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Binding Profile Assessment of SARS-CoV-2 Spike Protein RBD Mutants with hACE2 Protein Using In Silico Methods

Zhang, Yuzhao (2021) Binding Profile Assessment of SARS-CoV-2 Spike Protein RBD Mutants with hACE2 Protein Using In Silico Methods. Master's Thesis, University of Pittsburgh. (Unpublished)

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Abstract

SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2), a novel coronavirus, has brought an unprecedented pandemic to the world and affected over 100 million people. The virus infects humans using its spike glycoprotein, which is mediated by a crucial area, receptor binding domain (RBD), to bind to the human ACE2 (hACE2) receptor. Mutations on RBD have been observed in different countries and classified into various types. In this research work, we studied A435S, D364Y, G476S, N354D/D364Y, N501Y, R408I, V341I, V367F, V483A, W436R, N501Y, N501Y/E484K, N501Y/K417N, and N501Y/E484K/K417N, 14 mutant types plus the prototype. Employing molecular dynamics (MD) simulation, we investigated dynamics and structures of the complexes of the prototype and mutant types of SARS-CoV-2 spike RBDs and hACE2. We then probed binding free energies of the prototype and mutant types of RBD with hACE2 protein by using an end-point molecular mechanics Poisson Boltzmann surface area (MM-PBSA) method. According to MM-PBSA binding free energy calculation results, 10 of the mutant types showed enhanced binding affinities with hACE2 compared to the prototype. Our computational protocols were validated by the successful prediction of relative binding free energies between prototype and three mutants: N354D/D364Y, V367F, and W436R. Thus, this study provides a reliable computational protocol to fast assess the existing and emerging RBD mutations. More importantly, the binding hotspots identified by using the molecular mechanics generalized Born surface area (MM-GBSA) free energy decomposition approach can guide the rational design of small molecule drugs or vaccines free of drug resistance to interfere with or eradicate spike-hACE2 binding. We selected key residues for both RBD and hACE2 to assist binding pocket design and provide six potential binding sites. A docking study using one of the predicted binding pockets revealed COVID-19 treatment potential of molecules from the NPC library. The docking scores were also compared with binding inhibitory bioassay results from NCATS.


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Zhang, Yuzhaoyuz170@pitt.eduyuz1700000-0002-4896-2140
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairJun, Jadenjjj46@pitt.edujjj46
Thesis AdvisorWang, Junmeijunmei.wang@pitt.edujunmei.wang
Committee MemberFeng, Zhiweizhf11@pitt.eduzhf11
Date: 15 April 2021
Date Type: Publication
Defense Date: 25 March 2021
Approval Date: 15 April 2021
Submission Date: 5 April 2021
Access Restriction: 2 year -- Restrict access to University of Pittsburgh for a period of 2 years.
Number of Pages: 60
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: SARS-CoV-2; COVID-19; Spike RBD/hACE2; MD simulation; Free energy calculation and decomposition; Hotspot residues; Protein-protein interaction
Date Deposited: 15 Apr 2021 16:04
Last Modified: 15 Apr 2023 05:15
URI: http://d-scholarship.pitt.edu/id/eprint/40517

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