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

3-Chymotrypsin-like Protease (3CLpro) of SARS-CoV-2: Validation as a Molecular Target, Proposal of a Novel Catalytic Mechanism, and Inhibitors in Preclinical and Clinical Trials

Proteases represent common targets in combating infectious diseases, including COVID-19. The 3-chymotrypsin-like protease (3CLpro) is a validated molecular target for COVID-19, and it is key for developing potent and selective inhibitors for inhibiting viral replication of SARS-CoV-2. In this review, we discuss structural relationships and diverse subsites of 3CLpro, shedding light on the pivotal role of dimerization and active site architecture in substrate recognition and catalysis. Our analysis of bioinformatics and other published studies motivated us to investigate a novel catalytic mechanism for the SARS-CoV-2 polyprotein cleavage by 3CLpro, centering on the triad mechanism involving His41-Cys145-Asp187 and its indispensable role in viral replication. Our hypothesis is that Asp187 may participate in modulating the pKa of the His41, in which catalytic histidine may act as an acid and/or a base in the catalytic mechanism. Recognizing Asp187 as a crucial component in the catalytic process underscores its significance as a fundamental pharmacophoric element in drug design. Next, we provide an overview of both covalent and non-covalent inhibitors, elucidating advancements in drug development observed in preclinical and clinical trials. By highlighting various chemical classes and their pharmacokinetic profiles, our review aims to guide future research directions toward the development of highly selective inhibitors, underscore the significance of 3CLpro as a validated therapeutic target, and propel the progression of drug candidates through preclinical and clinical phases.

Cyclic β2,3-amino acids improve the serum stability of macrocyclic peptide inhibitors targeting the SARS-CoV-2 main protease

Due to their constrained conformations, cyclic β2,3-amino acids (cβAA) are key building blocks that can fold peptides into compact and rigid structures, improving peptidase resistance and binding affinity to target proteins, due to their constrained conformations. Although the translation efficiency of cβAAs is generally low, our engineered tRNA, referred to as tRNAPro1E2, enabled efficient incorporation of cβAAs into peptide libraries using the flexible in vitro translation (FIT) system. Here we report on the design and application of a macrocyclic peptide library incorporating 3 kinds of cβAAs: (1R,2S)-2-aminocyclopentane carboxylic acid (β1), (1S,2S)-2-aminocyclohexane carboxylic acid (β2), and (1R,2R)-2-aminocyclopentane carboxylic acid. This library was applied to an in vitro selection against the SARS-CoV-2 main protease (Mpro). The resultant peptides, BM3 and BM7, bearing one β2 and two β1, exhibited potent inhibitory activities with IC50 values of 40 and 20 nM, respectively. BM3 and BM7 also showed remarkable serum stability with half-lives of 48 and >168 h, respectively. Notably, BM3A and BM7A, wherein the cβAAs were substituted with alanine, lost their inhibitory activities against Mpro and displayed substantially shorter serum half-lives. This observation underscores the significant contribution of cβAA to the activity and stability of peptides. Overall, our results highlight the potential of cβAA in generating potent and highly stable macrocyclic peptides with drug-like properties.

Antiviral peptides inhibiting the main protease of SARS-CoV-2 investigated by computational screening and in vitro protease assay

The main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) plays an important role in viral replication and transcription and received great attention as a vital target for drug/peptide development. Therapeutic agents such as small-molecule drugs or peptides that interact with the Cys-His present in the catalytic site of Mpro are an efficient way to inhibit the protease. Although several emergency-approved vaccines showed good efficacy and drastically dropped the infection rate, evolving variants are still infecting and killing millions of people globally. While a small-molecule drug (Paxlovid) received emergency approval, small-molecule drugs have low target specificity and higher toxicity. Besides small-molecule drugs, peptide therapeutics are thus gaining increasing popularity as they are easy to synthesize and highly selective and have limited side effects. In this study, we investigated the therapeutic value of 67 peptides targeting Mpro using molecular docking. Subsequently, molecular dynamics (MD) simulations were implemented on eight protein-peptide complexes to obtain molecular-level information on the interaction between these peptides and the Mpro active site, which revealed that temporin L, indolicidin, and lymphocytic choriomeningitis virus (LCMV) GP1 are the best candidates in terms of stability, interaction, and structural compactness. These peptides were synthesized using the solid-phase peptide synthesis protocol, purified by reversed-phase high-performance liquid chromatography (RP-HPLC), and authenticated by mass spectrometry (MS). The in vitro fluorometric Mpro activity assay was used to validate the computational results, where temporin L and indolicidin were observed to be very active against SARS-CoV-2 Mpro with IC50 values of 38.80 and 87.23 μM, respectively. A liquid chromatography-MS (LC-MS) assay was developed, and the IC50 value of temporin L was measured at 23.8 μM. The solution-state nuclear magnetic resonance (NMR) structure of temporin L was determined in the absence of sodium dodecyl sulfate (SDS) micelles and was compared to previous temporin structures. This combined investigation provides critical insights and assists us to further develop peptide inhibitors of SARS-CoV-2 Mpro through structural guided investigation.

Studies on the selectivity of the SARS-CoV-2 papain-like protease reveal the importance of the P2' proline of the viral polyprotein

The SARS-CoV-2 papain-like protease (PLpro) is an antiviral drug target that catalyzes the hydrolysis of the viral polyproteins pp1a/1ab, so releasing the non-structural proteins (nsps) 1-3 that are essential for the coronavirus lifecycle. The LXGG↓X motif in pp1a/1ab is crucial for recognition and cleavage by PLpro. We describe molecular dynamics, docking, and quantum mechanics/molecular mechanics (QM/MM) calculations to investigate how oligopeptide substrates derived from the viral polyprotein bind to PLpro. The results reveal how the substrate sequence affects the efficiency of PLpro-catalyzed hydrolysis. In particular, a proline at the P2' position promotes catalysis, as validated by residue substitutions and mass spectrometry-based analyses. Analysis of PLpro catalyzed hydrolysis of LXGG motif-containing oligopeptides derived from human proteins suggests that factors beyond the LXGG motif and the presence of a proline residue at P2' contribute to catalytic efficiency, possibly reflecting the promiscuity of PLpro. The results will help in identifying PLpro substrates and guiding inhibitor design.

