Functional map of SARS-CoV-2 3CL protease reveals tolerant and immutable sites

Revealing SARS-CoV-2 Mpro mutation cold and hot spots: Dynamic residue network analysis meets machine learning

Deciphering the effect of evolutionary mutations of viruses and predicting future mutations is crucial for designing long-lasting and effective drugs. While understanding the impact of current mutations on protein drug targets is feasible, predicting future mutations due to natural evolution of viruses and environmental pressures remains challenging. Here, we leveraged existing mutation data during the evolution of the SARS-CoV-2 protein drug target main protease (Mpro) to test the predictive power of dynamic residue network (DRN) analysis in identifying mutation cold and hot spots. We conducted molecular dynamics simulations on the Mpro of SARS-CoV-2 (Wuhan strain) and calculated eight DRN metrics (averaged BC, CC, DC, EC, ECC, KC, L, PR), each of which identifies a unique network feature within the protein. The sets of residues with the highest and lowest values for each metric, comprising potential cold and hot spots, were compared to published biochemical analyses and per residue mutation frequencies observed across five SARS-CoV-2 lineages, encompassing a total of 191,878 sequences. Individual DRN metrics displayed only modest power to predict the mutation frequency of individual residues. However, integrating the eight DRN metrics with additional structural and sequence-derived metrics allowed us to develop machine learning models which significantly improved the prediction of residue mutation frequency. While further refinements should enhance accuracy, we demonstrated a robust method to understand pathogen evolution. This approach can also guide the development of long-lasting drugs by targeting functional residues located in and near active site, and allosteric sites, that are less prone to mutations.

SARS-CoV-2 main protease (M-pro) mutational profiling: An insight into mutation coldspots

SARS-CoV-2 and the COVID-19 pandemic have marked a milestone in the history of scientific research worldwide. To ensure that treatments are successful in the mid-long term, it is crucial to characterize SARS-CoV-2 mutations, as they might lead to viral resistance. Data from >5,700,000 SARS-CoV-2 genomes available at GISAID was used to report SARS-CoV-2 mutations. Given the pivotal role of its main protease (M-pro) in virus replication, a detailed analysis of SARS-CoV-2 M-pro mutations was conducted, with particular attention to mutation-resistant residues or mutation coldspots, defined as those residues that have mutated in five or fewer genomes. 32 mutation coldspots were identified, most of which mediate interprotomer interactions or funneling interaction networks from the substrate-binding site towards the dimerization surface and vice versa. Besides, mutation coldspots were virtually conserved in all main proteases from other CoVs. Our results provide valuable information about key residues to M-pro structure that could be useful in rational target-directed drug design and establish a solid groundwork based on mutation analyses for the inhibition of M-pro dimerization, with a potential applicability to future coronavirus outbreaks.

EvoAI enables extreme compression and reconstruction of the protein sequence space

Designing proteins with improved functions requires a deep understanding of how sequence and function are related, a vast space that is hard to explore. The ability to efficiently compress this space by identifying functionally important features is extremely valuable. Here we establish a method called EvoScan to comprehensively segment and scan the high-fitness sequence space to obtain anchor points that capture its essential features, especially in high dimensions. Our approach is compatible with any biomolecular function that can be coupled to a transcriptional output. We then develop deep learning and large language models to accurately reconstruct the space from these anchors, allowing computational prediction of novel, highly fit sequences without prior homology-derived or structural information. We apply this hybrid experimental-computational method, which we call EvoAI, to a repressor protein and find that only 82 anchors are sufficient to compress the high-fitness sequence space with a compression ratio of 1048. The extreme compressibility of the space informs both applied biomolecular design and understanding of natural evolution.

Large scale analysis of the SARS-CoV-2 main protease reveals marginal presence of nirmatrelvir-resistant SARS-CoV-2 Omicron mutants in Ontario, Canada, December 2021-September 2023

Background

In response to the COVID-19 pandemic, a new oral antiviral called nirmatrelvir-ritonavir (PaxlovidTM) was authorized for use in Canada in January 2022. In vitro studies have reported mutations in Mpro protein that may be associated with the development of nirmatrelvir resistance.

Objectives

To survey the prevalence, relevance and temporal patterns of Mpro mutations among SARS-CoV-2 Omicron lineages in Ontario, Canada.

Methods

A total of 93,082 Mpro gene sequences from December 2021 to September 2023 were analyzed. Reported in vitro Mpro mutations were screened against our database using in-house data science pipelines to determine the nirmatrelvir resistance. Negative binomial regression was conducted to analyze the temporal trends in Mpro mutation counts over the study time period.

Results

A declining trend was observed in non-synonymous mutations of Mpro sequences, showing a 7.9% reduction (95% CI: 6.5%-‬9.4%; p<0.001) every 30 days. The P132H was the most prevalent mutation (higher than 95%) in all Omicron lineages. In vitro nirmatrelvir-resistant mutations were found in 3.12% (n=29/929) Omicron lineages with very low counts, ranging from one to 19. Only two mutations, A7T (n=19) and M82I (n=9), showed temporal presence among the BA.1.1 in 2022 and the BQ.1.2.3 in 2022, respectively.

