Comprehensive fitness landscape of SARS-CoV-2 Mpro reveals insights into viral resistance mechanisms

3-chymotrypsin-like protease in SARS-CoV-2

Coronaviruses constitute a significant threat to the human population. Severe acute respiratory syndrome coronavirus-2, SARS-CoV-2, is a highly pathogenic human coronavirus that has caused the coronavirus disease 2019 (COVID-19) pandemic. It has led to a global viral outbreak with an exceptional spread and a high death toll, highlighting the need for effective antiviral strategies. 3-Chymotrypsin-like protease (3CLpro), the main protease in SARS-CoV-2, plays an indispensable role in the SARS-CoV-2 viral life cycle by cleaving the viral polyprotein to produce 11 individual non-structural proteins necessary for viral replication. 3CLpro is one of two proteases that function to produce new viral particles. It is a highly conserved cysteine protease with identical structural folds in all known human coronaviruses. Inhibitors binding with high affinity to 3CLpro will prevent the cleavage of viral polyproteins, thus impeding viral replication. Multiple strategies have been implemented to screen for inhibitors against 3CLpro, including peptide-like and small molecule inhibitors that covalently and non-covalently bind the active site, respectively. In addition, allosteric sites of 3CLpro have been identified to screen for small molecules that could make non-competitive inhibitors of 3CLpro. In essence, this review serves as a comprehensive guide to understanding the structural intricacies and functional dynamics of 3CLpro, emphasizing key findings that elucidate its role as the main protease of SARS-CoV-2. Notably, the review is a critical resource in recognizing the advancements in identifying and developing 3CLpro inhibitors as effective antiviral strategies against COVID-19, some of which are already approved for clinical use in COVID-19 patients.

Selective and non-selective evolutionary signatures found in the simplest replicative biological entities

Mitoviruses, which are considered evolutionary relics of extinct alpha-proteobacteria RNA phages, represent one of the simplest self-replicating biological systems. This study aims to quantitatively describe genomes and identify potential genomic signatures that support the protein phylogenetic-based classification criterion. Genomic variables, such as mononucleotide and dinucleotide composition, codon usage bias, and minimal free energy derived from optimized predicted RNA secondary structure, were analyzed. From the values obtained, the main evolutionary pressures were discussed, indicating that natural selection plays a significant role in shaping mitovirus genomes. However, neutral evolution also makes a significant contribution. This study reveals a significant discovery of structural divergence in Kvaramitovirus. The energy minimization approach employed to study 2D folding in this study reveals a distinct spatial organization of their genomes, providing evidence for the hypothesis of a single evolutionary event of circularization in the most recent common ancestor of the lineage. This hypothesis was discussed in light of recent discoveries by other researchers that partially support the existence of mitoviruses with circular genomes. Finally, this study represents a significant advancement in the understanding of mitoviruses, as it quantitatively describes the nucleotide sequence at the family and genus taxonomic levels. Additionally, we provide hypotheses that can be experimentally validated to inspire new research and address the gaps in knowledge of this fascinating, basally divergent RNA virus lineage.

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.

Mutational profiling of SARS-CoV-2 papain-like protease reveals requirements for function, structure, and drug escape

Papain-like protease (PLpro) is an attractive drug target for SARS-CoV-2 because it is essential for viral replication, cleaving viral poly-proteins pp1a and pp1ab, and has de-ubiquitylation and de-ISGylation activities, affecting innate immune responses. We employ Deep Mutational Scanning to evaluate the mutational effects on PLpro enzymatic activity and protein stability in mammalian cells. We confirm features of the active site and identify mutations in neighboring residues that alter activity. We characterize residues responsible for substrate binding and demonstrate that although residues in the blocking loop are remarkably tolerant to mutation, blocking loop flexibility is important for function. We additionally find a connected network of mutations affecting activity that extends far from the active site. We leverage our library to identify drug-escape variants to a common PLpro inhibitor scaffold and predict that plasticity in both the S4 pocket and blocking loop sequence should be considered during the drug design process.

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.

Kinetic comparison of all eleven viral polyprotein cleavage site processing events by SARS-CoV-2 main protease using a linked protein FRET platform

The main protease (Mpro) remains an essential therapeutic target for COVID-19 post infection intervention given its critical role in processing the majority of viral proteins encoded by the genome of severe acute respiratory syndrome related coronavirus 2 (SARS-CoV-2). Upon viral entry, the +ssRNA genome is translated into two long polyproteins (pp1a or the frameshift-dependent pp1ab) containing all the nonstructural proteins (nsps) required by the virus for immune modulation, replication, and ultimately, virion assembly. Included among these nsps is the cysteine protease Mpro (nsp5) which self-excises from the polyprotein, dimerizes, then sequentially cleaves 11 of the 15 cut-site junctions found between each nsp within the polyprotein. Many structures of Mpro (often bound to various small molecule inhibitors or peptides) have been detailed recently, including structures of Mpro bound to each of the polyprotein cleavage sequences, showing that Mpro can accommodate a wide range of targets within its active site. However, to date, kinetic characterization of the interaction of Mpro with each of its native cleavage sequences remains incomplete. Here, we present a robust and cost-effective FRET based system that benefits from a more consistent presentation of the substrate that is also closer in organization to the native polyprotein environment compared to previously reported FRET systems that use chemically modified peptides. Using this system, we were able to show that while each site maintains a similar Michaelis constant, the catalytic efficiency of Mpro varies greatly between cut-site sequences, suggesting a clear preference for the order of nsp processing.

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.