Predicting potential SARS-CoV-2 mutations of concern via full quantum mechanical modelling

Ab initio quantum mechanical models can characterize and predict intermolecular binding, but only recently have models including more than a few hundred atoms gained traction. Here, we simulate the electronic structure for approximately 13 000 atoms to predict and characterize binding of SARS-CoV-2 spike variants to the human ACE2 (hACE2) receptor using the quantum mechanics complexity reduction (QM-CR) approach. We compare four spike variants in our analysis: Wuhan, Omicron, and two Omicron-based variants. To assess binding, we mechanistically characterize the energetic contribution of each amino acid involved, and predict the effect of select single amino acid mutations. We validate our computational predictions experimentally by comparing the efficacy of spike variants binding to cells expressing hACE2. At the time we performed our simulations (December 2021), the mutation A484K which our model predicted to be highly beneficial to ACE2 binding had not been identified in epidemiological surveys; only recently (August 2023) has it appeared in variant BA.2.86. We argue that our computational model, QM-CR, can identify mutations critical for intermolecular interactions and inform the engineering of high-specificity interactors.

Fragment-based screening targeting an open form of the SARS-CoV-2 main protease binding pocket

To identify starting points for therapeutics targeting SARS-CoV-2, the Paul Scherrer Institute and Idorsia decided to collaboratively perform an X-ray crystallographic fragment screen against its main protease. Fragment-based screening was carried out using crystals with a pronounced open conformation of the substrate-binding pocket. Of 631 soaked fragments, a total of 29 hits bound either in the active site (24 hits), a remote binding pocket (three hits) or at crystal-packing interfaces (two hits). Notably, two fragments with a pose that was sterically incompatible with a more occluded crystal form were identified. Two isatin-based electrophilic fragments bound covalently to the catalytic cysteine residue. The structures also revealed a surprisingly strong influence of the crystal form on the binding pose of three published fragments used as positive controls, with implications for fragment screening by crystallography.

Peptidyl nitroalkene inhibitors of main protease rationalized by computational and crystallographic investigations as antivirals against SARS-CoV-2

The coronavirus disease 2019 (COVID-19) pandemic continues to represent a global public health issue. The viral main protease (Mpro) represents one of the most attractive targets for the development of antiviral drugs. Herein we report peptidyl nitroalkenes exhibiting enzyme inhibitory activity against Mpro (Ki: 1-10 μM) good anti-SARS-CoV-2 infection activity in the low micromolar range (EC50: 1-12 μM) without significant toxicity. Additional kinetic studies of compounds FGA145, FGA146 and FGA147 show that all three compounds inhibit cathepsin L, denoting a possible multitarget effect of these compounds in the antiviral activity. Structural analysis shows the binding mode of FGA146 and FGA147 to the active site of the protein. Furthermore, our results illustrate that peptidyl nitroalkenes are effective covalent reversible inhibitors of the Mpro and cathepsin L, and that inhibitors FGA145, FGA146 and FGA147 prevent infection against SARS-CoV-2.

A New Advanced Approach: Design and Screening of Affinity Peptide Ligands Using Computer Simulation Techniques

Peptides acquire target affinity based on the combination of residues in their sequences and the conformation formed by their flexible folding, an ability that makes them very attractive biomaterials in therapeutic, diagnostic, and assay fields. With the development of computer technology, computer-aided design and screening of affinity peptides has become a more efficient and faster method. This review summarizes successful cases of computer-aided design and screening of affinity peptide ligands in recent years and lists the computer programs and online servers used in the process. In particular, the characteristics of different design and screening methods are summarized and categorized to help researchers choose between different methods. In addition, experimentally validated sequences are listed, and their applications are described, providing directions for the future development and application of computational peptide screening and design.

Mass spectrometric assays monitoring the deubiquitinase activity of the SARS-CoV-2 papain-like protease inform on the basis of substrate selectivity and have utility for substrate identification

The SARS-CoV-2 papain-like protease (PLpro) and main protease (Mpro) are nucleophilic cysteine enzymes that catalyze hydrolysis of the viral polyproteins pp1a/1ab. By contrast with Mpro, PLpro is also a deubiquitinase (DUB) that accepts post-translationally modified human proteins as substrates. Here we report studies on the DUB activity of PLpro using synthetic Nε-lysine-branched oligopeptides as substrates that mimic post-translational protein modifications by ubiquitin (Ub) or Ub-like modifiers (UBLs), such as interferon stimulated gene 15 (ISG15). Mass spectrometry (MS)-based assays confirm the DUB activity of isolated recombinant PLpro. They reveal that the sequence of both the peptide fragment derived from the post-translationally modified protein and that derived from the UBL affects PLpro catalysis; the nature of substrate binding in the S sites appears to be more important for catalytic efficiency than binding in the S' sites. Importantly, the results reflect the reported cellular substrate selectivity of PLpro, i.e. human proteins conjugated to ISG15 are better substrates than those conjugated to Ub or other UBLs. The combined experimental and modelling results imply that PLpro catalysis is affected not only by the identity of the substrate residues binding in the S and S' sites, but also by the substrate fold and the conformational dynamics of the blocking loop 2 of the PLpro:substrate complex. Nε-Lysine-branched oligopeptides thus have potential to help the identification of PLpro substrates. More generally, the results imply that MS-based assays with Nε-lysine-branched oligopeptides have potential to monitor catalysis by human DUBs and hence to inform on their substrate preferences.

Upgrading nirmatrelvir to inhibit SARS-CoV-2 Mpro via DeepFrag and free energy calculations

The first oral drug for the treatment of COVID-19, Paxlovid, has been authorized; however, nirmatrelvir, a major component of the drug, is reported to be associated with some side effects. Moreover, the appearance of many novel variants raises concerns about drug resistance, and designing new potent inhibitors to prevent viral replication is thus urgent. In this context, using a hybrid approach combining machine learning (ML) and free energy simulations, 6 compounds obtained by modifying nirmatrelvir were proposed to bind strongly to SARS-CoV-2 Mpro. The structural modification of nirmatrelvir significantly enhances the electrostatic interaction free energy between the protein and ligand and slightly decreases the vdW term. However, the vdW term is the most important factor in controlling the ligand-binding affinity. In addition, the modified nirmatrelvir might be less toxic to the human body than the original inhibitor.

