Assessment of proton-coupled conformational dynamics of SARS and MERS coronavirus papain-like proteases: Implication for designing broad-spectrum antiviral inhibitors

Mechanism of Dimer Selectivity and Binding Cooperativity of BRAF Inhibitors

Aberrant signaling of BRAFV600E is a major cancer driver. Current FDA-approved RAF inhibitors selectively inhibit the monomeric BRAFV600E and suffer from tumor resistance. Recently, dimer-selective and equipotent RAF inhibitors have been developed; however, the mechanism of dimer selectivity is poorly understood. Here, we report extensive molecular dynamics (MD) simulations of the monomeric and dimeric BRAFV600E in the apo form or in complex with one or two dimer-selective (PHI1) or equipotent (LY3009120) inhibitor(s). The simulations uncovered the unprecedented details of the remarkable allostery in BRAFV600E dimerization and inhibitor binding. Specifically, dimerization retrains and shifts the αC helix inward and increases the flexibility of the DFG motif; dimer compatibility is due to the promotion of the αC-in conformation, which is stabilized by a hydrogen bond formation between the inhibitor and the αC Glu501. A more stable hydrogen bond further restrains and shifts the αC helix inward, which incurs a larger entropic penalty that disfavors monomer binding. This mechanism led us to propose an empirical way based on the co-crystal structure to assess the dimer selectivity of a BRAFV600E inhibitor. Simulations also revealed that the positive cooperativity of PHI1 is due to its ability to preorganize the αC and DFG conformation in the opposite protomer, priming it for binding the second inhibitor. The atomically detailed view of the interplay between BRAF dimerization and inhibitor allostery as well as cooperativity has implications for understanding kinase signaling and contributes to the design of protomer selective RAF inhibitors.

Force Field Limitations of All-Atom Continuous Constant pH Molecular Dynamics

All-atom constant pH molecular dynamics simulations offer a powerful tool for understanding pH-mediated and proton-coupled biological processes. As the protonation equilibria of protein side chains are shifted by electrostatic interactions and desolvation energies, pKa values calculated from the constant pH simulations may be sensitive to the underlying protein force field and water model. Here we investigated the force field dependence of the all-atom particle mesh Ewald (PME) continuous constant pH (PME-CpHMD) simulations of a mini-protein BBL. The replica-exchange titration simulations based on the Amber ff19sb and ff14sb force fields with the respective water models showed significantly overestimated pKa downshifts for a buried histidine (His166) and for two glutamic acids (Glu141 and Glu161) that are involved in salt-bridge interactions. These errors (due to undersolvation of neutral histidines and overstabilization of salt bridges) are consistent with the previously reported pKa's based on the CHARMM c22/CMAP force field, albeit in larger magnitudes. The pKa calculations also demonstrated that ff19sb with OPC water is significantly more accurate than ff14sb with TIP3P water, and the salt-bridge related pKa downshifts can be partially alleviated by the atom-pair specific Lennard-Jones corrections (NBFIX). Together, these data suggest that the accuracies of the protonation equilibria of proteins from constant pH simulations can significantly benefit from improvements of force fields.

Force Field Limitations of All-Atom Continuous Constant pH Molecular Dynamics

All-atom constant pH molecular dynamics simulations offer a powerful tool for understanding pH-mediated and proton-coupled biological processes. As the protonation equilibria of protein sidechains are shifted by electrostatic interactions and desolvation energies, pK a values calculated from the constant pH simulations may be sensitive to the underlying protein force field and water model. Here we investigated the force field dependence of the all-atom particle mesh Ewald (PME) continuous constant pH (PME-CpHMD) simulations of a mini-protein BBL. The replica-exchange titration simulations based on the Amber ff19sb and ff14sb force fields with the respective water models showed significantly overestimated pK a downshifts for a buried histidine (His166) and for two glutamic acids (Glu141 and Glu161) that are involved in salt-bridge interactions. These errors (due to undersolvation of neutral histidines and overstabilization of salt bridges) are consistent with the previously reported pK a's based on the CHARMM c22/CMAP force field, albeit in larger magnitudes. The pK a calculations also demonstrated that ff19sb with OPC water is significantly more accurate than ff14sb with TIP3P water, and the salt-bridge related pK a downshifts can be partially alleviated by the atom-pair specific Lennard-Jones corrections (NBFIX). Together, these data suggest that the accuracies of the protonation equilibria of proteins from constant pH simulations can significantly benefit from improvements of force fields.