Rugged fitness landscapes minimize promiscuity in the evolution of transcriptional repressors

How a protein's function influences the shape of its fitness landscape, smooth or rugged, is a fundamental question in evolutionary biochemistry. Smooth landscapes arise when incremental mutational steps lead to a progressive change in function, as commonly seen in enzymes and binding proteins. On the other hand, rugged landscapes are poorly understood because of the inherent unpredictability of how sequence changes affect function. Here, we experimentally characterize the entire sequence phylogeny, comprising 1,158 extant and ancestral sequences, of the DNA-binding domain (DBD) of the LacI/GalR transcriptional repressor family. Our analysis revealed an extremely rugged landscape with rapid switching of specificity, even between adjacent nodes. Further, the ruggedness arises due to the necessity of the repressor to simultaneously evolve specificity for asymmetric operators and disfavors potentially adverse regulatory crosstalk. Our study provides fundamental insight into evolutionary, molecular, and biophysical rules of genetic regulation through the lens of fitness landscapes.

Contributions of Hyperactive Mutations in Mpro from SARS-CoV-2 to Drug Resistance

The appearance and spread of mutations that cause drug resistance in rapidly evolving diseases, including infections by the SARS-CoV-2 virus, are major concerns for human health. Many drugs target enzymes, and resistance-conferring mutations impact inhibitor binding or enzyme activity. Nirmatrelvir, the most widely used inhibitor currently used to treat SARS-CoV-2 infections, targets the main protease (Mpro) preventing it from processing the viral polyprotein into active subunits. Our previous work systematically analyzed resistance mutations in Mpro that reduce binding to inhibitors; here, we investigate mutations that affect enzyme function. Hyperactive mutations that increase Mpro activity can contribute to drug resistance but have not been thoroughly studied. To explore how hyperactive mutations contribute to resistance, we comprehensively assessed how all possible individual mutations in Mpro affect enzyme function using a mutational scanning approach with a fluorescence resonance energy transfer (FRET)-based yeast readout. We identified hundreds of mutations that significantly increased the Mpro activity. Hyperactive mutations occurred both proximal and distal to the active site, consistent with protein stability and/or dynamics impacting activity. Hyperactive mutations were observed 3 times more than mutations which reduced apparent binding to nirmatrelvir in recent studies of laboratory-grown viruses selected for drug resistance. Hyperactive mutations were also about three times more prevalent than nirmatrelvir binding mutations in sequenced isolates from circulating SARS-CoV-2. Our findings indicate that hyperactive mutations are likely to contribute to the natural evolution of drug resistance in Mpro and provide a comprehensive list for future surveillance efforts.

An orally bioavailable SARS-CoV-2 main protease inhibitor exhibits improved affinity and reduced sensitivity to mutations

Inhibitors of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (Mpro) such as nirmatrelvir (NTV) and ensitrelvir (ETV) have proven effective in reducing the severity of COVID-19, but the presence of resistance-conferring mutations in sequenced viral genomes raises concerns about future drug resistance. Second-generation oral drugs that retain function against these mutants are thus urgently needed. We hypothesized that the covalent hepatitis C virus protease inhibitor boceprevir (BPV) could serve as the basis for orally bioavailable drugs that inhibit SARS-CoV-2 Mpro more efficiently than existing drugs. Performing structure-guided modifications of BPV, we developed a picomolar-affinity inhibitor, ML2006a4, with antiviral activity, oral pharmacokinetics, and therapeutic efficacy similar or superior to those of NTV. A crucial feature of ML2006a4 is a derivatization of the ketoamide reactive group that improves cell permeability and oral bioavailability. Last, ML2006a4 was found to be less sensitive to several mutations that cause resistance to NTV or ETV and occur in the natural SARS-CoV-2 population. Thus, anticipatory design can preemptively address potential resistance mechanisms to expand future treatment options against coronavirus variants.

On Inactivation of the Coronavirus Main Protease

A deeper understanding of the inactive conformations of the coronavirus main protease (MPro) could inform the design of allosteric drugs. Based on extensive molecular dynamics simulations, we built a Markov State Model to investigate structural changes that can inactivate the SARS-CoV-2 MPro. In a subset of structures, one subunit of the homodimer assumes an inactive conformation that resembles an inactive crystal structure. However, contradicting the widely held half-of-sites activity hypothesis, the most populated enzyme structures have two active subunits. We then used transition path theory (TPT) and the Jensen-Shannon Divergence (JSD) to pinpoint residues involved in the inactivation process. A π stack between Phe140 and His163 is a key feature that can distinguish active and inactive conformations of MPro. Each subunit has unique inactive conformations stabilized by π stacking interactions involving residues Phe140, Tyr118, His163, and His172, a hydrogen bonding network centered around His163 and His172, and a modified network of interactions in the dimer interface. The importance of these residues in maintaining an active structure explains the sensitivity of enzymatic activity to site-directed mutagenesis.

MD simulations indicate Omicron P132H of SARS-CoV-2 Mpro is a potential allosteric mutant involved in modulating the dynamics of catalytic site entry loop

The SARS-CoV-2 main protease Mpro, essential for viral replication is an important drug target. It plays a critical role in processing viral polyproteins necessary for viral replication assembly. One of the predominant SARS-CoV-2 Mpro mutations of Omicron variant is Pro132His. Structurally, this mutation site is located ∼22 Å away from the catalytic site. The solved crystal structure of this mutant in complex with inhibitors as well as its reported catalytic efficiency did not show any difference with respect to the wild type. Thus, the mutation was concluded to be non-allosteric. Based on microsecond long MD simulation of the Pro132His mutant and wild type, we show that Pro132His mutation affects the conformational equilibrium with more population of conformational substates having open catalytic site, modulated by the dynamics of the catalytic site entry loop, implying the allosteric nature of this mutation. The structural analysis indicates that rearrangement of hydrogen bonds between His132 and adjacent residues enhances the dynamics of the linker, which in turn is augmented by the inherent dynamic flexibility of the catalytic pocket entry site due to the presence of charged residues. The altered dynamics leading to loss of secondary structures corroborate well with the reported compromised thermal stability.

