs based on molecular simulation and energy decomposition

Wang, Siyi (2020) Characterizing the binding region of GPCRs based on molecular simulation and energy decomposition. Master's Thesis, University of Pittsburgh. (Unpublished)

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G protein coupled receptors (GPCRs) are one of the largest and most important families of membrane proteins in humans. The binding of GPCRs with their orthosteric ligands activates the internal signal transduction pathways and sets off a cascade of reactions to regulate biological processes. 30-40% drugs currently on the market target the orthosteric binding pocket of GPCRs, however, increasing attention has been devoted to the allosteric binding pockets for its unique advantages, such as high selectivity and less side effects. Comprehensive characterization of protein is invaluable to infer its evolutionary processes and biological functions to achieve the desired substrate specificity and to design a drug with coveted selectivity. However, protein is complicated by its different functional regions or domains that can bind to some of its protein partner(s), substrate(s), orthosteric ligand(s), or allosteric modulator(s). Unlike a small molecule that can be easily characterized by its fingerprints, there are no cogent methods to comprehensively characterize the features of an entire protein or its substructure. In the present work, a scoring function-based computing protocol Molecular Complex Characterizing System (MCCS) was applied to help characterize the GPCRs. I first quantitatively calculate the energy contribution of each individual residue based on the receptor-ligand/modulator interactions, and the quantitated energy contribution of the residues involved in the binding pocket was used to represent a pattern of the ligand recognition of a receptor. It was found that residue energy contribution can not only identify the residues that contribute commonly to the binding of agonist and antagonist, but also distinguish the selective ones for either agonist or antagonist. Then, I applied multiple molecular simulation method to predict the CB1/CB2 allosteric binding mode and study the structure-activity relationship (SAR) of CB1/CB2 modulators. The present work comprehensively characterizes the interaction between GPCR with their ligands based on a new approach, which may aid in the facilitation of rational drug development.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Wang, Siyisywang2018@gmail.comsiw29
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairFeng, Zhiweizhf11@pitt.eduzhf11
Committee MemberXie, XQxix15@pitt.eduXIX15
Committee MemberWang,
Committee MemberKirisci, Leventlevent@pitt.edulevent
Date: 9 April 2020
Date Type: Publication
Defense Date: 18 March 2020
Approval Date: 9 April 2020
Submission Date: 1 April 2020
Access Restriction: 2 year -- Restrict access to University of Pittsburgh for a period of 2 years.
Number of Pages: 101
Institution: University of Pittsburgh
Schools and Programs: School of Pharmacy > Pharmaceutical Sciences
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: Molecular Simulation, molecular docking, molecular dynamic simulation, GPCR, cannabinoid receptor
Date Deposited: 09 Apr 2020 17:14
Last Modified: 09 Apr 2022 05:15


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