Comprehensive fitness landscape of SARS-CoV-2 Mpro reveals insights into viral resistance mechanisms
- University of Massachusetts Medical School, United States
- Novartis, United States
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 (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.
Data availability
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.
Article and author information
Author details
Funding
Novartis Institutes for BioMedical Research
- 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.
Copyright
© 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.
Metrics
-
- 3,309
- views
-
- 596
- downloads
-
- 79
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Comprehensive fitness landscape of SARS-CoV-2 Mpro reveals insights into viral resistance mechanisms
eLife 11:e77433.
https://doi.org/10.7554/eLife.77433
Further reading
-
- Epidemiology and Global Health
- Medicine
- Microbiology and Infectious Disease
eLife has published the following articles on SARS-CoV-2 and COVID-19.
-
- Evolutionary Biology
- Microbiology and Infectious Disease
Accurate estimation of the effects of mutations on SARS-CoV-2 viral fitness can inform public-health responses such as vaccine development and predicting the impact of a new variant; it can also illuminate biological mechanisms including those underlying the emergence of variants of concern. Recently, Lan et al. reported a model of SARS-CoV-2 secondary structure and its underlying dimethyl sulfate reactivity data (Lan et al., 2022). I investigated whether base reactivities and secondary structure models derived from them can explain some variability in the frequency of observing different nucleotide substitutions across millions of patient sequences in the SARS-CoV-2 phylogenetic tree. Nucleotide basepairing was compared to the estimated ‘mutational fitness’ of substitutions, a measurement of the difference between a substitution’s observed and expected frequency that is correlated with other estimates of viral fitness (Bloom and Neher, 2023). This comparison revealed that secondary structure is often predictive of substitution frequency, with significant decreases in substitution frequencies at basepaired positions. Focusing on the mutational fitness of C→U, the most common type of substitution, I describe C→U substitutions at basepaired positions that characterize major SARS-CoV-2 variants; such mutations may have a greater impact on fitness than appreciated when considering substitution frequency alone.
