Dynamic Profiling of β-Coronavirus 3CL Mpro Protease Ligand-Binding Sites

Unsupervised Learning of Progress Coordinates during Weighted Ensemble Simulations: Application to NTL9 Protein Folding

A major challenge for many rare-event sampling strategies is the identification of progress coordinates that capture the slowest relevant motions. Machine-learning methods that can identify progress coordinates in an unsupervised manner have therefore been of great interest to the simulation community. Here, we developed a general method for identifying progress coordinates "on-the-fly" during weighted ensemble (WE) rare-event sampling via deep learning (DL) of outliers among sampled conformations. Our method identifies outliers in a latent space model of the system's sampled conformations that is periodically trained using a convolutional variational autoencoder. As a proof of principle, we applied our DL-enhanced WE method to simulate the NTL9 protein folding process. To enable rapid tests, our simulations propagated discrete-state synthetic molecular dynamics trajectories using a generative, fine-grained Markov state model. Results revealed that our on-the-fly DL of outliers enhanced the efficiency of WE by >3-fold in estimating the folding rate constant. Our efforts are a significant step forward in the unsupervised learning of slow coordinates during rare event sampling.

SARS-CoV-2 Mpro Dihedral Angles Reveal Allosteric Signaling

In allosteric proteins, identifying the pathways that signals take from allosteric ligand-binding sites to enzyme active sites or binding pockets and interfaces remains challenging. This avenue of research is motivated by the goals of understanding particular macromolecular systems of interest and creating general methods for their study. An especially important protein that is the subject of many investigations in allostery is the SARS-CoV-2 main protease (Mpro), which is necessary for coronaviral replication. It is both an attractive drug target and, due to intense interest in it for the development of pharmaceutical compounds, a gauge of the state of the art approaches in studying protein inhibition. Here we develop a computational method for characterizing protein allostery and use it to study Mpro. We propose a role of the protein's C-terminal tail in allosteric modulation and warn of unintuitive traps that can plague studies of the role of protein dihedral angles in transmitting allosteric signals.

Investigating the inhibition of benzimidazole derivatives on SARS-CoV-2 Mpro by enzyme activity inhibition, spectroscopy, and molecular docking

The inhibition of twenty-five 1,2-fused/disubstituted benzimidazoles on the SARS-CoV-2 Mpro were investigated in this work. It was found that four compounds (1i, 1k, 1l, and 1m) showed obvious inhibitory effect on Mpro. The inhibitory effect of 1k (IC50 46.86 μM) was the best. UV-vis, fluorescence, CD and molecular docking methods were used to reveal the mechanisms of interaction between these compounds and Mpro. Results indicated that static quenching was the main type of quenching. 1i, 1k, 1l, and 1m may alter the conformation and microenvironment of Mpro. The dominant forces between 1i (or 1l) and Mpro were hydrogen bonds or van der Waals forces. The dominant forces between 1k (or 1m) and Mpro were electrostatic or hydrophobic forces, which was consistent with the results of molecular docking. The influence of molecular structure on the binding was investigated. Chlorine atom groups were favorable for the 1,2-fused/disubstituted benzimidazoles derivative inhibitors of Mpro. This work confirmed the changes in the micro-environment of Mpro by 1k, and provided clues for the design of potential Mpro inhibitors.

Decoding SARS-CoV-2 Inhibition: Insights From Molecular Dynamics Simulation of Condensed Amino Thiourea Scaffold Small Molecules

The main protease (Mpro) of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) plays a crucial role in viral replication. In this study, the binding modes and inhibitory mechanisms of eight condensed amino thiourea scaffold inhibitors of Mpro in proteins were investigated using a combination of molecular docking, molecular dynamics simulations, and MM/PBSA binding free energy calculations. The results indicated that the para-hydroxyl group on the benzene ring at the head of the inhibitor has a decisive influence on the initial docking pose and binding free energy strength of the inhibitor. Additionally, the position and length of the hydrophobic side chain on the tail six-membered ring significantly impacted the final binding pose of the inhibitor. The presence of a long hydrophobic side chain in the ortho position of this ring, through its interaction with the P4 hydrophobic pocket, led to an opposite binding mode in the protein compared with when it was present with or without the para-side chain. Different lengths of para-substituted side chains affected the positioning of the inhibitors in the enzyme. These different binding modes led to variations in the binding free energy between the inhibitor and the protein, which in turn gave rise to differences in inhibitory capability.

