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Sci Rep . Analysis of critical protein-protein interactions of SARS-CoV-2 capping and proofreading molecular machineries towards designing dual targ

tetano

Editor, Senior Moderator
Sci Rep


. 2023 Jan 7;13(1):350.
doi: 10.1038/s41598-022-26778-8.
Analysis of critical protein-protein interactions of SARS-CoV-2 capping and proofreading molecular machineries towards designing dual target inhibitory peptides


Fatemeh Arabi-Jeshvaghani[SUP] 1 [/SUP], Fatemeh Javadi-Zarnaghi[SUP] 2 [/SUP], Mohamad Reza Ganjalikhany[SUP] 3 [/SUP]



Affiliations

Abstract

In recent years, the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as the cause of the coronavirus disease (COVID-19) global pandemic, and its variants, especially those with higher transmissibility and substantial immune evasion, have highlighted the imperative for developing novel therapeutics as sustainable solutions other than vaccination to combat coronaviruses (CoVs). Beside receptor recognition and virus entry, members of the SARS-CoV-2 replication/transcription complex are promising targets for designing antivirals. Here, the interacting residues that mediate protein-protein interactions (PPIs) of nsp10 with nsp16 and nsp14 were comprehensively analyzed, and the key residues' interaction maps, interaction energies, structural networks, and dynamics were investigated. Nsp10 stimulates both nsp14's exoribonuclease (ExoN) and nsp16's 2'O-methyltransferase (2'O-MTase). Nsp14 ExoN is an RNA proofreading enzyme that supports replication fidelity. Nsp16 2'O-MTase is responsible for the completion of RNA capping to ensure efficient replication and translation and escape from the host cell's innate immune system. The results of the PPIs analysis proposed crucial information with implications for designing SARS-CoV-2 antiviral drugs. Based on the predicted shared protein-protein interfaces of the nsp16-nsp10 and nsp14-nsp10 interactions, a set of dual-target peptide inhibitors was designed. The designed peptides were evaluated by molecular docking, peptide-protein interaction analysis, and free energy calculations, and then further optimized by in silico saturation mutagenesis. Based on the predicted evolutionary conservation of the interacted target residues among CoVs, the designed peptides have the potential to be developed as dual target pan-coronavirus inhibitors.
 
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