Unraveling the structural and functional dimensions of SARS-CoV2 proteins in the context of COVID-19 pathogenesis and therapeutics

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) has emerged as the causative agent behind the global pandemic of Coronavirus Disease 2019 (COVID-19). As the scientific community strives to comprehend the intricate workings of this virus, a fundamental aspect lies in deciphering the myriad proteins it expresses. This knowledge is pivotal in unraveling the complexities of the viral machinery and devising targeted therapeutic interventions. The proteomic landscape of SARS-CoV2 encompasses structural, non-structural, and open-reading frame proteins, each playing crucial roles in viral replication, host interactions, and the pathogenesis of COVID-19. This comprehensive review aims to provide an updated and detailed examination of the structural and functional attributes of SARS-CoV2 proteins. By exploring the intricate molecular architecture, we have highlighted the significance of these proteins in viral biology. Insights into their roles and interplay contribute to a deeper understanding of the virus's mechanisms, thereby paving the way for the development of effective therapeutic strategies. As the global scientific community strives to combat the ongoing pandemic, this synthesis of knowledge on SARS-CoV2 proteins serves as a valuable resource, fostering informed approaches toward mitigating the impact of COVID-19 and advancing the frontier of antiviral research.

Modeling of noncovalent inhibitors of the papain-like protease (PLpro) from SARS-CoV-2 considering the protein flexibility by using molecular dynamics and cross-docking

The papain-like protease (PLpro) found in coronaviruses that can be transmitted from animals to humans is a critical target in respiratory diseases linked to Severe Acute Respiratory Syndrome (SARS-CoV). Researchers have proposed designing PLpro inhibitors. In this study, a set of 89 compounds, including recently reported 2-phenylthiophenes with nanomolar inhibitory potency, were investigated as PLpro noncovalent inhibitors using advanced molecular modeling techniques. To develop the work with these inhibitors, multiple structures of the SARS-CoV-2 PLpro binding site were generated using a molecular sampling method. These structures were then clustered to select a group that represents the flexibility of the site. Subsequently, models of the protein-ligand complexes were created for the set of inhibitors within the chosen conformations. The quality of the complex models was assessed using LigRMSD software to verify similarities in the orientations of the congeneric series and interaction fingerprints to determine the recurrence of chemical interactions. With the multiple models constructed, a protocol was established to choose one per ligand, optimizing the correlation between the calculated docking energy values and the biological activities while incorporating the effect of the binding site's flexibility. A strong correlation (R2 = 0.922) was found when employing this flexible docking protocol.

Why is the Omicron main protease of SARS-CoV-2 less stable than its wild-type counterpart? A crystallographic, biophysical, and theoretical study of the free enzyme and its complex with inhibitor 13b-K

During the continuing evolution of SARS-CoV-2, the Omicron variant of concern emerged in the second half of 2021 and has been dominant since November that year. Along with its sublineages, it has maintained a prominent role ever since. The Nsp5 main protease (Mpro) of the Omicron virus is characterized by a single dominant mutation, P132H. Here we determined the X-ray crystal structures of the P132H mutant (or O-Mpro) as free enzyme and in complex with the Mpro inhibitor, the alpha-ketoamide 13b-K, and we conducted enzymology, biophysical as well as theoretical studies to characterize the O-Mpro. We found that O-Mpro has a similar overall structure and binding with 13b-K; however, it displays lower enzymatic activity and lower thermal stability compared to the WT-Mpro (with "WT" referring to the original Wuhan-1 strain). Intriguingly, the imidazole ring of His132 and the carboxylate plane of Glu240 are in a stacked configuration in the X-ray structures determined here. The empirical folding free energy calculations suggest that the O-Mpro dimer is destabilized relative to the WT-Mpro due to the less favorable van der Waals interactions and backbone conformation in the individual protomers. The all-atom continuous constant pH molecular dynamics (MD) simulations reveal that His132 and Glu240 display coupled titration. At pH 7, His132 is predominantly neutral and in a stacked configuration with respect to Glu240 which is charged. In order to examine whether the Omicron mutation eases the emergence of further Mpro mutations, we also determined crystal structures of the relatively frequent P132H+T169S double mutant but found little evidence for a correlation between the two sites.