The Conformational Space of the SARS-CoV-2 Main Protease Active Site Loops Is Determined by Ligand Binding and Interprotomer Allostery

The main protease (Mpro) of SARS-CoV-2 is essential for viral replication and is, therefore, an important drug target. Here, we investigate two flexible loops in Mpro that play a role in catalysis. Using all-atom molecular dynamics simulations, we analyze the structural ensemble of Mpro in an apo state and substrate-bound state. We find that the flexible loops can adopt open, intermediate (partly open), and closed conformations in solution, which differs from the partially closed state observed in crystal structures of Mpro. When the loops are in closed or intermediate states, the catalytic residues are more likely to be in close proximity, which is crucial for catalysis. Additionally, we find that substrate binding to one protomer of the homodimer increases the frequency of intermediate states in the bound protomer while also affecting the structural propensity of the apo protomer's flexible loops. Using dynamic network analysis, we identify multiple allosteric pathways connecting the two active sites of the homodimer. Common to these pathways is an allosteric hotspot involving the N-terminus, a critical region that comprises part of the binding pocket. Taken together, the results of our simulation study provide detailed insight into the relationships between the flexible loops and substrate binding in a prime drug target for COVID-19.

Natural and Synthetic Coumarins as Potential Drug Candidates against SARS-CoV-2/COVID-19

COVID-19, an airborne disease caused by a betacoronavirus named SARS-- CoV-2, was officially declared a pandemic in early 2020, resulting in more than 770 million confirmed cases and over 6.9 million deaths by September 2023. Although the introduction of vaccines in late 2020 helped reduce the number of deaths, the global effort to fight COVID-19 is far from over. While significant progress has been made in a short period, the fight against SARS-CoV-2/COVID-19 and other potential pandemic threats continues. Like AIDS and hepatitis C epidemics, controlling the spread of COVID-19 will require the development of multiple drugs to weaken the virus's resistance to different drug treatments. Therefore, it is essential to continue developing new drug candidates derived from natural or synthetic small molecules. Coumarins are a promising drug design and development scaffold due to their synthetic versatility and unique physicochemical properties. Numerous examples reported in scientific literature, mainly by in silico prospection, demonstrate their potential contribution to the rapid development of drugs against SARS-CoV-2/COVID-19 and other emergent and reemergent viruses.

Covalent small-molecule inhibitors of SARS-CoV-2 Mpro: Insights into their design, classification, biological activity, and binding interactions

Since 2020, many compounds have been investigated for their potential use in the treatment of SARS-CoV-2 infection. Among these agents, a huge number of natural products and FDA-approved drugs have been evaluated as potential therapeutics for SARS-CoV-2 using virtual screening and docking studies. However, the identification of the molecular targets involved in viral replication led to the development of rationally designed anti-SARS-CoV-2 agents. Among these targets, the main protease (Mpro) is one of the key enzymes needed in the replication of the virus. The data gleaned from the crystal structures of SARS-CoV-2 Mpro complexes with small-molecule covalent inhibitors has been used in the design and discovery of many highly potent and broad-spectrum Mpro inhibitors. The current review focuses mainly on the covalent type of SARS-CoV-2 Mpro inhibitors. The design, chemistry, and classification of these inhibitors were also in focus. The biological activity of these inhibitors, including their inhibitory activities against Mpro, their antiviral activities, and the SAR studies, were discussed. The review also describes the potential mechanism of the interaction between these inhibitors and the catalytic Cys145 residue in Mpro. Moreover, the binding modes and key binding interactions of these covalent inhibitors were also illustrated. The covalent inhibitors discussed in this review were of diverse chemical nature and origin. Their antiviral activity was mediated mainly by the inhibition of SARS-CoV-2 Mpro, with IC50 values in the micromolar to the nanomolar range. Many of these inhibitors exhibited broad-spectrum inhibitory activity against the Mpro enzymes of other coronaviruses (SARS-CoV-1 and MERS-CoV). The dual inhibition of the Mpro and PLpro enzymes of SARS-CoV-2 could also provide higher therapeutic benefits than Mpro inhibition. Despite the approval of nirmatrelvir by the FDA, many mutations in the Mpro enzyme of SARS-CoV-2 have been reported. Although some of these mutations did not affect the potency of nirmatrelvir, there is an urgent need to develop a second generation of Mpro inhibitors. We hope that the data summarized in this review could help researchers in the design of a new potent generation of SARS-CoV-2 Mpro inhibitors.

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.

High-Resolution Substrate Specificity Profiling of SARS-CoV-2 Mpro; Comparison to SARS-CoV Mpro

The SARS-CoV-2 Mpro protease from COVID-19 cleaves the pp1a and pp2b polyproteins at 11 sites during viral maturation and is the target of Nirmatrelvir, one of the two components of the frontline treatment sold as Paxlovid. We used the YESS 2.0 platform, combining protease and substrate expression in the yeast endoplasmic reticulum with fluorescence-activated cell sorting and next-generation sequencing, to carry out the high-resolution substrate specificity profiling of SARS-CoV-2 Mpro as well as the related SARS-CoV Mpro from SARS 2003. Even at such a high level of resolution, the substrate specificity profiles of both enzymes are essentially identical. The population of cleaved substrates isolated in our sorts is so deep, the relative catalytic efficiencies of the different cleavage sites on the SARS-CoV-2 polyproteins pp1a and pp2b are qualitatively predicted. These results not only demonstrated the precise and reproducible nature of the YESS 2.0/NGS approach to protease substrate specificity profiling but also should be useful in the design of next generation SARS-CoV-2 Mpro inhibitors, and by analogy, SARS-CoV Mpro inhibitors as well.