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.

Leveraging SARS-CoV-2 Main Protease (Mpro) for COVID-19 Mitigation with Selenium-Based Inhibitors

The implementation of innovative approaches is crucial in an ongoing endeavor to mitigate the impact of COVID-19 pandemic. The present study examines the strategic application of the SARS-CoV-2 Main Protease (Mpro) as a prospective instrument in the repertoire to combat the virus. The cloning, expression, and purification of Mpro, which plays a critical role in the viral life cycle, through heterologous expression in Escherichia coli in a completely soluble form produced an active enzyme. The hydrolysis of a specific substrate peptide comprising a six-amino-acid sequence (TSAVLQ) linked to a p-nitroaniline (pNA) fragment together with the use of a fluorogenic substrate allowed us to determine effective inhibitors incorporating selenium moieties, such as benzoselenoates and carbamoselenoates. The new inhibitors revealed their potential to proficiently inhibit Mpro with IC50-s in the low micromolar range. Our study contributes to the development of a new class of protease inhibitors targeting Mpro, ultimately strengthening the antiviral arsenal against COVID-19 and possibly, related coronaviruses.

Medicinal chemistry strategies towards the development of non-covalent SARS-CoV-2 Mpro inhibitors

The main protease (Mpro) of SARS-CoV-2 is an attractive target in anti-COVID-19 therapy for its high conservation and major role in the virus life cycle. The covalent Mpro inhibitor nirmatrelvir (in combination with ritonavir, a pharmacokinetic enhancer) and the non-covalent inhibitor ensitrelvir have shown efficacy in clinical trials and have been approved for therapeutic use. Effective antiviral drugs are needed to fight the pandemic, while non-covalent Mpro inhibitors could be promising alternatives due to their high selectivity and favorable druggability. Numerous non-covalent Mpro inhibitors with desirable properties have been developed based on available crystal structures of Mpro. In this article, we describe medicinal chemistry strategies applied for the discovery and optimization of non-covalent Mpro inhibitors, followed by a general overview and critical analysis of the available information. Prospective viewpoints and insights into current strategies for the development of non-covalent Mpro inhibitors are also discussed.

Discovery of Nirmatrelvir Resistance Mutations in SARS-CoV-2 3CLpro: A Computational-Experimental Approach

The COVID-19 pandemic has emphasized the urgency for effective antiviral therapies against SARS-CoV-2. Targeting the main protease (3CLpro) of the virus has emerged as a promising approach, and nirmatrelvir (PF-07321332), the active component of Pfizer's oral drug Paxlovid, has demonstrated remarkable clinical efficacy. However, the emergence of resistance mutations poses a challenge to its continued success. In this study, we employed alchemical free energy perturbation (FEP) alanine scanning to identify nirmatrelvir-resistance mutations within SARS-CoV-2 3CLpro. FEP identified several mutations, which were validated through in vitro IC50 experiments and found to result in 8- and 72-fold increases in nirmatrelvir IC50 values. Additionally, we constructed SARS-CoV-2 omicron replicons containing these mutations, and one of the mutants (S144A/E166A) displayed a 20-fold increase in EC50, confirming the role of FEP in identifying drug-resistance mutations. Our findings suggest that FEP can be a valuable tool in proactively monitoring the emergence of resistant strains and guiding the design of future inhibitors with reduced susceptibility to drug resistance. As nirmatrelvir is currently widely used for treating COVID-19, this research has important implications for surveillance efforts and antiviral development.

A Simulation Framework for Modeling the Within-Patient Evolutionary Dynamics of SARS-CoV-2

The global impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to considerable interest in detecting novel beneficial mutations and other genomic changes that may signal the development of variants of concern (VOCs). The ability to accurately detect these changes within individual patient samples is important in enabling early detection of VOCs. Such genomic scans for rarely acting positive selection are best performed via comparison of empirical data with simulated data wherein commonly acting evolutionary factors, including mutation and recombination, reproductive and infection dynamics, and purifying and background selection, can be carefully accounted for and parameterized. Although there has been work to quantify these factors in SARS-CoV-2, they have yet to be integrated into a baseline model describing intrahost evolutionary dynamics. To construct such a baseline model, we develop a simulation framework that enables one to establish expectations for underlying levels and patterns of patient-level variation. By varying eight key parameters, we evaluated 12,096 different model-parameter combinations and compared them with existing empirical data. Of these, 592 models (∼5%) were plausible based on the resulting mean expected number of segregating variants. These plausible models shared several commonalities shedding light on intrahost SARS-CoV-2 evolutionary dynamics: severe infection bottlenecks, low levels of reproductive skew, and a distribution of fitness effects skewed toward strongly deleterious mutations. We also describe important areas of model uncertainty and highlight additional sequence data that may help to further refine a baseline model. This study lays the groundwork for the improved analysis of existing and future SARS-CoV-2 within-patient data.