The S1'-S3' Pocket of the SARS-CoV-2 Main Protease Is Critical for Substrate Selectivity and Can Be Targeted with Covalent Inhibitors

The main protease (Mpro ) of SARS-CoV-2 is a well-characterized target for antiviral drug discovery. To date, most antiviral drug discovery efforts have focused on the S4-S1' pocket of Mpro ; however, it is still unclear whether the S1'-S3' pocket per se can serve as a new site for drug discovery. In this study, the S1'-S3' pocket of Mpro was found to differentially recognize viral peptidyl substrates. For instance, S3' in Mpro strongly favors Phe or Trp, and S1' favors Ala. The peptidyl inhibitor D-4-77, which possesses an α-bromoacetamide warhead, was discovered to be a promising inhibitor of Mpro , with an IC50 of 0.95 μM and an antiviral EC50 of 0.49 μM. The Mpro /inhibitor co-crystal structure confirmed the binding mode of the inhibitor to the S1'-S3' pocket and revealed a covalent mechanism. In addition, D-4-77 functions as an immune protectant and suppresses SARS-CoV-2 Mpro -induced antagonism of the host NF-κB innate immune response. These findings indicate that the S1'-S3' pocket of SARS-CoV-2 Mpro is druggable, and that inhibiting SARS-CoV-2 Mpro can simultaneously protect human innate immunity and inhibit virion assembly.

Identification of motif-based interactions between SARS-CoV-2 protein domains and human peptide ligands pinpoint antiviral targets

The virus life cycle depends on host-virus protein-protein interactions, which often involve a disordered protein region binding to a folded protein domain. Here, we used proteomic peptide phage display (ProP-PD) to identify peptides from the intrinsically disordered regions of the human proteome that bind to folded protein domains encoded by the SARS-CoV-2 genome. Eleven folded domains of SARS-CoV-2 proteins were found to bind 281 peptides from human proteins, and affinities of 31 interactions involving eight SARS-CoV-2 protein domains were determined (KD ∼ 7-300 μM). Key specificity residues of the peptides were established for six of the interactions. Two of the peptides, binding Nsp9 and Nsp16, respectively, inhibited viral replication. Our findings demonstrate how high-throughput peptide binding screens simultaneously identify potential host-virus interactions and peptides with antiviral properties. Furthermore, the high number of low-affinity interactions suggest that overexpression of viral proteins during infection may perturb multiple cellular pathways.

An efficient computational protocol for template-based design of peptides that inhibit interactions involving SARS-CoV-2 proteins

The RNA-dependent RNA polymerase (RdRp) complex of SARS-CoV-2 lies at the core of its replication and transcription processes. The interfaces between holo-RdRp subunits are highly conserved, facilitating the design of inhibitors with high affinity for the interaction interface hotspots. We, therefore, take this as a model protein complex for the application of a structural bioinformatics protocol to design peptides that inhibit RdRp complexation by preferential binding at the interface of its core subunit nonstructural protein, nsp12, with accessory factor nsp7. Here, the interaction hotspots of the nsp7-nsp12 subunit of RdRp, determined from a long molecular dynamics trajectory, are used as a template. A large library of peptide sequences constructed from multiple hotspot motifs of nsp12 is screened in-silico to determine sequences with high geometric complementarity and interaction specificity for the binding interface of nsp7 (target) in the complex. Two lead designed peptides are extensively characterized using orthogonal bioanalytical methods to determine their suitability for inhibition of RdRp complexation. Binding affinity of these peptides to accessory factor nsp7, determined using a surface plasmon resonance (SPR) assay, is slightly better than that of nsp12: dissociation constant of 133nM and 167nM, respectively, compared to 473nM for nsp12. A competitive ELISA is used to quantify inhibition of nsp7-nsp12 complexation, with one of the lead peptides giving an IC50 of 25μM . Cell penetrability and cytotoxicity are characterized using a cargo delivery assay and MTT cytotoxicity assay, respectively. Overall, this work presents a proof-of-concept of an approach for rational discovery of peptide inhibitors of SARS-CoV-2 protein-protein interactions.

Computation of Absolute Binding Free Energies for Noncovalent Inhibitors with SARS-CoV-2 Main Protease

Accurate, routine calculation of absolute binding free energies (ABFEs) for protein-ligand complexes remains a key goal of computer-aided drug design since it can enable screening and optimization of drug candidates. For development and testing of related methods, it is important to have high-quality datasets. To this end, from our own experimental studies, we have selected a set of 16 inhibitors of the SARS-CoV-2 main protease (Mpro) with structural diversity and well-distributed BFEs covering a 5 kcal/mol range. There is also minimal structural uncertainty since X-ray crystal structures have been deposited for 12 of the compounds. For methods testing, we report ABFE results from 2 μs molecular dynamics (MD) simulations using free energy perturbation (FEP) theory. The correlation of experimental and computed results is encouraging, with a Pearson's r2 of 0.58 and a Kendall τ of 0.24. The results indicate that current FEP-based ABFE calculations can be used for identification of active compounds (hits). While their accuracy for lead optimization is not yet sufficient, this activity remains addressable in separate lead series by relative BFE calculations.