Repurposing the Open Global Health Library for the discovery of novel Mpro destabilizers with scope as broad-spectrum antivirals

The SARS coronavirus 2 (SARS-CoV-2) epidemic remains globally active. The emergence of new variants of interest and variants of concern (VoCs), which are potentially more vaccine-resistant and less sensitive to existing treatments, is evident due to their high prevalence. The prospective spread of such variants and other coronaviruses with epidemic potential demands preparedness that can be met by developing fast-track workflows to find new candidates that target viral proteins with a clear in vitro and in vivo phenotype. Mpro (or 3CLpro) is directly involved in the viral replication cycle and the production and function of viral polyproteins, which makes it an ideal target. The biological relevance of Mpro is highly conserved among betacoronaviruses like HCoV-OC43 and SARS-CoV-2, which makes the identification of new chemical scaffolds targeting them a good starting point for designing broad-spectrum antivirals. We report an optimized methodology based on orthogonal cell-free assays to identify small molecules that inhibit the binding pockets of both SARS-CoV-2-Mpro and HCoV-OC43-Mpro; this blockade correlates with antiviral activities in HCoV-OC43 cellular models. By using such a fast-tracking approach against the Open Global Health Library (Merck KGaA), we have found evidence of the antiviral activity of compound OGHL98. In silico studies dissecting intermolecular interactions between OGHL98 and both proteases and comprising docking and molecular dynamics simulations (MDSs) concluded that the binding mode was primarily governed by conserved H-bonds with their C-terminal amino acids and that the rational design of OGHL98 has potential against VoCs proteases resistant to current therapeutics.

SARS-CoV-2 3CLPro Dihedral Angles Reveal Allosteric Signaling

In allosteric proteins, identifying the pathways that signals take from allosteric ligand-binding sites to enzyme active sites or binding pockets and interfaces remains challenging. This avenue of research is motivated by the goals of understanding particular macromolecular systems of interest and creating general methods for their study. An especially important protein that is the subject of many investigations in allostery is the SARS-CoV-2 main protease (Mpro), which is necessary for coronaviral replication. It is both an attractive drug target and, due to intense interest in it for the development of pharmaceutical compounds, a gauge of the state-of-the-art approaches in studying protein inhibition. Here we develop a computational method for characterizing protein allostery and use it to study Mpro. We propose a role of the protein's C-terminal tail in allosteric modulation and warn of unintuitive traps that can plague studies of the role of protein dihedrals angles in transmitting allosteric signals.

Deciphering the Coevolutionary Dynamics of L2 β-Lactamases via Deep Learning

L2 β-lactamases, serine-based class A β-lactamases expressed by Stenotrophomonas maltophilia, play a pivotal role in antimicrobial resistance (AMR). However, limited studies have been conducted on these important enzymes. To understand the coevolutionary dynamics of L2 β-lactamase, innovative computational methodologies, including adaptive sampling molecular dynamics simulations, and deep learning methods (convolutional variational autoencoders and BindSiteS-CNN) explored conformational changes and correlations within the L2 β-lactamase family together with other representative class A enzymes including SME-1 and KPC-2. This work also investigated the potential role of hydrophobic nodes and binding site residues in facilitating the functional mechanisms. The convergence of analytical approaches utilized in this effort yielded comprehensive insights into the dynamic behavior of the β-lactamases, specifically from an evolutionary standpoint. In addition, this analysis presents a promising approach for understanding how the class A β-lactamases evolve in response to environmental pressure and establishes a theoretical foundation for forthcoming endeavors in drug development aimed at combating AMR.

Identification of amentoflavone as a potent SARS-CoV-2 Mpro inhibitor: a combination of computational studies and in vitro biological evaluation

Small-molecule inhibitors of SARS-CoV-2 Mpro that block the active site pocket of the viral main protease have been considered potential therapeutics for the development of drugs against SARS-CoV-2. Here, we report the identification of amentoflavone (a biflavonoid) through docking-based virtual screening of a library comprised of 231 compounds consisting of flavonoids and isoflavonoids. The docking results were further substantiated through extensive analysis of the data obtained from all-atom 150 ns MD simulation. End-state effective free energy calculations using MM-PBSA calculations further suggested that (Ra)-amentoflavone (C3'-C8''-atropisomer) may show a greater binding affinity towards the Mpro than (Sa)-amentoflavone. In vitro cytotoxicity assay established that amentoflavone showed a high CC50 value indicating much lower toxicity. Further, potent inhibition of the Mpro by amentoflavone was established by studying the effect on HEK293T cells treated with SARS-CoV-2 Mpro expressing plasmid.Communicated by Ramaswamy H. Sarma.