Conclusion

The observations suggest that, as of September 2023, no significant or widespread resistance to nirmatrelvir has developed among SARS-CoV-2 Omicron variants in Ontario. This study highlights the importance of creating automated monitoring systems to track the emergence of nirmatrelvir-resistant mutations within the SARS-CoV-2 virus, utilizing genomic data generated in real-time.

Drug susceptibility and the potential for drug-resistant SARS-CoV-2 emergence in immunocompromised animals

The reduced susceptibility of mRNA vaccines and diminished neutralizing activity of therapeutic monoclonal antibodies against Omicron variants, including BQ.1.1, XBB, and their descendants, highlight the importance of antiviral therapies. Here, we assessed the efficacy of two antivirals, molnupiravir, targeting a viral RNA-dependent RNA polymerase, and nirmatrelvir, targeting a main protease, against BQ.1.1 in hamsters. We found that prophylactic or therapeutic treatment with either drug significantly reduced the viral load in the lungs of infected hamsters. We also evaluated the risk of emergence of drug-resistant viruses in immunocompromised hamsters. Although 13 days of drug treatment reduced viral titers, the immunocompromised hosts could not completely clear the virus. Viruses isolated from drug-treated immunocompromised hamsters did not show reduced susceptibility to the drugs. Molnupiravir and nirmatrelvir remain effective in vivo against variants with reduced susceptibility to monoclonal antibodies and mRNA vaccine-induced antibodies, with limited emergence of drug-resistant variants under the conditions tested.

A comprehensive study of SARS-CoV-2 main protease (Mpro) inhibitor-resistant mutants selected in a VSV-based system

Nirmatrelvir was the first protease inhibitor specifically developed against the SARS-CoV-2 main protease (3CLpro/Mpro) and licensed for clinical use. As SARS-CoV-2 continues to spread, variants resistant to nirmatrelvir and other currently available treatments are likely to arise. This study aimed to identify and characterize mutations that confer resistance to nirmatrelvir. To safely generate Mpro resistance mutations, we passaged a previously developed, chimeric vesicular stomatitis virus (VSV-Mpro) with increasing, yet suboptimal concentrations of nirmatrelvir. Using Wuhan-1 and Omicron Mpro variants, we selected a large set of mutants. Some mutations are frequently present in GISAID, suggesting their relevance in SARS-CoV-2. The resistance phenotype of a subset of mutations was characterized against clinically available protease inhibitors (nirmatrelvir and ensitrelvir) with cell-based, biochemical and SARS-CoV-2 replicon assays. Moreover, we showed the putative molecular mechanism of resistance based on in silico molecular modelling. These findings have implications on the development of future generation Mpro inhibitors, will help to understand SARS-CoV-2 protease inhibitor resistance mechanisms and show the relevance of specific mutations, thereby informing treatment decisions.

Phylogenetic signatures reveal multilevel selection and fitness costs in SARS-CoV-2

Background

Large-scale sequencing of SARS-CoV-2 has enabled the study of viral evolution during the COVID-19 pandemic. Some viral mutations may be advantageous to viral replication within hosts but detrimental to transmission, thus carrying a transient fitness advantage. By affecting the number of descendants, persistence times and growth rates of associated clades, these mutations generate localised imbalance in phylogenies. Quantifying these features in closely-related clades with and without recurring mutations can elucidate the tradeoffs between within-host replication and between-host transmission.

Methods

We implemented a novel phylogenetic clustering algorithm ( mlscluster, https://github.com/mrc-ide/mlscluster) to systematically explore time-scaled phylogenies for mutations under transient/multilevel selection. We applied this method to a SARS-CoV-2 time-calibrated phylogeny with >1.2 million sequences from England, and characterised these recurrent mutations that may influence transmission fitness across PANGO-lineages and genomic regions using Poisson regressions and summary statistics.

Results

We found no major differences across two epidemic stages (before and after Omicron), PANGO-lineages, and genomic regions. However, spike, nucleocapsid, and ORF3a were proportionally more enriched for transmission fitness polymorphisms (TFP)-homoplasies than other proteins. We provide a catalog of SARS-CoV-2 sites under multilevel selection, which can guide experimental investigations within and beyond the spike protein.

Conclusions

This study provides empirical evidence for the existence of important tradeoffs between within-host replication and between-host transmission shaping the fitness landscape of SARS-CoV-2. This method may be used as a fast and scalable means to shortlist large sequence databases for sites under putative multilevel selection which may warrant subsequent confirmatory analyses and experimental confirmation.