Crystal structures of main protease (Mpro) mutants of SARS-CoV-2 variants bound to PF-07304814

There is an urgent need to develop effective antiviral drugs to prevent the viral infection caused by constantly circulating SARS-CoV-2 as well as its variants. The main protease (Mpro) of SARS-CoV-2 is a salient enzyme that plays a vital role in viral replication and serves as a fascinating therapeutic target. PF-07304814 is a covalent inhibitor targeting SARS-CoV-2 Mpro with favorable inhibition potency and drug-like properties, thus making it a promising drug candidate for the treatment of COVID-19. We previously solved the structure of PF-07304814 in complex with SARS-CoV-2 Mpro. However, the binding modes of PF-07304814 with Mpros from evolving SARS-CoV-2 variants is under-determined. In the current study, we expressed six Mpro mutants (G15S, K90R, M49I, S46F, V186F, and Y54C) that have been identified in Omicron variants including the recently emerged XBB.1.16 subvariant and solved the crystal structures of PF-07304814 bound to Mpro mutants. Structural analysis provided insight into the key molecular determinants responsible for the interaction between PF-07304814 and these mutant Mpros. Patterns for PF-07304814 to bind with these investigated Mpro mutants and the wild-type Mpro are generally similar but with some differences as revealed by detailed structural comparison. Structural insights presented in this study will inform the development of novel drugs against SARS-CoV-2 and the possible conformation changes of Mpro mutants when bound to an inhibitor.

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.

In vitro selection of macrocyclic peptide inhibitors containing cyclic γ2,4-amino acids targeting the SARS-CoV-2 main protease

γ-Amino acids can play important roles in the biological activities of natural products; however, the ribosomal incorporation of γ-amino acids into peptides is challenging. Here we report how a selection campaign employing a non-canonical peptide library containing cyclic γ^2,4-amino acids resulted in the discovery of very potent inhibitors of the SARS-CoV-2 main protease (M^pro). Two kinds of cyclic γ^2,4-amino acids, cis-3-aminocyclobutane carboxylic acid (γ¹) and (1R,3S)-3-aminocyclopentane carboxylic acid (γ²), were ribosomally introduced into a library of thioether-macrocyclic peptides. One resultant potent M^pro inhibitor (half-maximal inhibitory concentration = 50 nM), GM4, comprising 13 residues with γ¹ at the fourth position, manifests a 5.2 nM dissociation constant. An M^pro:GM4 complex crystal structure reveals the intact inhibitor spans the substrate binding cleft. The γ¹ interacts with the S1' catalytic subsite and contributes to a 12-fold increase in proteolytic stability compared to its alanine-substituted variant. Knowledge of interactions between GM4 and M^pro enabled production of a variant with a 5-fold increase in potency.

The impact of SARS-CoV-2 3CL protease mutations on nirmatrelvir inhibitory efficiency. Computational insights into potential resistance mechanisms

The use of antiviral drugs can promote the appearance of mutations in the target protein that increase the resistance of the virus to the treatment. This is also the case of nirmatrelvir, a covalent inhibitor of the 3CL protease, or main protease, of SARS-CoV-2. In this work we show how the by-residue decomposition of noncovalent interactions established between the drug and the enzyme, in combination with an analysis of naturally occurring mutations, can be used to detect potential mutations in the 3CL protease conferring resistance to nirmatrelvir. We also investigate the consequences of these mutations on the reaction mechanism to form the covalent enzyme-inhibitor complex using QM/MM methods. In particular, we show that the E166V variant of the protease displays smaller binding affinity to nirmatrelvir and larger activation free energy for the formation of the covalent complex, both factors contributing to the observed resistance to the treatment with this drug. The conclusions derived from our work can be used to anticipate the consequences of the introduction of nirmatrelvir in the fitness landscape of the virus and to design new inhibitors adapted to some of the possible resistance mechanisms.

SARS-CoV-2 main protease inhibitors: What is moving in the field of peptides and peptidomimetics?

The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is still affecting people worldwide. Despite the good degree of immunological protection achieved through vaccination, there are still severe cases that require effective antivirals. In this sense, two specific pharmaceutical preparations have been marketed already, the RdRp polymerase inhibitor molnupiravir and the main viral protease inhibitor nirmatrelvir (commercialized as Paxlovid, a combination with ritonavir). Nirmatrelvir is a peptidomimetic acting as orally available, covalent, and reversible inhibitor of SARS-CoV-2 main viral protease. The success of this compound has revitalized the search for new peptide and peptidomimetic protease inhibitors. This highlight collects some selected examples among those recently published in the field of SARS-CoV-2.

Optimization of potential non-covalent inhibitors for the SARS-CoV-2 main protease inspected by a descriptor of the subpocket occupancy

The main protease is regarded as an essential drug target for treating Coronavirus Disease 2019. In the present study, 13 marketed drugs were investigated to explore the possible binding mechanism, utilizing molecular docking, molecular dynamics simulation, and MM-PB(GB)SA binding energy calculations. Our results suggest that fusidic acid, polydatin, SEN-1269, AZD6482, and UNC-2327 have high binding affinities of more than 23 kcal mol^-1. A descriptor was defined for the energetic occupancy of the subpocket, and it was found that S4 had a low occupancy of less than 10% on average. The molecular optimization of ADZ6482 via reinforcement learning algorithms was carried out to screen out three lead compounds, in which slight structural changes give more considerable binding energies and an occupancy of the S4 subpocket of up to 43%. The energetic occupancy could be a useful descriptor for evaluating the local binding affinity for drug design.

Characterizing the ligand-binding affinity toward SARS-CoV-2 Mpro via physics- and knowledge-based approaches

Computational approaches, including physics- and knowledge-based methods, have commonly been used to determine the ligand-binding affinity toward SARS-CoV-2 main protease (Mpro or 3CLpro). Strong binding ligands can thus be suggested as potential inhibitors for blocking the biological activity of the protease. In this context, this paper aims to provide a short review of computational approaches that have recently been applied in the search for inhibitor candidates of Mpro. In particular, molecular docking and molecular dynamics (MD) simulations are usually combined to predict the binding affinity of thousands of compounds. Quantitative structure-activity relationship (QSAR) is the least computationally demanding and therefore can be used for large chemical collections of ligands. However, its accuracy may not be high. Moreover, the quantum mechanics/molecular mechanics (QM/MM) method is most commonly used for covalently binding inhibitors, which also play an important role in inhibiting the activity of SARS-CoV-2. Furthermore, machine learning (ML) models can significantly increase the searching space of ligands with high accuracy for binding affinity prediction. Physical insights into the binding process can then be confirmed via physics-based calculations. Integration of ML models into computational chemistry provides many more benefits and can lead to new therapies sooner.