Development of de-novo coronavirus 3-chymotrypsin-like protease (3CLpro) inhibitors since COVID-19 outbreak: A strategy to tackle challenges of persistent virus infection

Although no longer a public health emergency of international concern, COVID-19 remains a persistent and critical health concern. The development of effective antiviral drugs could serve as the ultimate piece of the puzzle to curbing this global crisis. 3-chymotrypsin-like protease (3CLpro), with its substrate specificity mirroring that of the main picornavirus 3C protease and conserved across various coronaviruses, emerges as an ideal candidate for broad-spectrum antiviral drug development. Moreover, it holds the potential as a reliable contingency option to combat emerging SARS-CoV-2 variants. In this light, the approved drugs, promising candidates, and de-novo small molecule therapeutics targeting 3CLpro since the COVID-19 outbreak in 2020 are discussed. Emphasizing the significance of diverse structural characteristics in inhibitors, be they peptidomimetic or nonpeptidic, with a shared mission to minimize the risk of cross-resistance. Moreover, the authors propose an innovative optimization strategy for 3CLpro reversible covalent PROTACs, optimizing pharmacodynamics and pharmacokinetics to better prepare for potential future viral outbreaks.

Olgotrelvir, a dual inhibitor of SARS-CoV-2 Mpro and cathepsin L, as a standalone antiviral oral intervention candidate for COVID-19

BACKGROUND

Oral antiviral drugs with improved antiviral potency and safety are needed to address current challenges in clinical practice for treatment of COVID-19, including the risks of rebound, drug-drug interactions, and emerging resistance.

METHODS

Olgotrelvir (STI-1558) is designed as a next-generation antiviral targeting the SARS-CoV-2 main protease (Mpro), an essential enzyme for SARS-CoV-2 replication, and human cathepsin L (CTSL), a key enzyme for SARS-CoV-2 entry into host cells.

FINDINGS

Olgotrelvir is a highly bioavailable oral prodrug that is converted in plasma to its active form, AC1115. The dual mechanism of action of olgotrelvir and AC1115 was confirmed by enzyme activity inhibition assays and co-crystal structures of AC1115 with SARS-CoV-2 Mpro and human CTSL. AC1115 displayed antiviral activity by inhibiting replication of all tested SARS-CoV-2 variants in cell culture systems. Olgotrelvir also inhibited viral entry into cells using SARS-CoV-2 Spike-mediated pseudotypes by inhibition of host CTSL. In the K18-hACE2 transgenic mouse model of SARS-CoV-2-mediated disease, olgotrelvir significantly reduced the virus load in the lungs, prevented body weight loss, and reduced cytokine release and lung pathologies. Olgotrelvir demonstrated potent activity against the nirmatrelvir-resistant Mpro E166 mutants. Olgotrelvir showed enhanced oral bioavailability in animal models and in humans with significant plasma exposure without ritonavir. In phase I studies (ClinicalTrials.gov: NCT05364840 and NCT05523739), olgotrelvir demonstrated a favorable safety profile and antiviral activity.

CONCLUSIONS

Olgotrelvir is an oral inhibitor targeting Mpro and CTSL with high antiviral activity and plasma exposure and is a standalone treatment candidate for COVID-19.

FUNDING

Funded by Sorrento Therapeutics.

Development of novel ligands against SARS-CoV-2 Mpro enzyme: an in silico and in vitro Study

BACKGROUND

Despite tremendous efforts made by scientific community during the outbreak of COVID-19 pandemic, this disease still remains as a public health concern. Although different types of vaccines were globally used to reduce the mortality, emergence of new variants of SARS-CoV-2 is a challenging issue in COVID-19 pharmacotherapy. In this context, target therapy of SARS-CoV-2 by small ligands is a promising strategy.

METHODS

In this investigation, we applied ligand-based virtual screening for finding novel molecules based on nirmatrelvir structure. Various criteria including drug-likeness, ADME, and toxicity properties were applied for filtering the compounds. The selected candidate molecules were subjected to molecular docking and dynamics simulation for predicting the binding mode and binding free energy, respectively. Then the molecules were experimentally evaluated in terms of antiviral activity against SARS-CoV-2 and toxicity assessment.

RESULTS

The results demonstrated that the identified compounds showed inhibitory activity towards SARS-CoV-2 Mpro .

CONCLUSION

In summary, the introduced compounds may provide novel scaffold for further structural modification and optimization with improved anti SARS-CoV-2 Mpro activity.

Analyzing 3D structures of the SARS-CoV-2 main protease reveals structural features of ligand binding for COVID-19 drug discovery

The severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) main protease has an essential role in viral replication and has become a major target for coronavirus 2019 (COVID-19) drug development. Various inhibitors have been discovered or designed to bind to the main protease. The availability of more than 550 3D structures of the main protease provides a wealth of structural details on the main protease in both ligand-free and ligand-bound states. Therefore, we examined these structures to ascertain the structural features for the role of the main protease in the cleavage of polyproteins, the alternative conformations during main protease maturation, and ligand interactions in the main protease. The structural features unearthed could promote the development of COVID-19 drugs targeting the SARS-CoV-2 main protease.

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.