Computational Insights into SARS-CoV-2 Main Protease Mutations and Nirmatrelvir Efficacy: The Effects of P132H and P132H-A173V

Nirmatrelvir, a pivotal component of the oral antiviral Paxlovid for COVID-19, targets the SARS-CoV-2 main protease (Mpro) as a covalent inhibitor. Here, we employed combined computational methods to explore how the prevalent Omicron variant mutation P132H, alone and in combination with A173V (P132H-A173V), affects nirmatrelvir's efficacy. Our findings suggest that P132H enhances the noncovalent binding affinity of Mpro for nirmatrelvir, whereas P132H-A173V diminishes it. Although both mutants catalyze the rate-limiting step more efficiently than the wild-type (WT) Mpro, P132H slows the overall rate of covalent bond formation, whereas P132H-A173V accelerates it. Comprehensive analysis of noncovalent and covalent contributions to the overall binding free energy of the covalent complex suggests that P132H likely enhances Mpro sensitivity to nirmatrelvir, while P132H-A173V may confer resistance. Per-residue decompositions of the binding and activation free energies pinpoint key residues that significantly affect the binding affinity and reaction rates, revealing how the mutations modulate these effects. The mutation-induced conformational perturbations alter drug-protein local contact intensities and the electrostatic preorganization of the protein, affecting noncovalent binding affinity and the stability of key reaction states, respectively. Our findings inform the mechanisms of nirmatrelvir resistance and sensitivity, facilitating improved drug design and the detection of resistant strains.

Study of key residues in MERS-CoV and SARS-CoV-2 main proteases for resistance against clinically applied inhibitors nirmatrelvir and ensitrelvir

The Middle East Respiratory Syndrome Coronavirus (MERS-CoV) is an epidemic, zoonotically emerging pathogen initially reported in Saudi Arabia in 2012. MERS-CoV has the potential to mutate or recombine with other coronaviruses, thus acquiring the ability to efficiently spread among humans and become pandemic. Its high mortality rate of up to 35% and the absence of effective targeted therapies call for the development of antiviral drugs for this pathogen. Since the beginning of the SARS-CoV-2 pandemic, extensive research has focused on identifying protease inhibitors for the treatment of SARS-CoV-2. Our intention was therefore to assess whether these protease inhibitors are viable options for combating MERS-CoV. To that end, we used previously established protease assays to quantify inhibition of SARS-CoV-2, MERS-CoV and other main proteases. Nirmatrelvir inhibited several of these proteases, whereas ensitrelvir was less broadly active. To simulate nirmatrelvir's clinical use against MERS-CoV and subsequent resistance development, we applied a safe, surrogate virus-based system. Using the surrogate virus, we previously selected hallmark mutations of SARS-CoV-2-Mpro, such as T21I, M49L, S144A, E166A/K/V and L167F. In the current study, we selected a pool of MERS-CoV-Mpro mutants, characterized the resistance and modelled the steric effect of catalytic site mutants S142G, S142R, S147Y and A171S.

SARS-CoV-2 resistance to monoclonal antibodies and small-molecule drugs

Over four years have passed since the beginning of the COVID-19 pandemic. The scientific response has been rapid and effective, with many therapeutic monoclonal antibodies and small molecules developed for clinical use. However, given the ability for viruses to become resistant to antivirals, it is perhaps no surprise that the field has identified resistance to nearly all of these compounds. Here, we provide a comprehensive review of the resistance profile for each of these therapeutics. We hope that this resource provides an atlas for mutations to be aware of for each agent, particularly as a springboard for considerations for the next generation of antivirals. Finally, we discuss the outlook and thoughts for moving forward in how we continue to manage this, and the next, pandemic.

Resistance mechanisms of SARS-CoV-2 3CLpro to the non-covalent inhibitor WU-04

Drug resistance poses a significant challenge in the development of effective therapies against SARS-CoV-2. Here, we identified two double mutations, M49K/M165V and M49K/S301P, in the 3C-like protease (3CLpro) that confer resistance to a novel non-covalent inhibitor, WU-04, which is currently in phase III clinical trials (NCT06197217). Crystallographic analysis indicates that the M49K mutation destabilizes the WU-04-binding pocket, impacting the binding of WU-04 more significantly than the binding of 3CLpro substrates. The M165V mutation directly interferes with WU-04 binding. The S301P mutation, which is far from the WU-04-binding pocket, indirectly affects WU-04 binding by restricting the rotation of 3CLpro's C-terminal tail and impeding 3CLpro dimerization. We further explored 3CLpro mutations that confer resistance to two clinically used inhibitors: ensitrelvir and nirmatrelvir, and revealed a trade-off between the catalytic activity, thermostability, and drug resistance of 3CLpro. We found that mutations at the same residue (M49) can have distinct effects on the 3CLpro inhibitors, highlighting the importance of developing multiple antiviral agents with different skeletons for fighting SARS-CoV-2. These findings enhance our understanding of SARS-CoV-2 resistance mechanisms and inform the development of effective therapeutics.

EvoAI enables extreme compression and reconstruction of the protein sequence space

Designing proteins with improved functions requires a deep understanding of how sequence and function are related, a vast space that is hard to explore. The ability to efficiently compress this space by identifying functionally important features is extremely valuable. Here, we first establish a method called EvoScan to comprehensively segment and scan the high-fitness sequence space to obtain anchor points that capture its essential features, especially in high dimensions. Our approach is compatible with any biomolecular function that can be coupled to a transcriptional output. We then develop deep learning and large language models to accurately reconstruct the space from these anchors, allowing computational prediction of novel, highly fit sequences without prior homology-derived or structural information. We apply this hybrid experimental-computational method, which we call EvoAI, to a repressor protein and find that only 82 anchors are sufficient to compress the high-fitness sequence space with a compression ratio of 1048. The extreme compressibility of the space informs both applied biomolecular design and understanding of natural evolution.