Mechanistic investigation of SARS-CoV-2 main protease to accelerate design of covalent inhibitors

Targeted covalent inhibition represents one possible strategy to block the function of SARS-CoV-2 Main Protease (M^PRO), an enzyme that plays a critical role in the replication of the novel SARS-CoV-2. Toward the design of covalent inhibitors, we built a covalent inhibitor dataset using deep learning models followed by high throughput virtual screening of these candidates against M^PRO. Two top-ranking inhibitors were selected for mechanistic investigations-one with an activated ester warhead that has a piperazine core and the other with an acrylamide warhead. Specifically, we performed a detailed analysis of the free energetics of covalent inhibition by hybrid quantum mechanics/molecular mechanics simulations. Cleavage of a fragment of the non-structured protein (NSP) from the SARS-CoV-2 genome was also simulated for reference. Simulations show that both candidates form more stable enzyme-inhibitor (E-I) complexes than the chosen NSP. It was found that both the NSP fragment and the activated ester inhibitor react with CYS145 of M^PRO in a concerted manner, whereas the acrylamide inhibitor follows a stepwise mechanism. Most importantly, the reversible reaction and the subsequent hydrolysis reaction from E-I complexes are less probable when compared to the reactions with an NSP fragment, showing promise for these candidates to be the base for efficient M^PRO inhibitors.

Non-covalent cyclic peptides simultaneously targeting Mpro and NRP1 are highly effective against Omicron BA.2.75

Available vaccine-based immunity may at high risk of being evaded due to substantial mutations in the variant Omicron. The main protease (Mpro) of SARS-CoV-2 and human neuropilin-1 (NRP1), two less mutable proteins, have been reported to be crucial for SARS-CoV-2 replication and entry into host cells, respectively. Their dual blockade may avoid vaccine failure caused by continuous mutations of the SARS-CoV-2 genome and exert synergistic antiviral efficacy. Herein, four cyclic peptides non-covalently targeting both Mpro and NRP1 were identified using virtual screening. Among them, MN-2 showed highly potent affinity to Mpro (K_d = 18.2 ± 1.9 nM) and NRP1 (K_d = 12.3 ± 1.2 nM), which was about 3,478-fold and 74-fold stronger than that of the positive inhibitors Peptide-21 and EG3287. Furthermore, MN-2 exhibited significant inhibitory activity against Mpro and remarkable anti-infective activity against the pseudotyped variant Omicron BA.2.75 without obvious cytotoxicity. These data demonstrated that MN-2, a novel non-covalent cyclic peptide, is a promising agent against Omicron BA.2.75.

Ultrafast one-minute electronic detection of SARS-CoV-2 infection by 3CLpro enzymatic activity in untreated saliva samples

Since its onset in December 2019, severe acute respiratory syndrome coronavirus 2, SARS-CoV-2, has caused over 6.5 million deaths worldwide as of October 2022. Attempts to curb viral transmission rely heavily on reliable testing to detect infections since a large number of transmissions are carried through asymptomatic individuals. Many available detection methods fall short in terms of reliability or point-of-care applicability. Here, we report an electrochemical approach targeting a viral proteolytic enzyme, 3CLpro, as a marker of active infection. We detect proteolytic activity directly from untreated saliva within one minute of sample incubation using a reduction-oxidation pH indicator. Importantly, clinical tests of saliva samples from 50 subjects show accurate detection of SARS-CoV-2, with high sensitivity and specificity, validated by PCR testing. These, coupled with our platform's ultrafast detection, simplicity, low cost and point-of-care compatibility, make it a promising method for the real-world SARS-CoV-2 mass-screening.

Dual-targeting cyclic peptides of receptor-binding domain (RBD) and main protease (Mpro) as potential drug leads for the treatment of SARS-CoV-2 infection

The receptor-binding domain (RBD) and the main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) play a crucial role in the entry and replication of viral particles, and co-targeting both of them could be an attractive approach for the treatment of SARS-CoV-2 infection by setting up a "double lock" in the viral lifecycle. However, few dual RBD/Mpro-targeting agents have been reported. Here, four novel RBD/Mpro dual-targeting peptides, termed as MRs 1-4, were discovered by an integrated virtual screening scheme combining molecular docking-based screening and molecular dynamics simulation. All of them possessed nanomolar binding affinities to both RBD and Mpro ranging from 14.4 to 39.2 nM and 22.5-40.4 nM, respectively. Further pseudovirus infection assay revealed that the four selected peptides showed >50% inhibition against SARS-CoV-2 pseudovirus at a concentration of 5 µM without significant cytotoxicity to host cells. This study leads to the identification of a class of dual RBD/Mpro-targeting agents, which may be developed as potential and effective SARS-CoV-2 therapeutics.

Structural insights into Nirmatrelvir (PF-07321332)-3C-like SARS-CoV-2 protease complexation: a ligand Gaussian accelerated molecular dynamics study

Coronavirus 3C-like protease (3CLpro) is found in SARS-CoV-2 virus, which causes COVID-19. 3CLpro controls virus replication and is a major target for target-based antiviral discovery. As reported by Pfizer, Nirmatrelvir (PF-07321332) is a competitive protein inhibitor and a clinical candidate for orally delivered medication. However, the binding mechanisms between Nirmatrelvir and 3CLpro complex structures remain unknown. This study incorporated ligand Gaussian accelerated molecular dynamics, the one-dimensional and two-dimensional potential of mean force, normal molecular dynamics, and Kramers' rate theory to determine the binding and dissociation rate constants (k_off and k_on) associated with the binding of the 3CLpro protein to the Nirmatrelvir inhibitor. The proposed approach addresses the challenges in designing small-molecule antiviral drugs.