Adaptive language model training for molecular design

The vast size of chemical space necessitates computational approaches to automate and accelerate the design of molecular sequences to guide experimental efforts for drug discovery. Genetic algorithms provide a useful framework to incrementally generate molecules by applying mutations to known chemical structures. Recently, masked language models have been applied to automate the mutation process by leveraging large compound libraries to learn commonly occurring chemical sequences (i.e., using tokenization) and predict rearrangements (i.e., using mask prediction). Here, we consider how language models can be adapted to improve molecule generation for different optimization tasks. We use two different generation strategies for comparison, fixed and adaptive. The fixed strategy uses a pre-trained model to generate mutations; the adaptive strategy trains the language model on each new generation of molecules selected for target properties during optimization. Our results show that the adaptive strategy allows the language model to more closely fit the distribution of molecules in the population. Therefore, for enhanced fitness optimization, we suggest the use of the fixed strategy during an initial phase followed by the use of the adaptive strategy. We demonstrate the impact of adaptive training by searching for molecules that optimize both heuristic metrics, drug-likeness and synthesizability, as well as predicted protein binding affinity from a surrogate model. Our results show that the adaptive strategy provides a significant improvement in fitness optimization compared to the fixed pre-trained model, empowering the application of language models to molecular design tasks.

In Silico Design of New Dual Inhibitors of SARS-CoV-2 MPRO through Ligand- and Structure-Based Methods

The viral main protease is one of the most attractive targets among all key enzymes involved in the life cycle of SARS-CoV-2. Considering its mechanism of action, both the catalytic and dimerization regions could represent crucial sites for modulating its activity. Dual-binding the SARS-CoV-2 main protease inhibitors could arrest the replication process of the virus by simultaneously preventing dimerization and proteolytic activity. To this aim, in the present work, we identified two series' of small molecules with a significant affinity for SARS-CoV-2 M^PRO, by a hybrid virtual screening protocol, combining ligand- and structure-based approaches with multivariate statistical analysis. The Biotarget Predictor Tool was used to filter a large in-house structural database and select a set of benzo[b]thiophene and benzo[b]furan derivatives. ADME properties were investigated, and induced fit docking studies were performed to confirm the DRUDIT prediction. Principal component analysis and docking protocol at the SARS-CoV-2 M^PRO dimerization site enable the identification of compounds 1b,c,i,l and 2i,l as promising drug molecules, showing favorable dual binding site affinity on SARS-CoV-2 M^PRO.

An in-solution snapshot of SARS-COV-2 main protease maturation process and inhibition

The main protease from SARS-CoV-2 (Mpro) is responsible for cleavage of the viral polyprotein. Mpro self-processing is called maturation, and it is crucial for enzyme dimerization and activity. Here we use C145S Mpro to study the structure and dynamics of N-terminal cleavage in solution. Native mass spectroscopy analysis shows that mixed oligomeric states are composed of cleaved and uncleaved particles, indicating that N-terminal processing is not critical for dimerization. A 3.5 Å cryo-EM structure provides details of Mpro N-terminal cleavage outside the constrains of crystal environment. We show that different classes of inhibitors shift the balance between oligomeric states. While non-covalent inhibitor MAT-POS-e194df51-1 prevents dimerization, the covalent inhibitor nirmatrelvir induces the conversion of monomers into dimers, even with intact N-termini. Our data indicates that the Mpro dimerization is triggered by induced fit due to covalent linkage during substrate processing rather than the N-terminal processing.

Repositioning of anti-dengue compounds against SARS-CoV-2 as viral polyprotein processing inhibitor

A therapy for COVID-19 (Coronavirus Disease 19) caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) remains elusive due to the lack of an effective antiviral therapeutic molecule. The SARS-CoV-2 main protease (Mpro), which plays a vital role in the viral life cycle, is one of the most studied and validated drug targets. In Several prior studies, numerous possible chemical entities were proposed as potential Mpro inhibitors; however, most failed at various stages of drug discovery. Repositioning of existing antiviral compounds accelerates the discovery and development of potent therapeutic molecules. Hence, this study examines the applicability of anti-dengue compounds against the substrate binding site of Mpro for disrupting its polyprotein processing mechanism. An in-silico structure-based virtual screening approach is applied to screen 330 experimentally validated anti-dengue compounds to determine their affinity to the substrate binding site of Mpro. This study identified the top five compounds (CHEMBL1940602, CHEMBL2036486, CHEMBL3628485, CHEMBL200972, CHEMBL2036488) that showed a high affinity to Mpro with a docking score > -10.0 kcal/mol. The best-docked pose of these compounds with Mpro was subjected to 100 ns molecular dynamic (MD) simulation followed by MM/GBSA binding energy. This showed the maximum stability and comparable ΔG binding energy against the reference compound (X77 inhibitor). Overall, we repurposed the reported anti-dengue compounds against SARS-CoV-2-Mpro to impede its polyprotein processing for inhibiting SARS-CoV-2 infection.

