Comprehensive fitness landscape of SARS-CoV-2 M(pro) reveals insights into viral resistance mechanisms
Flynn, Julia M ; Samant, Neha S. ; Nachum, Gily S. ; Bakan, David T. ; Yilmaz, Nese Kurt ; Schiffer, Celia A. ; Moquin, Stephanie A. ; Dovala, Dustin ; Bolon, Daniel N A
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evolutionary biology
infectious disease
microbiology
SARS-CoV-2
Amino Acids, Peptides, and Proteins
Biochemistry, Biophysics, and Structural Biology
Ecology and Evolutionary Biology
Immunology and Infectious Disease
Infectious Disease
Medicinal Chemistry and Pharmaceutics
Medicinal-Pharmaceutical Chemistry
Microbiology
Virology
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Abstract
With the continual evolution of new strains of SARS-CoV-2 that are more virulent, transmissible, and able to evade current vaccines, there is an urgent need for effective anti-viral drugs SARS-CoV-2 main protease (M(pro)) is a leading target for drug design due to its conserved and indispensable role in the viral life cycle. Drugs targeting M(pro) appear promising but will elicit selection pressure for resistance. To understand resistance potential in M(pro), we performed a comprehensive mutational scan of the protease that analyzed the function of all possible single amino acid changes. We developed three separate high-throughput assays of M(pro) function in yeast, based on either the ability of M(pro) variants to cleave at a defined cut-site or on the toxicity of their expression to yeast. We used deep sequencing to quantify the functional effects of each variant in each screen. The protein fitness landscapes from all three screens were strongly correlated, indicating that they captured the biophysical properties critical to M(pro) function. The fitness landscapes revealed a non-active site location on the surface that is extremely sensitive to mutation making it a favorable location to target with inhibitors. In addition, we found a network of critical amino acids that physically bridge the two active sites of the M(pro) dimer. The clinical variants of M(pro) were predominantly functional in our screens, indicating that M(pro) is under strong selection pressure in the human population. Our results provide predictions of mutations that will be readily accessible to M(pro) evolution and that are likely to contribute to drug resistance. This complete mutational guide of M(pro) can be used in the design of inhibitors with reduced potential of evolving viral resistance.
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Flynn JM, Samant N, Schneider-Nachum G, Bakan DT, Yilmaz NK, Schiffer CA, Moquin SA, Dovala D, Bolon DNA. Comprehensive fitness landscape of SARS-CoV-2 Mpro reveals insights into viral resistance mechanisms. Elife. 2022 Jun 20;11:e77433. doi: 10.7554/eLife.77433. Epub ahead of print. PMID: 35723575. Link to article on publisher's site