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.

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.

Integrative Approach to Dissect the Drug Resistance Mechanism of the H172Y Mutation of SARS-CoV-2 Main Protease

Nirmatrelvir is an orally available inhibitor of SARS-CoV-2 main protease (Mpro) and the main ingredient of Paxlovid, a drug approved by the U.S. Food and Drug Administration for high-risk COVID-19 patients. Recently, a rare natural mutation, H172Y, was found to significantly reduce nirmatrelvir's inhibitory activity. As the COVID-19 cases skyrocket in China and the selective pressure of antiviral therapy builds in the US, there is an urgent need to characterize and understand how the H172Y mutation confers drug resistance. Here, we investigated the H172Y Mpro's conformational dynamics, folding stability, catalytic efficiency, and inhibitory activity using all-atom constant pH and fixed-charge molecular dynamics simulations, alchemical and empirical free energy calculations, artificial neural networks, and biochemical experiments. Our data suggest that the mutation significantly weakens the S1 pocket interactions with the N-terminus and perturbs the conformation of the oxyanion loop, leading to a decrease in the thermal stability and catalytic efficiency. Importantly, the perturbed S1 pocket dynamics weaken the nirmatrelvir binding in the P1 position, which explains the decreased inhibitory activity of nirmatrelvir. Our work demonstrates the predictive power of the combined simulation and artificial intelligence approaches, and together with biochemical experiments, they can be used to actively surveil continually emerging mutations of SARS-CoV-2 Mpro and assist the optimization of antiviral drugs. The presented approach, in general, can be applied to characterize mutation effects on any protein drug targets.

An Integrative Approach to Dissect the Drug Resistance Mechanism of the H172Y Mutation of SARS-CoV-2 Main Protease

Nirmatrelvir is an orally available inhibitor of SARS-CoV-2 main protease (Mpro) and the main ingredient of PAXLOVID, a drug approved by FDA for high-risk COVID-19 patients. Recently, a rare natural mutation, H172Y, was found to significantly reduce nirmatrelvir's inhibitory activity. As the COVID-19 cases skyrocket in China and the selective pressure of antiviral therapy builds up in the US, there is an urgent need to characterize and understand how the H172Y mutation confers drug resistance. Here we investigated the H172Y Mpro's conformational dynamics, folding stability, catalytic efficiency, and inhibitory activity using all-atom constant pH and fixed-charge molecular dynamics simulations, alchemical and empirical free energy calculations, artificial neural networks, and biochemical experiments. Our data suggests that the mutation significantly weakens the S1 pocket interactions with the N-terminus and perturbs the conformation of the oxyanion loop, leading to a decrease in the thermal stability and catalytic efficiency. Importantly, the perturbed S1 pocket dynamics weakens the nirma-trelvir binding in the P1 position, which explains the decreased inhibitory activity of nirmatrelvir. Our work demonstrates the predictive power of the combined simulation and artificial intel-ligence approaches, and together with biochemical experiments they can be used to actively surveil continually emerging mutations of SARS-CoV-2 Mpro and assist the discovery of new antiviral drugs. The presented workflow can be applicable to characterize mutation effects on any protein drug targets.

Identification of Cysteine 270 as a Novel Site for Allosteric Modulators of SARS-CoV-2 Papain-Like Protease

The coronavirus papain-like protease (PL^pro ) plays an important role in the proteolytic processing of viral polyproteins and the dysregulation of the host immune response, providing a promising therapeutic target. However, the development of inhibitors against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PL^pro is challenging owing to the restricted S1/S2 sites in the substrate binding pocket. Here we report the discovery of two activators of SARS-CoV-2 PL^pro and the identification of the unique residue, cysteine 270 (C270), as an allosteric and covalent regulatory site for the activators. This site is also specifically modified by glutathione, resulting in protease activation. Furthermore, a compound was found to allosterically inhibit the protease activity by covalent binding to C270. Together, these results elucidate an unrevealed molecular mechanism for allosteric modulation of SARS-CoV-2 PL^pro and provid a novel site for allosteric inhibitors design.