Sequence analysis of the Spike, RNA-dependent RNA polymerase, and protease genes reveals a distinct evolutionary pattern of SARS-CoV-2 variants circulating in Yogyakarta and Central Java provinces, Indonesia

During the Covid-19 pandemic, the resurgence of SARS-CoV-2 was due to the development of novel variants of concern (VOC). Thus, genomic surveillance is essential to monitor continuing evolution of SARS-CoV-2 and to track the emergence of novel variants. In this study, we performed phylogenetic, mutation, and selection pressure analyses of the Spike, nsp12, nsp3, and nsp5 genes of SARS-CoV-2 isolates circulating in Yogyakarta and Central Java provinces, Indonesia from May 2021 to February 2022. Various bioinformatics tools were employed to investigate the evolutionary dynamics of distinct SARS-CoV-2 isolates. During the study period, 213 and 139 isolates of Omicron and Delta variants were identified, respectively. Particularly in the Spike gene, mutations were significantly more abundant in Omicron than in Delta variants. Consistently, in all of four genes studied, the substitution rates of Omicron were higher than that of Delta variants, especially in the Spike and nsp12 genes. In addition, selective pressure analysis revealed several sites that were positively selected in particular genes, implying that these sites were functionally essential for virus evolution. In conclusion, our study demonstrated a distinct evolutionary pattern of SARS-CoV-2 variants circulating in Yogyakarta and Central Java provinces, Indonesia.

A comprehensive study of SARS-CoV-2 main protease (Mpro) inhibitor-resistant mutants selected in a VSV-based system

Nirmatrelvir was the first protease inhibitor (PI) specifically developed against the SARS-CoV-2 main protease (3CLpro/Mpro) and licensed for clinical use. As SARS-CoV-2 continues to spread, variants resistant to nirmatrelvir and other currently available treatments are likely to arise. This study aimed to identify and characterize mutations that confer resistance to nirmatrelvir. To safely generate Mpro resistance mutations, we passaged a previously developed, chimeric vesicular stomatitis virus (VSV-Mpro) with increasing, yet suboptimal concentrations of nirmatrelvir. Using Wuhan-1 and Omicron Mpro variants, we selected a large set of mutants. Some mutations are frequently present in GISAID, suggesting their relevance in SARS-CoV-2. The resistance phenotype of a subset of mutations was characterized against clinically available PIs (nirmatrelvir and ensitrelvir) with cell-based and biochemical assays. Moreover, we showed the putative molecular mechanism of resistance based on in silico molecular modelling. These findings have implications on the development of future generation Mpro inhibitors, will help to understand SARS-CoV-2 protease-inhibitor-resistance mechanisms and show the relevance of specific mutations in the clinic, thereby informing treatment decisions.

Fitness effects of mutations to SARS-CoV-2 proteins

Knowledge of the fitness effects of mutations to SARS-CoV-2 can inform assessment of new variants, design of therapeutics resistant to escape, and understanding of the functions of viral proteins. However, experimentally measuring effects of mutations is challenging: we lack tractable lab assays for many SARS-CoV-2 proteins, and comprehensive deep mutational scanning has been applied to only two SARS-CoV-2 proteins. Here, we develop an approach that leverages millions of publicly available SARS-CoV-2 sequences to estimate effects of mutations. We first calculate how many independent occurrences of each mutation are expected to be observed along the SARS-CoV-2 phylogeny in the absence of selection. We then compare these expected observations to the actual observations to estimate the effect of each mutation. These estimates correlate well with deep mutational scanning measurements. For most genes, synonymous mutations are nearly neutral, stop-codon mutations are deleterious, and amino acid mutations have a range of effects. However, some viral accessory proteins are under little to no selection. We provide interactive visualizations of effects of mutations to all SARS-CoV-2 proteins (https://jbloomlab.github.io/SARS2-mut-fitness/). The framework we describe is applicable to any virus for which the number of available sequences is sufficiently large that many independent occurrences of each neutral mutation are observed.

Bench-to-bedside: Innovation of small molecule anti-SARS-CoV-2 drugs in China

The ongoing COVID-19 pandemic has resulted in millions of deaths globally, highlighting the need to develop potent prophylactic and therapeutic strategies against SARS-CoV-2. Small molecule inhibitors (remdesivir, Paxlovid, and molnupiravir) are essential complements to vaccines and play important roles in clinical treatment of SARS-CoV-2. Many advances have been made in development of anti-SARS-CoV-2 inhibitors in China, but progress in discovery and characterization of pharmacological activity, antiviral mechanisms, and clinical efficacy are limited. We review development of small molecule anti-SARS-CoV-2 drugs (azvudine [approved by the NMPA of China on July 25, 2022], VV116 [approved by the NMPA of China on January 29, 2023], FB2001, WPV01, pentarlandir, and cepharanthine) in China and summarize their pharmacological activity, potential mechanisms of action, clinical trials and use, and important milestones in their discovery. The role of structural biology in drug development is also reviewed. Future studies should focus on development of diverse second-generation inhibitors with excellent oral bioavailability, superior plasma half-life, increased antiviral activity against SARS-CoV-2 and its variants, high target specificity, minimal side effects, reduced drug-drug interactions, and improved lung histopathology.