Probing the mutational landscape of the SARS-CoV-2 spike protein via quantum mechanical modeling of crystallographic structures

We employ a recently developed complexity-reduction quantum mechanical (QM-CR) approach, based on complexity reduction of density functional theory calculations, to characterize the interactions of the SARS-CoV-2 spike receptor binding domain (RBD) with ACE2 host receptors and antibodies. QM-CR operates via ab initio identification of individual amino acid residue's contributions to chemical binding and leads to the identification of the impact of point mutations. Here, we especially focus on the E484K mutation of the viral spike protein. We find that spike residue 484 hinders the spike's binding to the human ACE2 receptor (hACE2). In contrast, the same residue is beneficial in binding to the bat receptor Rhinolophus macrotis ACE2 (macACE2). In agreement with empirical evidence, QM-CR shows that the E484K mutation allows the spike to evade categories of neutralizing antibodies like C121 and C144. The simulation also shows how the Delta variant spike binds more strongly to hACE2 compared to the original Wuhan strain, and predicts that a E484K mutation can further improve its binding. Broad agreement between the QM-CR predictions and experimental evidence supports the notion that ab initio modeling has now reached the maturity required to handle large intermolecular interactions central to biological processes.

Label-free Sensing of Main Protease Activity of SARS-CoV-2 with an Aerolysin Nanopore

The main protease (M pro ), which is highly conserved and plays a critical role in the replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a natural biomarker for SARS-CoV-2. Accurate assessment of the M pro activity is crucial for the detection of SARS-CoV-2. Herein, we report a nanopore-based sensing strategy that uses an enzyme-catalyzed cleavage reaction of a peptide substrate to measure the M pro  activity. The peptide was specifically cleaved by the M pro , thereby releasing the output products that, when translocated through aerolysin, quantitatively produced the signature current events. The proposed method exhibited high sensitivity, allowing the detection of M pro concentrations as low as 1 nM without the use of any signal amplification techniques. This simple, convenient, and label-free nanopore assay may expand the diagnostic tools for viruses.

Identification and validation of novel microtubule suppressors with an imidazopyridine scaffold through structure-based virtual screening and docking

Targeting the colchicine binding site of α/β tubulin microtubules can lead to suppression of microtubule dynamics, cell cycle arrest and apoptosis. Therefore, the development of microtubule (MT) inhibitors is considered a promising route to anticancer agents. Our approach to identify novel scaffolds as MT inhibitors depends on a 3D-structure-based pharmacophore approach and docking using three programs MOE, Autodock and BUDE (Bristol University Docking Engine) to screen a library of virtual compounds. From this work we identified the compound 7-(3-hydroxy-4-methoxy-phenyl)-3-(3-trifluoromethyl-phenyl)-6,7-dihydro-3H-imidazo[4,5-b]pyridin-5-ol (6) as a novel inhibitor scaffold. This compound inhibited several types of cancer cell proliferation at low micromolar concentrations with low toxicity. Compound 6 caused cell cycle arrest in the G2/M phase and blocked tubulin polymerization at low micromolar concentration (IC₅₀ = 6.1 ±0.1 μM), inducing apoptosis via activation of caspase 9, increasing the level of the pro-apoptotic protein Bax and decreasing the level of the anti-apoptotic protein Bcl2. In summary, our approach identified a lead compound with potential antimitotic and antiproliferative activity.

Identification of a Dual Inhibitor of Secreted Phospholipase A2 (GIIA sPLA2) and SARS-CoV-2 Main Protease

The development of novel agents to combat COVID-19 is of high importance. SARS-CoV-2 main protease (M^pro) is a highly attractive target for the development of novel antivirals and a variety of inhibitors have already been developed. Accumulating evidence on the pathobiology of COVID-19 has shown that lipids and lipid metabolizing enzymes are critically involved in the severity of the infection. The purpose of the present study was to identify an inhibitor able to simultaneously inhibit both SARS-CoV-2 M^pro and phospholipase A₂ (PLA₂), an enzyme which plays a significant role in inflammatory diseases. Evaluating several PLA₂ inhibitors, we demonstrate that the previously known potent inhibitor of Group IIA secretory PLA₂, GK241, may also weakly inhibit SARS-CoV-2 M^pro. Molecular mechanics docking and molecular dynamics calculations shed light on the interactions between GK241 and SARS-CoV-2 M^pro. 2-Oxoamide GK241 may represent a lead molecular structure for the development of dual PLA₂ and SARS-CoV-2 M^pro inhibitors.

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 (M^pro) of SARS-CoV-2 is promising target for antiviral drugs, which plays a vital role for viral duplication. Development of the inhibitor against M^pro 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 M^pro, 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 M^pro, 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 M^pro inhibitors to combat COVID-19.

The emerging potential of interactive virtual reality in drug discovery

INTRODUCTION

The potential of virtual reality (VR) to contribute to drug design and development has been recognized for many years. A recent advance is to use VR not only to visualize and interact with molecules, but also to interact with molecular dynamics simulations 'on the fly' (interactive molecular dynamics in VR, IMD-VR), which is useful for flexible docking and examining binding processes and conformational changes.

AREAS COVERED

The authors use the term 'interactive VR' to refer to software where interactivity is an inherent part of the user VR experience e.g. in making structural modifications or interacting with a physically rigorous molecular dynamics (MD) simulation, as opposed to using VR controllers to rotate and translate the molecule for enhanced visualization. Here, they describe these methods and their application to problems relevant to drug discovery, highlighting the possibilities that they offer in this arena.

EXPERT OPINION

The ease of viewing and manipulating molecular structures and dynamics, using accessible VR hardware, and the ability to modify structures on the fly (e.g. adding or deleting atoms) - and for groups of researchers to work together in the same virtual environment - makes modern interactive VR a valuable tool to add to the armory of drug design and development methods.

Primer for Designing Main Protease (Mpro) Inhibitors of SARS-CoV-2

The COVID-19 outbreak has been devastating, with hundreds of millions of infections and millions of deaths reported worldwide. In response, the application of structure-activity relationships (SAR) upon experimentally validated inhibitors of SARS-CoV-2 main protease (Mpro) may provide an avenue for the identification of new lead compounds active against COVID-19. Upon the basis of information gleaned from a combination of reported crystal structures and the docking of experimentally validated inhibitors, four "rules" for designing potent Mpro inhibitors have been proposed. The aim here is to guide medicinal chemists toward the most probable hits and to provide guidance on repurposing available structures as Mpro inhibitors. Experimental examination of our own previously reported inhibitors using the four "rules" identified a potential lead compound, the cathepsin inhibitor GB111-NH2, that was 2.3 times more potent than SARS-CoV-2 Mpro inhibitor N3.