GPU-Accelerated All-Atom Particle-Mesh Ewald Continuous Constant pH Molecular Dynamics in Amber

Constant pH molecular dynamics (MD) simulations sample protonation states on the fly according to the conformational environment and user specified pH conditions; however, the current accuracy is limited due to the use of implicit-solvent models or a hybrid solvent scheme. Here, we report the first GPU-accelerated implementation, parametrization, and validation of the all-atom continuous constant pH MD (CpHMD) method with particle-mesh Ewald (PME) electrostatics in the Amber22 pmemd.cuda engine. The titration parameters for Asp, Glu, His, Cys, and Lys were derived for the CHARMM c22 and Amber ff14sb and ff19sb force fields. We then evaluated the PME-CpHMD method using the asynchronous pH replica-exchange titration simulations with the c22 force field for six benchmark proteins, including BBL, hen egg white lysozyme (HEWL), staphylococcal nuclease (SNase), thioredoxin, ribonuclease A (RNaseA), and human muscle creatine kinase (HMCK). The root-mean-square deviation from the experimental pK_a's of Asp, Glu, His, and Cys is 0.76 pH units, and the Pearson's correlation coefficient for the pK_a shifts with respect to model values is 0.80. We demonstrated that a finite-size correction or much enlarged simulation box size can remove a systematic error of the calculated pK_a's and improve agreement with experiment. Importantly, the simulations captured the relevant biology in several challenging cases, e.g., the titration order of the catalytic dyad Glu35/Asp52 in HEWL and the coupled residues Asp19/Asp21 in SNase, the large pK_a upshift of the deeply buried catalytic Asp26 in thioredoxin, and the large pK_a downshift of the deeply buried catalytic Cys283 in HMCK. We anticipate that PME-CpHMD will offer proper pH control to improve the accuracies of MD simulations and enable mechanistic studies of proton-coupled dynamical processes that are ubiquitous in biology but remain poorly understood due to the lack of experimental tools and limitation of current MD simulations.

Reactivity and binding mode of disulfiram, its metabolites, and derivatives in SARS-CoV-2 PLpro: insights from computational chemistry studies

The papain-like protease (PLpro) from SARS-CoV-2 is an important target for the development of antivirals against COVID-19. The safe drug disulfiram (DSF) presents antiviral activity inhibiting PLpro in vitro, and it is under clinical trial studies, indicating to be a promising anti-COVID-19 drug. In this work, we aimed to understand the mechanism of PLpro inhibition by DSF and verify if DSF metabolites and derivatives could be potential inhibitors too. Molecular docking, DFT, and ADMET techniques were applied. The carbamoylation of the active site cysteine residue by DSF metabolite (DETC-MeSO) is kinetically and thermodynamically favorable (ΔG‡ = 3.15 and ΔG =  - 12.10 kcal mol-1, respectively). Our results strongly suggest that the sulfoxide metabolites from DSF are promising covalent inhibitors of PLpro and should be tested in in vitro and in vivo assays to confirm their antiviral action.

Fluorine Atoms on C6H5-Corrole Affect the Interaction with Mpro and PLpro Proteases of SARS-CoV-2: Molecular Docking and 2D-QSAR Approaches