SARS-CoV-2 main protease cleaves MAGED2 to antagonize host antiviral defense

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the agent causing the global pandemic of COVID-19. SARS-CoV-2 genome encodes a main protease (nsp5, also called Mpro) and a papain-like protease (nsp3, also called PLpro), which are responsible for processing viral polyproteins to assemble a functional replicase complex. In this study, we found that Mpro of SARS-CoV-2 can cleave human MAGED2 and other mammalian orthologs at Gln-263. Moreover, SARS-CoV and MERS-CoV Mpro can also cleave human MAGED2, suggesting MAGED2 cleavage by Mpro is an evolutionarily conserved mechanism of coronavirus infection in mammals. Intriguingly, Mpro from Beta variant cleaves MAGED2 more efficiently than wild type, but Omicron Mpro is opposite. Further studies show that MAGED2 inhibits SARS-CoV-2 infection at viral replication step. Mechanistically, MAGED2 is associated with SARS-CoV-2 nucleocapsid protein through its N-terminal region in an RNA-dependent manner, and this disrupts the interaction between SARS-CoV-2 nucleocapsid protein and viral genome, thus inhibiting viral replication. When MAGED2 is cleaved by Mpro, the N-terminal of MAGED2 will translocate into the nucleus, and the truncated MAGED2 is unable to suppress SARS-CoV-2 replication. This work not only discovers the antiviral function of MAGED2 but also provides new insights into how SARS-CoV-2 Mpro antagonizes host antiviral response. IMPORTANCE Host factors that restrict severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection remain elusive. Here, we found that MAGED2 can be cleaved by SARS-CoV-2 main protease (Mpro) at Gln-263. SARS-CoV and MERS-CoV Mpro can also cleave MAGED2, and MAGED2 from multiple species can be cleaved by SARS-CoV-2 Mpro. Mpro from Beta variant cleaves MAGED2 more efficiently efficiently than wild type, but Omicron is the opposite. MAGED2 depletion enhances SARS-CoV-2 infection, suggesting its inhibitory role in SARS-CoV-2 infection. Mechanistically, MAGED2 restricts SARS-CoV-2 replication by disrupting the interaction between nucleocapsid and viral genomes. When MAGED2 is cleaved, its N-terminal will translocate into the nucleus. In this way, Mpro relieves MAGED2' inhibition on viral replication. This study improves our understanding of complex viral-host interaction and provides novel targets to treat SARS-CoV-2 infection.

A low-background, fluorescent assay to evaluate inhibitors of diverse viral proteases

Multiple coronaviruses (CoVs) can cause respiratory diseases in humans. While prophylactic vaccines designed to prevent infection are available for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), incomplete vaccine efficacy, vaccine hesitancy, and the threat of other pathogenic CoVs for which vaccines do not exist have highlighted the need for effective antiviral therapies. While antiviral compounds targeting the viral polymerase and protease are already in clinical use, their sensitivity to potential resistance mutations as well as their breadth against the full range of human and preemergent CoVs remain incompletely defined. To begin to fill that gap in knowledge, we report here the development of an improved, noninfectious, cell-based fluorescent assay with high sensitivity and low background that reports on the activity of viral proteases, which are key drug targets. We demonstrate that the assay is compatible with not only the SARS-CoV-2 Mpro protein but also orthologues from a range of human and nonhuman CoVs as well as clinically reported SARS-CoV-2 drug-resistant Mpro variants. We then use this assay to define the breadth of activity of two clinically used protease inhibitors, nirmatrelvir and ensitrelvir. Continued use of this assay will help define the strengths and limitations of current therapies and may also facilitate the development of next-generation protease inhibitors that are broadly active against both currently circulating and preemergent CoVs. IMPORTANCE Coronaviruses (CoVs) are important human pathogens with the ability to cause global pandemics. Working in concert with vaccines, antivirals specifically limit viral disease in people who are actively infected. Antiviral compounds that target CoV proteases are already in clinical use; their efficacy against variant proteases and preemergent zoonotic CoVs, however, remains incompletely defined. Here, we report an improved, noninfectious, and highly sensitive fluorescent method of defining the sensitivity of CoV proteases to small molecule inhibitors. We use this approach to assay the activity of current antiviral therapies against clinically reported SARS-CoV-2 protease mutants and a panel of highly diverse CoV proteases. Additionally, we show this system is adaptable to other structurally nonrelated viral proteases. In the future, this assay can be used to not only better define the strengths and limitations of current therapies but also help develop new, broadly acting inhibitors that more broadly target viral families.