Learning from prepandemic data to forecast viral escape

Effective pandemic preparedness relies on anticipating viral mutations that are able to evade host immune responses to facilitate vaccine and therapeutic design. However, current strategies for viral evolution prediction are not available early in a pandemic-experimental approaches require host polyclonal antibodies to test against1-16, and existing computational methods draw heavily from current strain prevalence to make reliable predictions of variants of concern17-19. To address this, we developed EVEscape, a generalizable modular framework that combines fitness predictions from a deep learning model of historical sequences with biophysical and structural information. EVEscape quantifies the viral escape potential of mutations at scale and has the advantage of being applicable before surveillance sequencing, experimental scans or three-dimensional structures of antibody complexes are available. We demonstrate that EVEscape, trained on sequences available before 2020, is as accurate as high-throughput experimental scans at anticipating pandemic variation for SARS-CoV-2 and is generalizable to other viruses including influenza, HIV and understudied viruses with pandemic potential such as Lassa and Nipah. We provide continually revised escape scores for all current strains of SARS-CoV-2 and predict probable further mutations to forecast emerging strains as a tool for continuing vaccine development ( evescape.org ).

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.

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.

Large library docking for novel SARS-CoV-2 main protease non-covalent and covalent inhibitors

Antiviral therapeutics to treat SARS-CoV-2 are needed to diminish the morbidity of the ongoing COVID-19 pandemic. A well-precedented drug target is the main viral protease (MPro ), which is targeted by an approved drug and by several investigational drugs. Emerging viral resistance has made new inhibitor chemotypes more pressing. Adopting a structure-based approach, we docked 1.2 billion non-covalent lead-like molecules and a new library of 6.5 million electrophiles against the enzyme structure. From these, 29 non-covalent and 11 covalent inhibitors were identified in 37 series, the most potent having an IC50 of 29 and 20 μM, respectively. Several series were optimized, resulting in low micromolar inhibitors. Subsequent crystallography confirmed the docking predicted binding modes and may template further optimization. While the new chemotypes may aid further optimization of MPro inhibitors for SARS-CoV-2, the modest success rate also reveals weaknesses in our approach for challenging targets like MPro versus other targets where it has been more successful, and versus other structure-based techniques against MPro itself.

A simulation framework for modeling the within-patient evolutionary dynamics of SARS-CoV-2

The global impact of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has led to considerable interest in detecting novel beneficial mutations and other genomic changes that may signal the development of variants of concern (VOCs). The ability to accurately detect these changes within individual patient samples is important in enabling early detection of VOCs. Such genomic scans for positive selection are best performed via comparison of empirical data to simulated data wherein evolutionary factors, including mutation and recombination rates, reproductive and infection dynamics, and purifying and background selection, can be carefully accounted for and parameterized. While there has been work to quantify these factors in SARS-CoV-2, they have yet to be integrated into a baseline model describing intra-host evolutionary dynamics. To construct such a baseline model, we develop a simulation framework that enables one to establish expectations for underlying levels and patterns of patient-level variation. By varying eight key parameters, we evaluated 12,096 different model-parameter combinations and compared them to existing empirical data. Of these, 592 models (~5%) were plausible based on the resulting mean expected number of segregating variants. These plausible models shared several commonalities shedding light on intra-host SARS-CoV-2 evolutionary dynamics: severe infection bottlenecks, low levels of reproductive skew, and a distribution of fitness effects skewed towards strongly deleterious mutations. We also describe important areas of model uncertainty and highlight additional sequence data that may help to further refine a baseline model. This study lays the groundwork for the improved analysis of existing and future SARS-CoV-2 within-patient data.

Systematic Analyses of the Resistance Potential of Drugs Targeting SARS-CoV-2 Main Protease

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 to nirmatrelvir (Pfizer), and ensitrelvir (Xocova) in a yeast screen. We identified 142 resistance mutations for nirmatrelvir and 177 for ensitrelvir, many of which have not been previously reported. Ninety-nine mutations caused apparent resistance to both inhibitors, suggesting likelihood for the evolution of cross-resistance. The mutation with the strongest drug resistance score against nirmatrelvir in our study (E166V) was the most impactful resistance mutation recently reported in multiple viral passaging studies. Many mutations that exhibited inhibitor-specific resistance were consistent with the distinct interactions of each inhibitor in the substrate binding site. In addition, mutants 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 compensatory 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.

Accelerating antiviral drug discovery: lessons from COVID-19

During the coronavirus disease 2019 (COVID-19) pandemic, a wave of rapid and collaborative drug discovery efforts took place in academia and industry, culminating in several therapeutics being discovered, approved and deployed in a 2-year time frame. This article summarizes the collective experience of several pharmaceutical companies and academic collaborations that were active in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antiviral discovery. We outline our opinions and experiences on key stages in the small-molecule drug discovery process: target selection, medicinal chemistry, antiviral assays, animal efficacy and attempts to pre-empt resistance. We propose strategies that could accelerate future efforts and argue that a key bottleneck is the lack of quality chemical probes around understudied viral targets, which would serve as a starting point for drug discovery. Considering the small size of the viral proteome, comprehensively building an arsenal of probes for proteins in viruses of pandemic concern is a worthwhile and tractable challenge for the community.

Dynamical Nonequilibrium Molecular Dynamics Simulations Identify Allosteric Sites and Positions Associated with Drug Resistance in the SARS-CoV-2 Main Protease

The SARS-CoV-2 main protease (Mpro) plays an essential role in the coronavirus lifecycle by catalyzing hydrolysis of the viral polyproteins at specific sites. Mpro is the target of drugs, such as nirmatrelvir, though resistant mutants have emerged that threaten drug efficacy. Despite its importance, questions remain on the mechanism of how Mpro binds its substrates. Here, we apply dynamical nonequilibrium molecular dynamics (D-NEMD) simulations to evaluate structural and dynamical responses of Mpro to the presence and absence of a substrate. The results highlight communication between the Mpro dimer subunits and identify networks, including some far from the active site, that link the active site with a known allosteric inhibition site, or which are associated with nirmatrelvir resistance. They imply that some mutations enable resistance by altering the allosteric behavior of Mpro. More generally, the results show the utility of the D-NEMD technique for identifying functionally relevant allosteric sites and networks including those relevant to resistance.