The chymotrypsin-like cysteine protease (3CL^pro, also known as main protease—M^pro) and papain-like protease (PL^pro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been used as the main targets for screening potential synthetic inhibitors for posterior in vitro evaluation of the most promising compounds. In this sense, the present work reports for the first time the evaluation of the interaction between M^pro/PL^pro with a series of 17 porphyrin analogues-corrole (C1), meso-aryl-corrole (C2), and 15 fluorinated-meso-aryl-corrole derivatives (C3–C17) via molecular docking calculations. The impact of fluorine atoms on meso-aryl-corrole structure was also evaluated in terms of binding affinity and physical-chemical properties by two-dimensional quantitative structure–activity relationship (2D-QSAR). The presence of phenyl moieties increased the binding capacity of corrole for both proteases and depending on the position of fluorine atoms might impact positively or negatively the binding capacity. For M^pro the para-fluorine atoms might decrease drastically the binding capacity, while for PL^pro there was a certain increase in the binding affinity of fluorinated-corroles with the increase of fluorine atoms into meso-aryl-corrole structure mainly from tri-fluorinated insertions. The 2D-QSAR models indicated two separated regions of higher and lower affinity for M^pro:C1–C17 based on dual electronic parameters (σ_I and σ_R), as well as one model was obtained with a correlation between the docking score value of M^pro:C2–C17 and the corresponding ¹³C nuclear magnetic resonance (NMR) chemical shifts of the sp² carbon atoms (δ_C-1 and δ_C-2) of C2–C17. Overall, the fluorinated-meso-aryl-corrole derivatives showed favorable in silico parameters as potential synthetic compounds for future in vitro assays on the inhibition of SARS-CoV-2 replication.

A Guide to the Continuous Constant pH Molecular Dynamics Methods in Amber and CHARMM [Article v1.0]

Like temperature and pressure, solution pH is an important environmental variable in biomolecular simulations. Virtually all proteins depend on pH to maintain their structure and function. In conventional molecular dynamics (MD) simulations of proteins, pH is implicitly accounted for by assigning and fixing protonation states of titratable sidechains. This is a significant limitation, as the assigned protonation states may be wrong and they may change during dynamics. In this tutorial, we guide the reader in learning and using the various continuous constant pH MD methods in Amber and CHARMM packages, which have been applied to predict pK a values and elucidate proton-coupled conformational dynamics of a variety of proteins including enzymes and membrane transporters.

H172Y mutation perturbs the S1 pocket and nirmatrelvir binding of SARS-CoV-2 main protease through a nonnative hydrogen bond

Nirmatrelvir is an orally available inhibitor of SARS-CoV-2 main protease (Mpro) and the main ingredient of PAXLOVID, a drug approved by FDA for high-risk COVID-19 patients. Although the prevalent Mpro mutants in the SARS-CoV-2 Variants of Concern (e.g., Omicron) are still susceptible to nirmatrelvir, a rare natural mutation, H172Y, was found to significantly reduce nirmatrelvir's inhibitory activity. As the selective pressure of antiviral therapy may favor resistance mutations, there is an urgent need to understand the effect of the H172Y mutation on Mpro's structure, function, and drug resistance. Here we report the molecular dynamics (MD) simulations as well as the measurements of stability, enzyme kinetics of H172Y Mpro, and IC50 value of nirmatrelvir. Simulations showed that mutation disrupts the interactions between the S1 pocket and N terminus of the opposite protomer. Intriguingly, a native hydrogen bond (H-bond) between Phe140 and the N terminus is replaced by a transient H-bond between Phe140 and Tyr172. In the ligand-free simulations, strengthening of this nonnative H-bond is correlated with disruption of the conserved aromatic stacking between Phe140 and His163, leading to a partial collapse of the oxyanion loop. In the nirmatrelvir-bound simulations, the nonnative H-bond is correlated with the loss of an important H-bond between Glu166 and nirmatrelvir's lactam nitrogen at P1 position. These results are consistent with the newly reported X-ray structures of H172Y Mpro and suggest a mechanism by which the H172Y substitution perturbs the S1 pocket, leading to the decreased structural stability and binding affinity, which in turn explains the drastic reduction in catalytic activity and antiviral susceptibility.

Targeting SARS-CoV-2 Papain-Like Protease in the Post-Vaccine Era

While vaccines remain at the forefront of global healthcare responses, pioneering therapeutics against SARS-CoV-2 are expected to fill the gaps for waning immunity. Rapid development and approval of orally available direct-acting antivirals targeting crucial SARS-CoV-2 proteins marked the beginning of the era of small-molecule drugs for COVID-19. In that regard, the papain-like protease (PLpro) can be considered a major SARS-CoV-2 therapeutic target due to its dual biological role in suppressing host innate immune responses and in ensuring viral replication. Here, we summarize the challenges of targeting PLpro and innovative early-stage PLpro-specific small molecules. We propose that state-of-the-art computer-aided drug design (CADD) methodologies will play a critical role in the discovery of PLpro compounds as a novel class of COVID-19 drugs.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