Targeting SARS-CoV-2 Main Protease for Treatment of COVID-19: Covalent Inhibitors Structure-Activity Relationship Insights and Evolution Perspectives

The viral main protease is one of the most attractive targets among all key enzymes involved in the SARS-CoV-2 life cycle. Covalent inhibition of the cysteine145 of SARS-CoV-2 MPRO with selective antiviral drugs will arrest the replication process of the virus without affecting human catalytic pathways. In this Perspective, we analyzed the in silico, in vitro, and in vivo data of the most representative examples of covalent SARS-CoV-2 MPRO inhibitors reported in the literature to date. In particular, the studied molecules were classified into eight different categories according to their reactive electrophilic warheads, highlighting the differences between their reversible/irreversible mechanism of inhibition. Furthermore, the analyses of the most recurrent pharmacophoric moieties and stereochemistry of chiral carbons were reported. The analyses of noncovalent and covalent in silico protocols, provided in this Perspective, would be useful for the scientific community to discover new and more efficient covalent SARS-CoV-2 MPRO inhibitors.

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.

Conserved coronavirus proteins as targets of broad-spectrum antivirals

Coronaviruses are a class of single-stranded, positive-sense RNA viruses that have caused three major outbreaks over the past two decades: Middle East respiratory syndrome-related coronavirus (MERS-CoV), severe acute respiratory syndrome coronavirus (SARS-CoV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). All outbreaks have been associated with significant morbidity and mortality. In this study, we have identified and explored conserved binding sites in the key coronavirus proteins for the development of broad-spectrum direct acting anti-coronaviral compounds and validated the significance of this conservation for drug discovery with existing experimental data. We have identified four coronaviral proteins with highly conserved binding site sequence and 3D structure similarity: PLpro, Mpro, nsp10-nsp16 complex(methyltransferase), and nsp15 endoribonuclease. We have compiled all available experimental data for known antiviral medications inhibiting these targets and identified compounds active against multiple coronaviruses. The identified compounds representing potential broad-spectrum antivirals include: GC376, which is active against six viral Mpro (out of six tested, as described in research literature); mycophenolic acid, which is active against four viral PLpro (out of four); and emetine, which is active against four viral RdRp (out of four). The approach described in this study for coronaviruses, which combines the assessment of sequence and structure conservation across a viral family with the analysis of accessible chemical structure - antiviral activity data, can be explored for the development of broad-spectrum drugs for multiple viral families.

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.

Genetic Surveillance of SARS-CoV-2 M pro Reveals High Sequence and Structural Conservation Prior to the Introduction of Protease Inhibitor Paxlovid

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to represent a global health emergency as a highly transmissible, airborne virus. An important coronaviral drug target for treatment of COVID-19 is the conserved main protease (M^pro). Nirmatrelvir is a potent M^pro inhibitor and the antiviral component of Paxlovid. The significant viral sequencing effort during the ongoing COVID-19 pandemic represented a unique opportunity to assess potential nirmatrelvir escape mutations from emerging variants of SARS-CoV-2. To establish the baseline mutational landscape of M^pro prior to the introduction of M^pro inhibitors, M^pro sequences and its cleavage junction regions were retrieved from ~4,892,000 high-quality SARS-CoV-2 genomes in the open-access Global Initiative on Sharing Avian Influenza Data (GISAID) database. Any mutations identified from comparison to the reference sequence (Wuhan-Hu-1) were catalogued and analyzed. Mutations at sites key to nirmatrelvir binding and protease functionality (e.g., dimerization sites) were still rare. Structural comparison of M^pro also showed conservation of key nirmatrelvir contact residues across the extended Coronaviridae family (α-, β-, and γ-coronaviruses). Additionally, we showed that over time, the SARS-CoV-2 M^pro enzyme remained under purifying selection and was highly conserved relative to the spike protein. Now, with the emergency use authorization (EUA) of Paxlovid and its expected widespread use across the globe, it is essential to continue large-scale genomic surveillance of SARS-CoV-2 M^pro evolution. This study establishes a robust analysis framework for monitoring emergent mutations in millions of virus isolates, with the goal of identifying potential resistance to present and future SARS-CoV-2 antivirals.

The Functional Landscape of SARS-CoV-2 3CL Protease

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) as the etiologic agent of COVID-19 (coronavirus disease 2019) has drastically altered life globally. Numerous efforts have been placed on the development of therapeutics to treat SARS-CoV-2 infection. One particular target is the 3CL protease (3CL ^pro ), which holds promise as it is essential to the virus and highly conserved among coronaviruses, suggesting that it may be possible to find broad inhibitors that treat not just SARS-CoV-2 but other coronavirus infections as well. While the 3CL protease has been studied by many groups for SARS-CoV-2 and other coronaviruses, our understanding of its tolerance to mutations is limited, knowledge which is particularly important as 3CL protease inhibitors become utilized clinically. Here, we develop a yeast-based deep mutational scanning approach to systematically profile the activity of all possible single mutants of the SARS-CoV-2 3CL ^pro , and validate our results both in yeast and in authentic viruses. We reveal that the 3CL ^pro is highly malleable and is capable of tolerating mutations throughout the protein, including within the substrate binding pocket. Yet, we also identify specific residues that appear immutable for function of the protease, suggesting that these interactions may be novel targets for the design of future 3CL ^pro inhibitors. Finally, we utilize our screening results as a basis to identify E166V as a resistance-conferring mutation against the therapeutic 3CL ^pro inhibitor, nirmatrelvir, in clinical use. Collectively, the functional map presented herein may serve as a guide for further understanding of the biological properties of the 3CL protease and for drug development for current and future coronavirus pandemics.