Naturally Occurring Mutations of SARS-CoV-2 Main Protease Confer Drug Resistance to Nirmatrelvir

The SARS-CoV-2 main protease (Mpro) is the drug target of Pfizer's oral drug nirmatrelvir. The emergence of SARS-CoV-2 variants with mutations in Mpro raised the alarm of potential drug resistance. To identify potential clinically relevant drug-resistant mutants, we systematically characterized 102 naturally occurring Mpro mutants located at 12 residues at the nirmatrelvir-binding site, among which 22 mutations in 5 residues, including S144M/F/A/G/Y, M165T, E166 V/G/A, H172Q/F, and Q192T/S/L/A/I/P/H/V/W/C/F, showed comparable enzymatic activity to the wild-type (kcat/Km < 10-fold change) while being resistant to nirmatrelvir (Ki > 10-fold increase). X-ray crystal structures were determined for six representative mutants with and/or without GC-376/nirmatrelvir. Using recombinant SARS-CoV-2 viruses generated from reverse genetics, we confirmed the drug resistance in the antiviral assay and showed that Mpro mutants with reduced enzymatic activity had attenuated viral replication. Overall, our study identified several drug-resistant hotspots in Mpro that warrant close monitoring for possible clinical evidence of nirmatrelvir resistance, some of which have already emerged in independent viral passage assays conducted by others.

A yeast-based system to study SARS-CoV-2 Mpro structure and to identify nirmatrelvir resistant mutations

The SARS-CoV-2 main protease (Mpro) is a major therapeutic target. The Mpro inhibitor, nirmatrelvir, is the antiviral component of Paxlovid, an orally available treatment for COVID-19. As Mpro inhibitor use increases, drug resistant mutations will likely emerge. We have established a non-pathogenic system, in which yeast growth serves as an approximation for Mpro activity, enabling rapid identification of mutants with altered enzymatic activity and drug sensitivity. The E166 residue is known to be a potential hot spot for drug resistance and yeast assays identified substitutions which conferred strong nirmatrelvir resistance and others that compromised activity. On the other hand, N142A and the P132H mutation, carried by the Omicron variant, caused little to no change in drug response and activity. Standard enzymatic assays confirmed the yeast results. In turn, we solved the structures of Mpro E166R, and Mpro E166N, providing insights into how arginine may drive drug resistance while asparagine leads to reduced activity. The work presented here will help characterize novel resistant variants of Mpro that may arise as Mpro antivirals become more widely used.

In vitro and in vivo characterization of SARS-CoV-2 resistance to ensitrelvir

Ensitrelvir, an oral antiviral agent that targets a SARS-CoV-2 main protease (3CLpro or Nsp5), is clinically useful against SARS-CoV-2 including its omicron variants. Since most omicron subvariants have reduced sensitivity to most monoclonal antibody therapies, SARS-CoV-2 resistance to other antivirals including main protease inhibitors such as ensitrelvir is a major public health concern. Here, repeating passages of SARS-CoV-2 in the presence of ensitrelvir revealed that the M49L and E166A substitutions in Nsp5 are responsible for reduced sensitivity to ensitrelvir. Both substitutions reduced in vitro virus growth in the absence of ensitrelvir. The combination of the M49L and E166A substitutions allowed the virus to largely evade the suppressive effect of ensitrelvir in vitro. The virus possessing Nsp5-M49L showed similar pathogenicity to wild-type virus, whereas the virus possessing Nsp5-E166A or Nsp5-M49L/E166A slightly attenuated. Ensitrelvir treatment of hamsters infected with the virus possessing Nsp5-M49L/E166A was ineffective; however, nirmatrelvir or molnupiravir treatment was effective. Therefore, it is important to closely monitor the emergence of ensitrelvir-resistant SARS-CoV-2 variants to guide antiviral treatment selection.

In vitro and in vivo characterization of SARS-CoV-2 strains resistant to nirmatrelvir

Nirmatrelvir, an oral antiviral agent that targets a SARS-CoV-2 main protease (3CLpro), is clinically useful against infection with SARS-CoV-2 including its omicron variants. Since most omicron subvariants have reduced sensitivity to many monoclonal antibody therapies, potential SARS-CoV-2 resistance to nirmatrelvir is a major public health concern. Several amino acid substitutions have been identified as being responsible for reduced susceptibility to nirmatrelvir. Among them, we selected L50F/E166V and L50F/E166A/L167F in the 3CLpro because these combinations of substitutions are unlikely to affect virus fitness. We prepared and characterized delta variants possessing Nsp5-L50F/E166V and Nsp5-L50F/E166A/L167F. Both mutant viruses showed decreased susceptibility to nirmatrelvir and their growth in VeroE6/TMPRSS2 cells was delayed. Both mutant viruses showed attenuated phenotypes in a male hamster infection model, maintained airborne transmissibility, and were outcompeted by wild-type virus in co-infection experiments in the absence of nirmatrelvir, but less so in the presence of the drug. These results suggest that viruses possessing Nsp5-L50F/E166V and Nsp5-L50F/E166A/L167F do not become dominant in nature. However, it is important to closely monitor the emergence of nirmatrelvir-resistant SARS-CoV-2 variants because resistant viruses with additional compensatory mutations could emerge, outcompete the wild-type virus, and become dominant.