Inhibitor induced conformational changes in SARS-COV-2 papain-like protease

SARS-CoV-2's papain-like protease (PLpro) interaction with ligands has recently been explored with a myriad of crystal structures. We used molecular dynamics (MD) simulations to study different PLpro-ligand complexes, their ligand-induced conformational changes, and interactions. We focused on inhibitors reported with known IC50 against PLpro, namely GRL-0617, XR8-89, PLP_Snyder530, and Sander's recently published compound 7 (CPD7), and compared these trajectories against the apostructure (Apo), with a total of around 60 µs worth simulation data. We aimed to study the conformational changes using molecular dynamics simulations for the inhibitors in the PLpro. PCA analyses and the MSM models revealed distinct conformations of PLpro in the absence/presence of ligands and proposed that BL2-loop contributes to the accessibility of these inhibitors. Further, bulkier substituents closer to Tyr268 and Gln269 could improve inhibition of SARS-CoV-2 PLpro by occupying the region between BL2-groove and BL2-loop, but we also expand on the relevance of exploring multiple PLpro sub-pockets to improve inhibition.

Identification of bio-active food compounds as potential SARS-CoV-2 PLpro inhibitors-modulators via negative image-based screening and computational simulations

Despite significant studies on the COVID-19 pandemic, scientists around the world are still battling to find a definitive therapy against the ongoing severe global health crisis. In this study, advanced computational approaches have been employed to identify bioactive food constituents as potential SARS-CoV-2 PLpro inhibitors-modulators. As a validated antiviral drug target, PLpro has gained tremendous attention for therapeutics developments. Therefore, targeting the multifunctional SARS-CoV-2 PLpro protein, ∼1039 bioactive dietary compounds have been screened extensively through novel techniques like negative image-based (NIB) screening and molecular docking approaches. In particular, the three different models of NIB screening have been generated and used to re-score the dietary compounds based on the negative image which is created by reversing the shape and electrostatics features of PLpro protein's ligand-binding cavity. Further, 100 ns molecular dynamics simulation has been performed and MM-GBSA based binding free energies have been estimated for the final proposed four dietary compounds (PC000550, PC000361, PC000558, and PC000573) as potential inhibitors/modulators of SARS-CoV-2 PLpro protein. Employed computational study outcome also has been compared with respect to the earlier experimentally investigated compound GRL0617 against SARS-CoV-2 PLpro protein, which suggests much greater interaction potential in terms of binding affinity and other energetic contributions for the proposed dietary compounds. Hence, the present study suggests that proposed dietary compounds can be suitable chemical entities for modulating the activity of PLpro protein or can be further utilized for optimizing or screening of novel chemical surrogates, however also needs experimental evaluation for entry in clinical studies for better assessment.

Profiling MAP kinase cysteines for targeted covalent inhibitor design

Mitogen-activated protein kinases (MAPK) are important therapeutic targets, and yet no inhibitors have advanced to the market. Here we applied the GPU-accelerated continuous constant pH molecular dynamics (CpHMD) to calculate the pK a's and profile the cysteine reactivities of all 14 MAPKs for assisting the targeted covalent inhibitor design. The simulations not only recapitulated but also rationalized the reactive cysteines in the front pocket of JNK1/2/3 and the extended front pocket of p38α. Interestingly, the DFG - 1 cysteine in the DFG-in conformation of ERK1/ERK2 was found somewhat reactive or unreactive; however, simulations of MKK7 showed that switching to the DFG-out conformation makes the DFG - 1 cysteine reactive, suggesting the advantage of type II covalent inhibitors. Additionally, the simulations prospectively predicted several druggable cysteine and lysine sites, including the αH head cysteine in JNK1/3 and DFG + 6 cysteine in JNK2, corroborating the chemical proteomic screening data. Given the low cost and the ability to offer physics-based rationales, we envision CpHMD simulations to complement the chemo-proteomic platform for systematic profiling cysteine reactivities for targeted covalent drug discovery.