Computational design of stapled peptide inhibitor against SARS‐CoV ‐2 receptor binding domain

Since its first detection in 2019, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS‐CoV‐2) has been the cause of millions of deaths worldwide. Despite the development and administration of different vaccines, the situation is still worrisome as the virus is constantly mutating to produce newer variants some of which are highly infectious. This raises an urgent requirement to understand the infection mechanism and thereby design therapeutic‐based treatment for COVID‐19. The gateway of the virus to the host cell is mediated by the binding of the receptor binding domain (RBD) of the virus spike protein to the angiotensin‐converting enzyme 2 (ACE2) of the human cell. Therefore, the RBD of SARS‐CoV‐2 can be used as a target to design therapeutics. The α1 helix of ACE2, which forms direct contact with the RBD surface, has been used as a template in the current study to design stapled peptide therapeutics. Using computer simulation, the mechanism and thermodynamics of the binding of six stapled peptides with RBD have been estimated. Among these, the one with two lactam stapling agents has shown binding affinity, sufficient to overcome RBD‐ACE2 binding. Analyses of the mechanistic detail reveal that a reorganization of amino acids at the RBD‐ACE2 interface produces favorable enthalpy of binding whereas conformational restriction of the free peptide reduces the loss in entropy to result higher binding affinity. The understanding of the relation of the nature of the stapling agent with their binding affinity opens up the avenue to explore stapled peptides as therapeutic against SARS‐CoV‐2.

In Silico Drug Repositioning to Target the SARS-CoV-2 Main Protease as Covalent Inhibitors Employing a Combined Structure-Based Virtual Screening Strategy of Pharmacophore Models and Covalent Docking

The epidemic caused by the SARS-CoV-2 coronavirus, which has spread rapidly throughout the world, requires urgent and effective treatments considering that the appearance of viral variants limits the efficacy of vaccines. The main protease of SARS-CoV-2 (M^pro) is a highly conserved cysteine proteinase, fundamental for the replication of the coronavirus and with a specific cleavage mechanism that positions it as an attractive therapeutic target for the proposal of irreversible inhibitors. A structure-based strategy combining 3D pharmacophoric modeling, virtual screening, and covalent docking was employed to identify the interactions required for molecular recognition, as well as the spatial orientation of the electrophilic warhead, of various drugs, to achieve a covalent interaction with Cys145 of M^pro. The virtual screening on the structure-based pharmacophoric map of the SARS-CoV-2 M^pro in complex with an inhibitor N3 (reference compound) provided high efficiency by identifying 53 drugs (FDA and DrugBank databases) with probabilities of covalent binding, including N3 (Michael acceptor) and others with a variety of electrophilic warheads. Adding the energy contributions of affinity for non-covalent and covalent docking, 16 promising drugs were obtained. Our findings suggest that the FDA-approved drugs Vaborbactam, Cimetidine, Ixazomib, Scopolamine, and Bicalutamide, as well as the other investigational peptide-like drugs (DB04234, DB03456, DB07224, DB7252, and CMX-2043) are potential covalent inhibitors of SARS-CoV-2 M^pro.

Investigating novel thiazolyl-indazole derivatives as scaffolds for SARS-CoV-2 MPro inhibitors

COVID-19 is a global pandemic caused by infection with the SARS-CoV-2 virus. Remdesivir, a SARS-CoV-2 RNA polymerase inhibitor, is the only drug to have received widespread approval for treatment of COVID-19. The SARS-CoV-2 main protease enzyme (M^Pro), essential for viral replication and transcription, remains an active target in the search for new treatments. In this study, the ability of novel thiazolyl-indazole derivatives to inhibit M^Pro is evaluated. These compounds were synthesized via the heterocyclization of phenacyl bromide with (R)-carvone, (R)-pulegone and (R)-menthone thiosemicarbazones. The binding affinity and binding interactions of each compound were evaluated through Schrödinger Glide docking, AMBER molecular dynamics simulations, and MM-GBSA free energy estimation, and these results were compared with similar calculations of M^Pro binding various 5-mer substrates (VKLQA, VKLQS, VKLQG) and a previously identified M^Pro tight-binder X77. From these simulations, we can see that binding is driven by residue specific interactions such as π-stacking with His41, and S/π interactions with Met49 and Met165. The compounds were also experimentally evaluated in a M^Pro biochemical assay and the most potent compound containing a phenylthiazole moiety inhibited protease activity with an IC₅₀ of 92.9 ​μM. This suggests that the phenylthiazole scaffold is a promising candidate for the development of future M^Pro inhibitors.

Computationally driven discovery of SARS-CoV-2 Mpro inhibitors: from design to experimental validation

We report a fast-track computationally driven discovery of new SARS-CoV-2 main protease (M^pro) inhibitors whose potency ranges from mM for the initial non-covalent ligands to sub-μM for the final covalent compound (IC₅₀ = 830 ± 50 nM). The project extensively relied on high-resolution all-atom molecular dynamics simulations and absolute binding free energy calculations performed using the polarizable AMOEBA force field. The study is complemented by extensive adaptive sampling simulations that are used to rationalize the different ligand binding poses through the explicit reconstruction of the ligand–protein conformation space. Machine learning predictions are also performed to predict selected compound properties. While simulations extensively use high performance computing to strongly reduce the time-to-solution, they were systematically coupled to nuclear magnetic resonance experiments to drive synthesis and for in vitro characterization of compounds. Such a study highlights the power of in silico strategies that rely on structure-based approaches for drug design and allows the protein conformational multiplicity problem to be addressed. The proposed fluorinated tetrahydroquinolines open routes for further optimization of M^pro inhibitors towards low nM affinities.

The dominant binding mode of the QUB-00006-Int-07 main protease inhibitor during absolute binding free energy simulations.

