Coronaviruses can evolve and spread rapidly to cause severe disease morbidity and mortality, as exemplified by SARS-CoV-2 variants of the COVID-19 pandemic. Although currently available vaccines remain mostly effective against SARS-CoV-2 variants, additional treatment strategies are needed. Inhibitors that target essential viral enzymes, such as proteases and polymerases, represent key classes of antivirals. However, clinical use of antiviral therapies inevitably leads to emergence of drug resistance. In this study we implemented a strategy to pre-emptively address drug resistance to protease inhibitors targeting the main protease (Mpro) of SARS-CoV-2, an essential enzyme that promotes viral maturation. We solved nine high-resolution cocrystal structures of SARS-CoV-2 Mpro bound to substrate peptides and six structures with cleavage products. These structures enabled us to define the substrate envelope of Mpro, map the critical recognition elements, and identify evolutionarily vulnerable sites that may be susceptible to resistance mutations that would compromise binding of the newly developed Mpro inhibitors. Our results suggest strategies for developing robust inhibitors against SARS-CoV-2 that will retain longer-lasting efficacy against this evolving viral pathogen.

Herein we provide a living summary of the data generated during the COVID Moonshot project focused on the development of SARS-CoV-2 main protease (Mpro) inhibitors. Our approach uniquely combines crowdsourced medicinal chemistry insights with high throughput crystallography, exascale computational chemistry infrastructure for simulations, and machine learning in triaging designs and predicting synthetic routes. This manuscript describes our methodologies leading to both covalent and non-covalent inhibitors displaying protease IC50 values under 150 nM and viral inhibition under 5 uM in multiple different viral replication assays. Furthermore, we provide over 200 crystal structures of fragment-like and lead-like molecules in complex with the main protease. Over 1000 synthesized and ordered compounds are also reported with the corresponding activity in Mpro enzymatic assays using two different experimental setups. The data referenced in this document will be continually updated to reflect the current experimental progress of the COVID Moonshot project, and serves as a citable reference for ensuing publications. All of the generated data is open to other researchers who may find it of use.

Drugs that target the main protease (Mpro) of SARS-CoV-2 are effective therapeutics that have entered clinical use. Wide-scale use of these drugs will apply selection pressure for the evolution of resistance mutations. To understand resistance potential in Mpro, we performed comprehensive surveys of amino acid changes that can cause resistance in a yeast screen to nirmatrelvir (contained in the drug Paxlovid), and ensitrelvir (Xocova) that is currently in phase III trials. The most impactful resistance mutation (E166V) recently reported in multiple viral passaging studies with nirmatrelvir showed the strongest drug resistance score for nirmatrelvir, while P168R had the strongest resistance score for ensitrelvir. Using a systematic approach to assess potential drug resistance, we identified 142 resistance mutations for nirmatrelvir and 177 for ensitrelvir. Among these mutations, 99 caused apparent resistance to both inhibitors, suggesting a strong likelihood for the evolution of cross-resistance. Many mutations that exhibited inhibitor-specific resistance were consistent with distinct ways that each inhibitor protrudes beyond the substrate envelope. In addition, mutations with strong drug resistance scores tended to have reduced function. Our results indicate that strong pressure from nirmatrelvir or ensitrelvir will select for multiple distinct resistant lineages that will include both primary resistance mutations that weaken interactions with drug while decreasing enzyme function and secondary mutations that increase enzyme activity. The comprehensive identification of resistance mutations enables the design of inhibitors with reduced potential of developing resistance and aids in the surveillance of drug resistance in circulating viral populations.

Coronaviruses, as exemplified by SARS-CoV-2, can evolve and spread rapidly to cause severe disease morbidity and mortality. Direct acting antivirals (DAAs) are highly effective in decreasing disease burden especially when they target essential viral enzymes, such as proteases and polymerases, as demonstrated in HIV-1 and HCV and most recently SARS-CoV-2. Optimization of these DAAs through iterative structure-based drug design has been shown to be critical. Particularly, the evolutionarily conserved molecular mechanisms underlying viral replication can be leveraged to develop robust antivirals against rapidly evolving viral targets. The main protease (Mpro) of SARS-CoV-2, which is evolutionarily constrained to recognize and cleave 11 specific sites to promote viral maturation, exemplifies one such target. In this study we define the substrate envelope of Mpro by determining the molecular basis of substrate recognition, through nine high-resolution cocrystal structures of SARS-CoV-2 Mpro with the viral cleavage sites. These structures enable identification of evolutionarily vulnerable sites beyond the substrate envelope that may be susceptible to drug resistance and compromise binding of the newly developed Mpro inhibitors.

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