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 (Mpro) is a leading target for drug design due to its conserved and indispensable role in the viral life cycle. Drugs targeting Mpro appear promising but will elicit selection pressure for resistance. To understand resistance potential in Mpro, 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 Mpro function in yeast, based on either the ability of Mpro 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 Mpro 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 Mpro dimer. The clinical variants of Mpro were predominantly functional in our screens, indicating that Mpro is under strong selection pressure in the human population. Our results provide predictions of mutations that will be readily accessible to Mpro evolution and that are likely to contribute to drug resistance. This complete mutational guide of Mpro can be used in the design of inhibitors with reduced potential of evolving viral resistance.
Next generation sequencing data has been deposited to the NCBI short read archive (PRJNA842255). Tabulated raw counts of all variants in all replicates are included in Figure 2 - source data 1. Figure 2 - source data 1, Figure 4 - source data 1, Figure 4 - source data 2, and Figure 5 - source data 1 contain the data used to generate all the figures.
Comprehensive fitness landscape of SARS-CoV-2 Mpro in S. cerevisiae - raw sequence readsNCBI Short Read Archive, PRJNA842255.
- Julia M Flynn
- Neha Samant
- Gily Schneider-Nachum
- Nese Kurt Yilmaz
- Celia A Schiffer
- Daniel NA Bolon
DTB, SAM, and DD are employees of Novartis Institutes for Biomedical Research and were involved in study design, data interpretation, and preparation of this manuscript.
- C Brandon Ogbunugafor, Yale University, United States
© 2022, Flynn et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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