Fitness effects of mutations to SARS-CoV-2 proteins

Knowledge of the fitness effects of mutations to SARS-CoV-2 can inform assessment of new variants, design of therapeutics resistant to escape, and understanding of the functions of viral proteins. However, experimentally measuring effects of mutations is challenging: we lack tractable lab assays for many SARS-CoV-2 proteins, and comprehensive deep mutational scanning has been applied to only two SARS-CoV-2 proteins. Here we develop an approach that leverages millions of publicly available SARS-CoV-2 sequences to estimate effects of mutations. We first calculate how many independent occurrences of each mutation are expected to be observed along the SARS-CoV-2 phylogeny in the absence of selection. We then compare these expected observations to the actual observations to estimate the effect of each mutation. These estimates correlate well with deep mutational scanning measurements. For most genes, synonymous mutations are nearly neutral, stop-codon mutations are deleterious, and amino-acid mutations have a range of effects. However, some viral accessory proteins are under little to no selection. We provide interactive visualizations of effects of mutations to all SARS-CoV-2 proteins (https://jbloomlab.github.io/SARS2-mut-fitness/). The framework we describe is applicable to any virus for which the number of available sequences is sufficiently large that many independent occurrences of each neutral mutation are observed.

Global prevalence of SARS-CoV-2 3CL protease mutations associated with nirmatrelvir or ensitrelvir resistance

BACKGROUND

Nirmatrelvir-ritonavir (Paxlovid) and ensitrelvir are 3-chymotrypsin-like cysteine protease (3CLpro) inhibitors which have been approved for the treatment of COVID-19 in 2021 and 2022, respectively. Previous studies have identified 3CLpro mutations that are associated with reduced susceptibility to these antivirals. The aim of the current study was to estimate the global prevalence of 3CLpro inhibitor-resistant SARS-CoV-2 strains.

METHODS

We compiled a list of 3CLpro mutations which have been associated with nirmatrelvir or ensitrelvir resistance based on either viral replication or 3CLpro activity assays, and determined their prevalence among 13.4 million sequences deposited in GISAID as of December 14, 2022, about 1 year after the approval of nirmatrelvir-ritonavir. We analyzed the prevalence for different time periods, SARS-CoV-2 lineages and geographical locations.

FINDINGS

Overall, 0.5% (67,095/13,446,588) of the sequences contained at least one mutation that was shown to affect the inhibitory activity of nirmatrelvir or ensitrelvir on viral replication or 3CLpro activity. We did not observe any increasing trend of resistance after the widespread clinical use of nirmatrelvir-ritonavir. G15S (2070 per million) and T21I (1386 per million) were the most prevalent mutations, and these mutations were dominant in some SARS-CoV-2 lineages. E166V and S144E, previously shown to affect the inhibitory activity of nirmatrelvir on viral replication or protease activity by > 100-folds, were found in <1 per million sequences.

INTERPRETATION

Our data suggest that 3CLpro inhibitor resistance is currently rare. However, continuous global genotypic and phenotypic surveillance would be crucial in the early detection of resistant mutants.

FUNDING

Richard and Carol Yu, May Tam Mak Mei Yin, The Shaw Foundation Hong Kong, Michael Tong, Marina Lee, Government Consultancy Service, the Emergency Key Program of Guangzhou Laboratory (See acknowledgements for full list).

Rapid resistance profiling of SARS-CoV-2 protease inhibitors

Resistance to nirmatrelvir (Paxlovid) has been shown by multiple groups and may already exist in clinical SARS-CoV-2 isolates. Here a panel of SARS-CoV-2 main protease (Mpro) variants and a robust cell-based assay are used to compare the resistance profiles of nirmatrelvir, ensitrelvir, and FB2001. The results reveal distinct resistance mechanisms ("fingerprints") and indicate that these next-generation drugs have the potential to be effective against nirmatrelvir-resistant variants and vice versa.

Structural basis of nirmatrelvir and ensitrelvir activity against naturally occurring polymorphisms of the SARS-CoV-2 main protease

SARS-CoV-2 is the causative agent of COVID-19. The main viral protease (Mpro) is an attractive target for antivirals. The clinically approved drug nirmatrelvir and the clinical candidate ensitrelvir have so far showed great potential for treatment of viral infection. However, the broad use of antivirals is often associated with resistance generation. Herein, we enzymatically characterized 14 naturally occurring Mpro polymorphisms that are close to the binding site of these antivirals. Nirmatrelvir retained its potency against most polymorphisms tested, while mutants G143S and Q189K were associated with diminished inhibition constants. For ensitrelvir, diminished inhibition constants were observed for polymorphisms M49I, G143S, and R188S, but not for Q189K, suggesting a distinct resistance profile between inhibitors. In addition, the crystal structures of selected polymorphisms revealed interactions that were critical for loss of potency. In conclusion, our data will assist the monitoring of potential resistant strains, support the design of combined therapy, as well as assist the development of the next generation of Mpro inhibitors.

Rapid resistance profiling of SARS-CoV-2 protease inhibitors

Resistance to nirmatrelvir (Paxlovid) has been shown by multiple groups and may already exist in clinical SARS-CoV-2 isolates. Here a panel of SARS-CoV-2 main protease (Mpro) variants and a robust cell-based assay are used to compare the resistance profiles of nirmatrelvir, ensitrelvir, and FB2001. The results reveal distinct resistance mechanisms ("fingerprints") and indicate that these next-generation drugs have the potential to be effective against nirmatrelvir-resistant variants and vice versa.