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.

Modulation of in Vitro SARS-CoV-2 Infection by Stephania tetrandra and Its Alkaloid Constituents

Botanical natural products have been widely consumed for their purported usefulness against COVID-19. Here, six botanical species from multiple sources and 173 isolated natural product compounds were screened for blockade of wild-type (WT) SARS-CoV-2 infection in human 293T epithelial cells overexpressing ACE-2 and TMPRSS2 protease (293TAT). Antiviral activity was demonstrated by an extract from Stephania tetrandra. Extract fractionation, liquid chromatography-mass spectrometry (LC-MS), antiviral assays, and computational analyses revealed that the alkaloid fraction and purified alkaloids tetrandrine, fangchinoline, and cepharanthine inhibited WT SARS-CoV-2 infection. The alkaloids and alkaloid fraction also inhibited the delta variant of concern but not WT SARS-CoV-2 in VeroAT cells. Membrane permeability assays demonstrate that the alkaloids are biologically available, although fangchinoline showed lower permeability than tetrandrine. At high concentrations, the extract, alkaloid fractions, and pure alkaloids induced phospholipidosis in 293TAT cells and less so in VeroAT cells. Gene expression profiling during virus infection suggested that alkaloid fraction and tetrandrine displayed similar effects on cellular gene expression and pathways, while fangchinoline showed distinct effects on cells. Our study demonstrates a multifaceted approach to systematically investigate the diverse activities conferred by complex botanical mixtures, their cell-context specificity, and their pleiotropic effects on biological systems.

Developing an appropriate evolutionary baseline model for the study of SARS-CoV-2 patient samples

Over the past 3 years, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has spread through human populations in several waves, resulting in a global health crisis. In response, genomic surveillance efforts have proliferated in the hopes of tracking and anticipating the evolution of this virus, resulting in millions of patient isolates now being available in public databases. Yet, while there is a tremendous focus on identifying newly emerging adaptive viral variants, this quantification is far from trivial. Specifically, multiple co-occurring and interacting evolutionary processes are constantly in operation and must be jointly considered and modeled in order to perform accurate inference. We here outline critical individual components of such an evolutionary baseline model-mutation rates, recombination rates, the distribution of fitness effects, infection dynamics, and compartmentalization-and describe the current state of knowledge pertaining to the related parameters of each in SARS-CoV-2. We close with a series of recommendations for future clinical sampling, model construction, and statistical analysis.

Antitarget, Anti-SARS-CoV-2 Leads, Drugs, and the Drug Discovery-Genetics Alliance Perspective

The most advanced antiviral molecules addressing major SARS-CoV-2 targets (Main protease, Spike protein, and RNA polymerase), compared with proteins of other human pathogenic coronaviruses, may have a short-lasting clinical efficacy. Accumulating knowledge on the mechanisms underlying the target structural basis, its mutational progression, and the related biological significance to virus replication allows envisaging the development of better-targeted therapies in the context of COVID-19 epidemic and future coronavirus outbreaks. The identification of evolutionary patterns based solely on sequence information analysis for those targets can provide meaningful insights into the molecular basis of host-pathogen interactions and adaptation, leading to drug resistance phenomena. Herein, we will explore how the study of observed and predicted mutations may offer valuable suggestions for the application of the so-called "synthetic lethal" strategy to SARS-CoV-2 Main protease and Spike protein. The synergy between genetics evidence and drug discovery may prioritize the development of novel long-lasting antiviral agents.

Crystal Structures of Inhibitor-Bound Main Protease from Delta- and Gamma-Coronaviruses

With the spread of SARS-CoV-2 throughout the globe causing the COVID-19 pandemic, the threat of zoonotic transmissions of coronaviruses (CoV) has become even more evident. As human infections have been caused by alpha- and beta-CoVs, structural characterization and inhibitor design mostly focused on these two genera. However, viruses from the delta and gamma genera also infect mammals and pose a potential zoonotic transmission threat. Here, we determined the inhibitor-bound crystal structures of the main protease (Mpro) from the delta-CoV porcine HKU15 and gamma-CoV SW1 from the beluga whale. A comparison with the apo structure of SW1 Mpro, which is also presented here, enabled the identification of structural arrangements upon inhibitor binding at the active site. The cocrystal structures reveal binding modes and interactions of two covalent inhibitors, PF-00835231 (active form of lufotrelvir) bound to HKU15, and GC376 bound to SW1 Mpro. These structures may be leveraged to target diverse coronaviruses and toward the structure-based design of pan-CoV inhibitors.

Novel dithiocarbamates selectively inhibit 3CL protease of SARS-CoV-2 and other coronaviruses

Since end of 2019, the global and unprecedented outbreak caused by the coronavirus SARS-CoV-2 led to dramatic numbers of infections and deaths worldwide. SARS-CoV-2 produces two large viral polyproteins which are cleaved by two cysteine proteases encoded by the virus, the 3CL protease (3CL^pro) and the papain-like protease, to generate non-structural proteins essential for the virus life cycle. Both proteases are recognized as promising drug targets for the development of anti-coronavirus chemotherapy. Aiming at identifying broad spectrum agents for the treatment of COVID-19 but also to fight emergent coronaviruses, we focused on 3CL^pro that is well conserved within this viral family. Here we present a high-throughput screening of more than 89,000 small molecules that led to the identification of a new chemotype, potent inhibitor of the SARS-CoV-2 3CL^pro. The mechanism of inhibition, the interaction with the protease using NMR and X-Ray, the specificity against host cysteine proteases and promising antiviral properties in cells are reported.