Hydroxamate and thiosemicarbazone: Two highly promising scaffolds for the development of SARS-CoV-2 antivirals

The emerging COVID-19 pandemic generated by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has severely threatened human health. The main protease (Mpro) of SARS-CoV-2 is promising target for antiviral drugs, which plays a vital role for viral duplication. Development of the inhibitor against Mpro is an ideal strategy to combat COVID-19. In this work, twenty-three hydroxamates 1a-i and thiosemicarbazones 2a-n were identified by FRET screening to be the potent inhibitors of Mpro, which exhibited more than 94% (except 1c) and more than 69% inhibition, and an IC50 value in the range of 0.12-31.51 and 2.43-34.22 μM, respectively. 1a and 2b were found to be the most effective inhibitors in the hydroxamates and thiosemicarbazones, with an IC50 of 0.12 and 2.43 μM, respectively. Enzyme kinetics, jump dilution and thermal shift assays revealed that 2b is a competitive inhibitor of Mpro, while 1a is a time-dependently inhibitor; 2b reversibly but 1a irreversibly bound to the target; the binding of 2b increased but 1a decreased stability of the target, and DTT assays indicate that 1a is the promiscuous cysteine protease inhibitor. Cytotoxicity assays showed that 1a has low, but 2b has certain cytotoxicity on the mouse fibroblast cells (L929). Docking studies revealed that the benzyloxycarbonyl carbon of 1a formed thioester with Cys145, while the phenolic hydroxyl oxygen of 2b formed H-bonds with Cys145 and Asn142. This work provided two promising scaffolds for the development of Mpro inhibitors to combat COVID-19.

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

With the continual evolution of new strains of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) that are more virulent, transmissible, and able to evade current vaccines, there is an urgent need for effective anti-viral drugs. The SARS-CoV-2 main protease (Mpro) is a leading target for drug design due to its conserved and indispensable role in the viral life cycle. Drugs targeting Mpro appear promising but will elicit selection pressure for resistance. To understand resistance potential in Mpro, we performed a comprehensive mutational scan of the protease that analyzed the function of all possible single amino acid changes. We developed three separate high throughput assays of Mpro function in yeast, based on either the ability of Mpro variants to cleave at a defined cut-site or on the toxicity of their expression to yeast. We used deep sequencing to quantify the functional effects of each variant in each screen. The protein fitness landscapes from all three screens were strongly correlated, indicating that they captured the biophysical properties critical to Mpro function. The fitness landscapes revealed a non-active site location on the surface that is extremely sensitive to mutation, making it a favorable location to target with inhibitors. In addition, we found a network of critical amino acids that physically bridge the two active sites of the Mpro dimer. The clinical variants of Mpro were predominantly functional in our screens, indicating that Mpro is under strong selection pressure in the human population. Our results provide predictions of mutations that will be readily accessible to Mpro evolution and that are likely to contribute to drug resistance. This complete mutational guide of Mpro can be used in the design of inhibitors with reduced potential of evolving viral resistance.

Thermodynamic and structural insights into the repurposing of drugs that bind to SARS-CoV-2 main protease

Although researchers have been working tirelessly since the COVID-19 outbreak, so far only three drugs - remdesivir, ronapreve and molnupiravir - have been approved for use in some countries which directly target the SARS-CoV-2 virus. Given the slow pace and substantial costs of new drug discovery and development, together with the urgency of the matter, repurposing of existing drugs for the ongoing disease is an attractive proposition. In a recent study, a high-throughput X-ray crystallographic screen was performed for a selection of drugs which have been approved or are in clinical trials. Thirty-seven compounds have been identified from drug libraries all of which bind to the SARS-CoV-2 main protease (3CL^pro). In the current study, we use molecular dynamics simulation and an ensemble-based free energy approach, namely, enhanced sampling of molecular dynamics with approximation of continuum solvent (ESMACS), to investigate a subset of the aforementioned compounds. The drugs studied here are highly diverse, interacting with different binding sites and/or subsites of 3CL^pro. The predicted free energies are compared with experimental results wherever they are available and they are found to be in excellent agreement. Our study also provides detailed energetic insights into the nature of the associated drug-protein binding, in turn shedding light on the design and discovery of potential drugs.