Nirmatrelvir and COVID-19: development, pharmacokinetics, clinical efficacy, resistance, relapse, and pharmacoeconomics

Nirmatrelvir/ritonavir (N/R) is one of the most effective antiviral drugs against SARS-CoV-2. The preclinical development, pharmacodynamics and pharmacokinetics of N/R are reviewed herein. Randomized clinical trials have been conducted exclusively with pre-Omicron variants of concern, but in vitro studies show that efficacy against all Omicron sublineages is preserved, as confirmed by post-marketing observational studies. Nevertheless, investigations of large viral genome repositories have shown that mutation in the main protease causing resistance to N/R are increasingly frequent. In addition, virological and clinical rebounds after N/R discontinuation have been reported in immunocompetent patients. This finding is of concern when translated to immunocompromised patients, in whom N/R efficacy has not been formally investigated in clinical trials. Economical sustainability and perspectives for this therapeutic arena are discussed.

Natural Flavonoid Derivatives Have Pan-Coronavirus Antiviral Activity

The SARS-CoV-2 protease (3CLpro) is one of the key targets for the development of efficacious drugs for COVID-19 treatment due to its essential role in the life cycle of the virus and exhibits high conservation among coronaviruses. Recent studies have shown that flavonoids, which are small natural molecules, have antiviral activity against coronaviruses (CoVs), including SARS-CoV-2. In this study, we identified the docking sites and binding affinity of several natural compounds, similar to flavonoids, and investigated their inhibitory activity towards 3CLpro enzymatic activity. The selected compounds were then tested in vitro for their cytotoxicity, for antiviral activity against SARS-CoV-2, and the replication of other coronaviruses in different cell lines. Our results showed that Baicalein (100 μg/mL) exerted strong 3CLpro activity inhibition (>90%), whereas Hispidulin and Morin displayed partial inhibition. Moreover, Baicalein, up to 25 μg/mL, hindered >50% of SARS-CoV-2 replication in Vero E6 cultures. Lastly, Baicalein displayed antiviral activity against alphacoronavirus (Feline-CoV) and betacoronavirus (Bovine-CoV and HCoV-OC43) in the cell lines. Our study confirmed the antiviral activity of Baicalein against SARS-CoV-2 and demonstrated clear evidence of its pan-coronaviral activity.

Multiple pathways for SARS-CoV-2 resistance to nirmatrelvir

Nirmatrelvir, an oral antiviral targeting the 3CL protease of SARS-CoV-2, has been demonstrated to be clinically useful against COVID-19 (refs. 1,2). However, because SARS-CoV-2 has evolved to become resistant to other therapeutic modalities3-9, there is a concern that the same could occur for nirmatrelvir. Here we examined this possibility by in vitro passaging of SARS-CoV-2 in nirmatrelvir using two independent approaches, including one on a large scale. Indeed, highly resistant viruses emerged from both and their sequences showed a multitude of 3CL protease mutations. In the experiment peformed with many replicates, 53 independent viral lineages were selected with mutations observed at 23 different residues of the enzyme. Nevertheless, several common mutational pathways to nirmatrelvir resistance were preferred, with a majority of the viruses descending from T21I, P252L or T304I as precursor mutations. Construction and analysis of 13 recombinant SARS-CoV-2 clones showed that these mutations mediated only low-level resistance, whereas greater resistance required accumulation of additional mutations. E166V mutation conferred the strongest resistance (around 100-fold), but this mutation resulted in a loss of viral replicative fitness that was restored by compensatory changes such as L50F and T21I. Our findings indicate that SARS-CoV-2 resistance to nirmatrelvir does readily arise via multiple pathways in vitro, and the specific mutations observed herein form a strong foundation from which to study the mechanism of resistance in detail and to inform the design of next-generation protease inhibitors.

Sierra SARS-CoV-2 sequence and antiviral resistance analysis program

INTRODUCTION

Although most laboratories are capable of employing established protocols to perform full-genome SARS-CoV-2 sequencing, many are unable to assess sequence quality, select appropriate mutation-detection thresholds, or report on the potential clinical significance of mutations in the targets of antiviral therapy METHODS: We describe the technical aspects and benchmark the performance of Sierra SARS-CoV-2, a program designed to perform these functions on user-submitted FASTQ and FASTA sequence files and lists of Spike mutations. Sierra SARS-CoV-2 indicates which sequences contain an unexpectedly large number of unusual mutations and which mutations are associated with reduced susceptibility to clinical stage mAbs, the RdRP inhibitor remdesivir, or the Mpro inhibitor nirmatrelvir RESULTS: To assess the performance of Sierra SARS-CoV-2 on FASTQ files, we applied it to 600 representative FASTQ sequences and compared the results to the COVID-19 EDGE program. To assess its performance on FASTA files, we applied it to nearly one million representative FASTA sequences and compared the results to the GISAID mutation annotation. To assess its performance on mutations lists, we applied it to 13,578 distinct Spike RBD mutation patterns and showed that exactly or partially matching annotations were available for 88% of patterns CONCLUSION: Sierra SARS-CoV-2 leverages previously published data to improve the quality control of submitted viral genomic data and to provide functional annotation on the impact of mutations in the targets of antiviral SARS-CoV-2 therapy. The program can be found at https://covdb.stanford.edu/sierra/sars2/ and its source code at https://github.com/hivdb/sierra-sars2.