The Substitutions L50F, E166A, and L167F in SARS-CoV-2 3CLpro Are Selected by a Protease Inhibitor In Vitro and Confer Resistance To Nirmatrelvir

The SARS-CoV-2 main protease (3CLpro) has an indispensable role in the viral life cycle and is a therapeutic target for the treatment of COVID-19. The potential of 3CLpro-inhibitors to select for drug-resistant variants needs to be established. Therefore, SARS-CoV-2 was passaged in vitro in the presence of increasing concentrations of ALG-097161, a probe compound designed in the context of a 3CLpro drug discovery program. We identified a combination of amino acid substitutions in 3CLpro (L50F E166A L167F) that is associated with a >20× increase in 50% effective concentration (EC₅₀) values for ALG-097161, nirmatrelvir (PF-07321332), PF-00835231, and ensitrelvir. While two of the single substitutions (E166A and L167F) provide low-level resistance to the inhibitors in a biochemical assay, the triple mutant results in the highest levels of resistance (6× to 72×). All substitutions are associated with a significant loss of enzymatic 3CLpro activity, suggesting a reduction in viral fitness. Structural biology analysis indicates that the different substitutions reduce the number of inhibitor/enzyme interactions while the binding of the substrate is maintained. These observations will be important for the interpretation of resistance development to 3CLpro inhibitors in the clinical setting. IMPORTANCE Paxlovid is the first oral antiviral approved for treatment of SARS-CoV-2 infection. Antiviral treatments are often associated with the development of drug-resistant viruses. In order to guide the use of novel antivirals, it is essential to understand the risk of resistance development and to characterize the associated changes in the viral genes and proteins. In this work, we describe for the first time a pathway that allows SARS-CoV-2 to develop resistance against Paxlovid in vitro. The characteristics of in vitro antiviral resistance development may be predictive for the clinical situation. Therefore, our work will be important for the management of COVID-19 with Paxlovid and next-generation SARS-CoV-2 3CLpro inhibitors.

The Substitutions L50F, E166A, and L167F in SARS-CoV-2 3CLpro Are Selected by a Protease Inhibitor In Vitro and Confer Resistance To Nirmatrelvir

The SARS-CoV-2 main protease (3CLpro) has an indispensable role in the viral life cycle and is a therapeutic target for the treatment of COVID-19. The potential of 3CLpro-inhibitors to select for drug-resistant variants needs to be established. Therefore, SARS-CoV-2 was passaged in vitro in the presence of increasing concentrations of ALG-097161, a probe compound designed in the context of a 3CLpro drug discovery program. We identified a combination of amino acid substitutions in 3CLpro (L50F E166A L167F) that is associated with a >20× increase in 50% effective concentration (EC₅₀) values for ALG-097161, nirmatrelvir (PF-07321332), PF-00835231, and ensitrelvir. While two of the single substitutions (E166A and L167F) provide low-level resistance to the inhibitors in a biochemical assay, the triple mutant results in the highest levels of resistance (6× to 72×). All substitutions are associated with a significant loss of enzymatic 3CLpro activity, suggesting a reduction in viral fitness. Structural biology analysis indicates that the different substitutions reduce the number of inhibitor/enzyme interactions while the binding of the substrate is maintained. These observations will be important for the interpretation of resistance development to 3CLpro inhibitors in the clinical setting. IMPORTANCE Paxlovid is the first oral antiviral approved for treatment of SARS-CoV-2 infection. Antiviral treatments are often associated with the development of drug-resistant viruses. In order to guide the use of novel antivirals, it is essential to understand the risk of resistance development and to characterize the associated changes in the viral genes and proteins. In this work, we describe for the first time a pathway that allows SARS-CoV-2 to develop resistance against Paxlovid in vitro. The characteristics of in vitro antiviral resistance development may be predictive for the clinical situation. Therefore, our work will be important for the management of COVID-19 with Paxlovid and next-generation SARS-CoV-2 3CLpro inhibitors.

Nirmatrelvir Resistance in SARS-CoV-2 Omicron_BA.1 and WA1 Replicons and Escape Strategies

The antiviral component of Paxlovid, nirmatrelvir (NIR), forms a covalent bond with Cys145 of SARS-CoV-2 nsp5. To explore NIR resistance we designed mutations to impair binding of NIR over substrate. Using 12 Omicron (BA.1) and WA.1 SARS-CoV-2 replicons, cell-based complementation and enzymatic assays, we showed that in both strains, E166V imparted high NIR resistance (∼55-fold), with major decrease in WA1 replicon fitness (∼20-fold), but not BA.1 (∼2-fold). WA1 replicon fitness was restored by L50F. These differences may contribute to a potentially lower barrier to resistance in Omicron than WA1. E166V is rare in untreated patients, albeit more prevalent in paxlovid-treated EPIC-HR clinical trial patients. Importantly, NIR-resistant replicons with E166V or E166V/L50F remained susceptible to a) the flexible GC376, and b) PF-00835231, which forms additional interactions. Molecular dynamics simulations show steric clashes between the rigid and bulky NIR t-butyl and β-branched V166 distancing the NIR warhead from its Cys145 target. In contrast, GC376, through "wiggling and jiggling" accommodates V166 and still covalently binds Cys145. PF-00835231 uses its strategically positioned methoxy-indole to form a β-sheet and overcome E166V. Drug design based on strategic flexibility and main chain-targeting may help develop second-generation nsp5-targeting antivirals efficient against NIR-resistant viruses.