Computational Identification of Possible Allosteric Sites and Modulators of the SARS-CoV-2 Main Protease

In this study, we target the main protease (M^pro) of the SARS-CoV-2 virus as it is a crucial enzyme for viral replication. Herein, we report three plausible allosteric sites on M^pro that can expand structure-based drug discovery efforts for new M^pro inhibitors. To find these sites, we used mixed-solvent molecular dynamics (MixMD) simulations, an efficient computational protocol that finds binding hotspots through mapping the surface of unbound proteins with 5% cosolvents in water. We have used normal mode analysis to support our claim of allosteric control for these sites. Further, we have performed virtual screening against the sites with 361 hits from M^pro screenings available through the National Center for Advancing Translational Sciences (NCATS). We have identified the NCATS inhibitors that bind to the remote sites better than the active site of M^pro, and we propose these molecules may be allosteric regulators of the system. After identifying our sites, new X-ray crystal structures were released that show fragment molecules in the sites we found, supporting the notion that these sites are accurate and druggable.

Machine learning prediction of 3CLpro SARS-CoV-2 docking scores

Molecular docking results of two training sets containing 866 and 8,696 compounds were used to train three different machine learning (ML) approaches. Neural network approaches according to Keras and TensorFlow libraries and the gradient boosted decision trees approach of XGBoost were used with DScribe’s Smooth Overlap of Atomic Positions molecular descriptors. In addition, neural networks using the SchNetPack library and descriptors were used. The ML performance was tested on three different sets, including compounds for future organic synthesis. The final evaluation of the ML predicted docking scores was based on the ZINC in vivo set, from which 1,200 compounds were randomly selected with respect to their size. The results obtained showed a consistent ML prediction capability of docking scores, and even though compounds with more than 60 atoms were found slightly overestimated they remain valid for a subsequent evaluation of their drug repurposing suitability.

Discovery of SARS-CoV-2 Mpro peptide inhibitors from modelling substrate and ligand binding

The main protease (Mpro) of SARS-CoV-2 is central to viral maturation and is a promising drug target, but little is known about structural aspects of how it binds to its 11 natural cleavage sites. We used biophysical and crystallographic data and an array of biomolecular simulation techniques, including automated docking, molecular dynamics (MD) and interactive MD in virtual reality, QM/MM, and linear-scaling DFT, to investigate the molecular features underlying recognition of the natural Mpro substrates. We extensively analysed the subsite interactions of modelled 11-residue cleavage site peptides, crystallographic ligands, and docked COVID Moonshot-designed covalent inhibitors. Our modelling studies reveal remarkable consistency in the hydrogen bonding patterns of the natural Mpro substrates, particularly on the N-terminal side of the scissile bond. They highlight the critical role of interactions beyond the immediate active site in recognition and catalysis, in particular plasticity at the S2 site. Building on our initial Mpro-substrate models, we used predictive saturation variation scanning (PreSaVS) to design peptides with improved affinity. Non-denaturing mass spectrometry and other biophysical analyses confirm these new and effective 'peptibitors' inhibit Mpro competitively. Our combined results provide new insights and highlight opportunities for the development of Mpro inhibitors as anti-COVID-19 drugs.

Inter-Subunit Dynamics Controls Tunnel Formation During the Oxygenation Process in Hemocyanin Hexamers

Hemocyanin from horseshoe crab in its active form is a homo-hexameric protein. It exists in open and closed conformations when transitioning between deoxygenated and oxygenated states. Here, we present a detailed dynamic atomistic investigation of the oxygenated and deoxygenated states of the hexameric hemocyanin using explicit solvent molecular dynamics simulations. We focus on the variation in solvent cavities and the formation of tunnels in the two conformational states. By employing principal component analysis and CVAE-based deep learning, we are able to differentiate between the dynamics of the deoxy- and oxygenated states of hemocyanin. Finally, our results identify the deoxygenated open conformation, which adopts a stable, closed conformation after the oxygenation process.

The Role of Hydrophobic Nodes in the Dynamics of Class A β-Lactamases

Class A β-lactamases are known for being able to rapidly gain broad spectrum catalytic efficiency against most β-lactamase inhibitor combinations as a result of elusively minor point mutations. The evolution in class A β-lactamases occurs through optimisation of their dynamic phenotypes at different timescales. At long-timescales, certain conformations are more catalytically permissive than others while at the short timescales, fine-grained optimisation of free energy barriers can improve efficiency in ligand processing by the active site. Free energy barriers, which define all coordinated movements, depend on the flexibility of the secondary structural elements. The most highly conserved residues in class A β-lactamases are hydrophobic nodes that stabilize the core. To assess how the stable hydrophobic core is linked to the structural dynamics of the active site, we carried out adaptively sampled molecular dynamics (MD) simulations in four representative class A β-lactamases (KPC-2, SME-1, TEM-1, and SHV-1). Using Markov State Models (MSM) and unsupervised deep learning, we show that the dynamics of the hydrophobic nodes is used as a metastable relay of kinetic information within the core and is coupled with the catalytically permissive conformation of the active site environment. Our results collectively demonstrate that the class A enzymes described here, share several important dynamic similarities and the hydrophobic nodes comprise of an informative set of dynamic variables in representative class A β-lactamases.