Fullerenes against COVID-19: Repurposing C60 and C70 to Clog the Active Site of SARS-CoV-2 Protease

The persistency of COVID-19 in the world and the continuous rise of its variants demand new treatments to complement vaccines. Computational chemistry can assist in the identification of moieties able to lead to new drugs to fight the disease. Fullerenes and carbon nanomaterials can interact with proteins and are considered promising antiviral agents. Here, we propose the possibility to repurpose fullerenes to clog the active site of the SARS-CoV-2 protease, M^pro. Through the use of docking, molecular dynamics, and energy decomposition techniques, it is shown that C₆₀ has a substantial binding energy to the main protease of the SARS-CoV-2 virus, M^pro, higher than masitinib, a known inhibitor of the protein. Furthermore, we suggest the use of C₇₀ as an innovative scaffold for the inhibition of SARS-CoV-2 M^pro. At odds with masitinib, both C₆₀ and C₇₀ interact more strongly with SARS-CoV-2 M^pro when different protonation states of the catalytic dyad are considered. The binding of fullerenes to M^pro is due to shape complementarity, i.e., vdW interactions, and is aspecific. As such, it is not sensitive to mutations that can eliminate or invert the charges of the amino acids composing the binding pocket. Fullerenic cages should therefore be more effective against the SARS-CoV-2 virus than the available inhibitors such as masinitib, where the electrostatic term plays a crucial role in the binding.

Insights into the binding and covalent inhibition mechanism of PF-07321332 to SARS-CoV-2 Mpro

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been causing the COVID-19 pandemic, resulting in several million deaths being reported. Numerous investigations have been carried out to discover a compound that can inhibit the biological activity of the SARS-CoV-2 main protease, which is an enzyme related to the viral replication. Among these, PF-07321332 (Nirmatrelvir) is currently under clinical trials for COVID-19 therapy. Therefore, in this work, atomistic and electronic simulations were performed to unravel the binding and covalent inhibition mechanism of the compound to M^pro. Initially, 5 μs of steered-molecular dynamics simulations were carried out to evaluate the ligand-binding process to SARS-CoV-2 M^pro. The successfully generated bound state between the two molecules showed the important role of the PF-07321332 pyrrolidinyl group and the residues Glu166 and Gln189 in the ligand-binding process. Moreover, from the MD-refined structure, quantum mechanics/molecular mechanics (QM/MM) calculations were carried out to unravel the reaction mechanism for the formation of the thioimidate product from SARS-CoV-2 M^pro and the PF-07321332 inhibitor. We found that the catalytic triad Cys145–His41–Asp187 of SARS-CoV-2 M^pro plays an important role in the activation of the PF-07321332 covalent inhibitor, which renders the deprotonation of Cys145 and, thus, facilitates further reaction. Our results are definitely beneficial for a better understanding of the inhibition mechanism and designing new effective inhibitors for SARS-CoV-2 M^pro.

The catalytic triad Cys145–His41–Asp187 of SARS-CoV-2 M^pro plays an important role in the activation of the PF-07321332 covalent inhibitor.

Impact of Warhead Modulations on the Covalent Inhibition of SARS-CoV-2 Mpro Explored by QM/MM Simulations

The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus-2, SARS-CoV-2, shows the need for effective antiviral treatments. Here, we present a simulation study of the inhibition of the SARS-CoV-2 main protease (Mpro), a cysteine hydrolase essential for the life cycle of the virus. The free energy landscape for the mechanism of the inhibition process is explored by QM/MM umbrella sampling and free energy perturbation simulations at the M06-2X/MM level of theory for two proposed peptidyl covalent inhibitors that share the same recognition motif but feature distinct cysteine-targeting warheads. Regardless of the intrinsic reactivity of the modeled inhibitors, namely a Michael acceptor and a hydroxymethyl ketone activated carbonyl, our results confirm that the inhibitory process takes place by means of a two-step mechanism, in which the formation of an ion pair C145/H41 dyad precedes the protein-inhibitor covalent bond formation. The nature of this second step is strongly dependent on the functional groups in the warhead: while the nucleophilic attack of the C145 sulfur atom on the Cα of the double bond of the Michael acceptor takes place concertedly with the proton transfer from H41 to Cβ, in the compound with an activated carbonyl, the sulfur attacks the carbonyl carbon concomitant with a proton transfer from H41 to the carbonyl oxygen via the hydroxyl group. An analysis of the free energy profiles, structures along the reaction path, and interactions between the inhibitors and the different pockets of the active site on the protein shows a measurable effect of the warhead on the kinetics and thermodynamics of the process. These results and QM/MM methods can be used as a guide to select warheads to design efficient irreversible and reversible inhibitors of SARS-CoV-2 Mpro.

Concordance of X-ray and AlphaFold2 Models of SARS-CoV-2 Main Protease with Residual Dipolar Couplings Measured in Solution

The 68-kDa homodimeric 3C-like protease of SARS-CoV-2, M^pro (3CLpro/Nsp5), is a promising antiviral drug target. We evaluate the concordance of models generated by the newly introduced AlphaFold2 structure prediction program with residual dipolar couplings (RDCs) measured in solution for ¹⁵N–¹H^N and ¹³C′–¹H^N atom pairs. The latter were measured using a new, highly precise TROSY-AntiTROSY Encoded RDC (TATER) experiment. Three sets of AlphaFold2 models were evaluated: (1) M^pro_AF, generated using the standard AlphaFold2 input structural database; (2) M^pro_AFD, where the AlphaFold2 implementation was modified to exclude all candidate template X-ray structures deposited after Jan 1, 2020; and (3) M^pro_AFS, which excluded all structures homologous to coronaviral M^pro. Close agreement between all three sets of AlphaFold models and experimental RDC data is found for most of the protein. For residues in well-defined secondary structure, the agreement decreases somewhat upon Amber relaxation. For these regions, M^pro_AF agreement exceeds that of most high-resolution X-ray structures. Residues from domain 2 that comprise elements of both the active site and the homo-dimerization interface fit less well across all structures. These results indicate novel opportunities for combining experimentation with molecular dynamics simulations, where solution RDCs provide highly precise input for QM/MM simulations of substrate binding/reaction trajectories.