Nirmatrelvir-resistant SARS-CoV-2 variants with high fitness in an infectious cell culture system

The oral protease inhibitor nirmatrelvir is of key importance for prevention of severe coronavirus disease 2019 (COVID-19). To facilitate resistance monitoring, we studied severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) escape from nirmatrelvir in cell culture. Resistant variants harbored combinations of substitutions in the SARS-CoV-2 main protease (Mpro). Reverse genetics revealed that E166V and L50F + E166V conferred high resistance in infectious culture, replicon, and Mpro systems. While L50F, E166V, and L50F + E166V decreased replication and Mpro activity, L50F and L50F + E166V variants had high fitness in the infectious system. Naturally occurring L50F compensated for fitness cost of E166V and promoted viral escape. Molecular dynamics simulations revealed that E166V and L50F + E166V weakened nirmatrelvir-Mpro binding. Polymerase inhibitor remdesivir and monoclonal antibody bebtelovimab retained activity against nirmatrelvir-resistant variants, and combination with nirmatrelvir enhanced treatment efficacy compared to individual compounds. These findings have implications for monitoring and ensuring treatments with efficacy against SARS-CoV-2 and emerging sarbecoviruses.

Nirmatrelvir-resistant SARS-CoV-2 variants with high fitness in an infectious cell culture system

The oral protease inhibitor nirmatrelvir is of key importance for prevention of severe coronavirus disease 2019 (COVID-19). To facilitate resistance monitoring, we studied severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) escape from nirmatrelvir in cell culture. Resistant variants harbored combinations of substitutions in the SARS-CoV-2 main protease (Mpro). Reverse genetics revealed that E166V and L50F + E166V conferred high resistance in infectious culture, replicon, and Mpro systems. While L50F, E166V, and L50F + E166V decreased replication and Mpro activity, L50F and L50F + E166V variants had high fitness in the infectious system. Naturally occurring L50F compensated for fitness cost of E166V and promoted viral escape. Molecular dynamics simulations revealed that E166V and L50F + E166V weakened nirmatrelvir-Mpro binding. Polymerase inhibitor remdesivir and monoclonal antibody bebtelovimab retained activity against nirmatrelvir-resistant variants, and combination with nirmatrelvir enhanced treatment efficacy compared to individual compounds. These findings have implications for monitoring and ensuring treatments with efficacy against SARS-CoV-2 and emerging sarbecoviruses.

Recent changes in the mutational dynamics of the SARS-CoV-2 main protease substantiate the danger of emerging resistance to antiviral drugs

Introduction

The current coronavirus pandemic is being combated worldwide by nontherapeutic measures and massive vaccination programs. Nevertheless, therapeutic options such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main-protease (Mpro) inhibitors are essential due to the ongoing evolution toward escape from natural or induced immunity. While antiviral strategies are vulnerable to the effects of viral mutation, the relatively conserved Mpro makes an attractive drug target: Nirmatrelvir, an antiviral targeting its active site, has been authorized for conditional or emergency use in several countries since December 2021, and a number of other inhibitors are under clinical evaluation. We analyzed recent SARS-CoV-2 genomic data, since early detection of potential resistances supports a timely counteraction in drug development and deployment, and discovered accelerated mutational dynamics of Mpro since early December 2021.

Methods

We performed a comparative analysis of 10.5 million SARS-CoV-2 genome sequences available by June 2022 at GISAID to the NCBI reference genome sequence NC_045512.2. Amino-acid exchanges within high-quality regions in 69,878 unique Mpro sequences were identified and time- and in-depth sequence analyses including a structural representation of mutational dynamics were performed using in-house software.

Results

The analysis showed a significant recent event of mutational dynamics in Mpro. We report a remarkable increase in mutational variability in an eight-residue long consecutive region (R188-G195) near the active site since December 2021.

Discussion

The increased mutational variability in close proximity to an antiviral-drug binding site as described herein may suggest the onset of the development of antiviral resistance. This emerging diversity urgently needs to be further monitored and considered in ongoing drug development and lead optimization.

Prediction of Recurrent Mutations in SARS-CoV-2 Using Artificial Neural Networks

Predicting SARS-CoV-2 mutations is difficult, but predicting recurrent mutations driven by the host, such as those caused by host deaminases, is feasible. We used machine learning to predict which positions from the SARS-CoV-2 genome will hold a recurrent mutation and which mutations will be the most recurrent. We used data from April 2021 that we separated into three sets: a training set, a validation set, and an independent test set. For the test set, we obtained a specificity value of 0.69, a sensitivity value of 0.79, and an Area Under the Curve (AUC) of 0.8, showing that the prediction of recurrent SARS-CoV-2 mutations is feasible. Subsequently, we compared our predictions with updated data from January 2022, showing that some of the false positives in our prediction model become true positives later on. The most important variables detected by the model's Shapley Additive exPlanation (SHAP) are the nucleotide that mutates and RNA reactivity. This is consistent with the SARS-CoV-2 mutational bias pattern and the preference of some host deaminases for specific sequences and RNA secondary structures. We extend our investigation by analyzing the mutations from the variants of concern Alpha, Beta, Delta, Gamma, and Omicron. Finally, we analyzed amino acid changes by looking at the predicted recurrent mutations in the M-pro and spike proteins.

Combinations of Host- and Virus-Targeting Antiviral Drugs Confer Synergistic Suppression of SARS-CoV-2

Three directly acting antivirals (DAAs) demonstrated substantial reduction in COVID-19 hospitalizations and deaths in clinical trials. However, these agents did not completely prevent severe illness and are associated with cases of rebound illness and viral shedding. Combination regimens can enhance antiviral potency, reduce the emergence of drug-resistant variants, and lower the dose of each component in the combination. Concurrently targeting virus entry and virus replication offers opportunities to discover synergistic drug combinations. While combination antiviral drug treatments are standard for chronic RNA virus infections, no antiviral combination therapy has been approved for SARS-CoV-2. Here, we demonstrate that combining host-targeting antivirals (HTAs) that target TMPRSS2 and hence SARS-CoV-2 entry, with the DAA molnupiravir, which targets SARS-CoV-2 replication, synergistically suppresses SARS-CoV-2 infection in Calu-3 lung epithelial cells. Strong synergy was observed when molnupiravir, an oral drug, was combined with three TMPRSS2 (HTA) oral or inhaled inhibitors: camostat, avoralstat, or nafamostat. The combination of camostat plus molnupiravir was also effective against the beta and delta variants of concern. The pyrimidine biosynthesis inhibitor brequinar combined with molnupiravir also conferred robust synergistic inhibition. These HTA+DAA combinations had similar potency to the synergistic all-DAA combination of molnupiravir plus nirmatrelvir, the protease inhibitor found in paxlovid. Pharmacodynamic modeling allowed estimates of antiviral potency at all possible concentrations of each agent within plausible therapeutic ranges, suggesting possible in vivo efficacy. The triple combination of camostat, brequinar, and molnupiravir further increased antiviral potency. These findings support the development of HTA+DAA combinations for pandemic response and preparedness. IMPORTANCE Imagine a future viral pandemic where if you test positive for the new virus, you can quickly take some medicines at home for a few days so that you do not get too sick. To date, only single drugs have been approved for outpatient use against SARS-CoV-2, and we are learning that these have some limitations and may succumb to drug resistance. Here, we show that combinations of two oral drugs are better than the single ones in blocking SARS-CoV-2, and we use mathematical modeling to show that these drug combinations are likely to work in people. We also show that a combination of three oral drugs works even better at eradicating the virus. Our findings therefore bode well for the development of oral drug cocktails for at home use at the first sign of an infection by a coronavirus or other emerging viral pathogens.

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

The SARS-CoV-2 3CL protease (3CLpro) is an attractive therapeutic target, as it is essential to the virus and highly conserved among coronaviruses. However, our current understanding of its tolerance to mutations is limited. Here, we develop a yeast-based deep mutational scanning approach to systematically profile the activity of all possible single mutants of the 3CLpro and validate a subset of our results within authentic viruses. We reveal that the 3CLpro is highly malleable and is capable of tolerating mutations throughout the protein. Yet, we also identify specific residues that appear immutable, suggesting that these may be targets for future 3CLpro inhibitors. Finally, we utilize our screening as a basis to identify E166V as a resistance-conferring mutation against the clinically used 3CLpro inhibitor, nirmatrelvir. Collectively, the functional map presented herein may serve as a guide to better understand the biological properties of the 3CLpro and for drug development against coronaviruses.

As the virus evolves, so too must we: a drug developer's perspective : We need a new paradigm in searching for next-generation countermeasures

The SARS-CoV-2 virus has been raging globally for over 2 years with no end in sight. It has become clear that this virus possesses enormous genetic plasticity, and it will not be eradicated. Under increasing selective pressure from population immunity, the evolution of SARS-CoV-2 has driven it towards greater infectivity, and evasion of humoral and cellular immunity. Omicron and its expanding army of subvariants and recombinants have impaired vaccine protection and made most antibody drugs obsolete. Antiviral drugs, though presently effective, may select for more resistant strains over time. It may be inevitable, then, that future SARS-CoV-2 variants will be immune to our current virus-directed countermeasures. Thus, to gain control over the virus, we need to adopt a new paradigm in searching for next-generation countermeasures and develop host-directed therapeutics (HDTx) and host-directed antivirals (HDA). Different from the virus-directed countermeasures, HDTx and HDA may offer variant agnostic treatment to reduce the risk and severity of infections. In addition, they may exert more uniform effects against the genetically diverse SARS-CoV-2 quasispecies, thereby diminishing the risk of selecting resistant variants. Some promising HDTx and HDA approaches are summarized here.

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 a proxy 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 showed that an E166R substitution conferred strong nirmatrelvir resistance while an E166N mutation compromised activity. On the other hand, N142A and P132H mutations 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.

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

The SARS-CoV-2 main protease (M pro ) is a major therapeutic target. The M pro inhibitor, nirmatrelvir, is the antiviral component of Paxlovid, an orally available treatment for COVID-19. As M pro inhibitor use increases, drug resistant mutations will likely emerge. We have established a non-pathogenic system, in which yeast growth serves as a proxy for M pro 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 showed that an E166R substitution conferred strong nirmatrelvir resistance while an E166N mutation compromised activity. On the other hand, N142A and P132H mutations caused little to no change in drug response and activity. Standard enzymatic assays confirmed the yeast results. In turn, we solved the structures of M pro E166R, and M pro 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 M pro that may arise as M pro antivirals become more widely used.

Developing evolution-resistant drugs for COVID-19

Analyzing how mutations affect the main protease of SARS-CoV-2 may help researchers develop drugs that are effective against current and future variants of the virus.