Identification of potent food constituents as SARS-CoV-2 papain-like protease modulators through advanced pharmacoinformatics approaches

The current ongoing pandemic of COVID-19 urges immediate treatment measures for controlling the highly contagious SARS-CoV-2 infections. The papain-like protease (PLpro), which is released from nsp3, is presently being evaluated as a significant anti-viral drug target for COVID-19 therapy development. Particularly, PLpro is implicated in the cleavage of viral polyproteins and antagonizes the host innate immune response through its deubiquitinating and deISGylating actions, thus making it a high-profile antiviral therapeutic target. The present study reports a few specific food compounds that can bind tightly with the SARS-CoV-2 PLpro protein identified through extensive computational screening techniques. Precisely, extensive advanced computational approaches combining target-based virtual screening, particularly employing sub-structure based similarity search, molecular docking, molecular dynamics (MD) simulations, and MM-GBSA based binding free energy calculations have been employed for the identification of the most promising food compounds with substantial functional implications as SARS-CoV-2 PLpro protein inhibitors/modulators. Observations from the present research investigation also provide a deeper understanding of the binding modes of the proposed four food compounds with SARS-CoV-2 PLpro protein. In docking analyses, all compounds have established essential inter-molecular interaction profiles at the active site cavity of the SARS-CoV-2 PLpro protein. Similarly, the long-range 100 ns conventional MD simulation studies also provided an in-depth understanding of probable interactions and dynamic behaviour of the SARS-CoV-2 PLpro protein-food compound complexes. Binding free energies of all molecular systems revealed a strong interaction affinity of food compounds towards the SARS-CoV-2 PLpro protein. Moreover, clear-cut comparative analyses against the known standard inhibitor also suggest that proposed food compounds may act as potential active chemical entities for modulating the action of the SARS-CoV-2 PLpro protein.

Protein pK a Prediction with Machine Learning

Protein pK _a prediction is essential for the investigation of the pH-associated relationship between protein structure and function. In this work, we introduce a deep learning-based protein pK _a predictor DeepKa, which is trained and validated with the pK _a values derived from continuous constant-pH molecular dynamics (CpHMD) simulations of 279 soluble proteins. Here, the CpHMD implemented in the Amber molecular dynamics package has been employed (Huang Y.J. Chem. Inf. Model.2018, 58, 1372-1383). Notably, to avoid discontinuities at the boundary, grid charges are proposed to represent protein electrostatics. We show that the prediction accuracy by DeepKa is close to that by CpHMD benchmarking simulations, validating DeepKa as an efficient protein pK _a predictor. In addition, the training and validation sets created in this study can be applied to the development of machine learning-based protein pK _a predictors in the future. Finally, the grid charge representation is general and applicable to other topics, such as the protein-ligand binding affinity prediction.

Virus structure and structure-based antivirals

Structure-based antiviral developments in the past two years have been dominated by the structure determination and inhibition of SARS-CoV-2 proteins and new lead molecules for picornaviruses. The SARS-CoV-2 spike protein has been targeted successfully with antibodies, nanobodies, and receptor protein mimics effectively blocking receptor binding or fusion. The two most promising non-structural proteins sharing strong structural and functional conservation across virus families are the main protease and the RNA-dependent RNA polymerase, for which design and reuse of broad range inhibitors already approved for use has been an attractive avenue. For picornaviruses, the increasing recognition of the transient expansion of the capsid as a critical transition towards RNA release has been targeted through a newly identified, apparently widely conserved, druggable, interprotomer pocket preventing viral entry. We summarize some of the key papers in these areas and ponder the practical uses and contributions of molecular modeling alongside empirical structure determination.

Structure-Function Characteristics of SARS-CoV-2 Proteases and Their Potential Inhibitors from Microbial Sources

The COVID-19 pandemic, caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is considered the greatest challenge to the global health community of the century as it continues to expand. This has prompted immediate urgency to discover promising drug targets for the treatment of COVID-19. The SARS-CoV-2 viral proteases, 3-chymotrypsin-like protease (3CLpro) and papain-like cysteine protease (PLpro), have become the promising target to study due to their essential functions in spreading the virus by RNA transcription, translation, protein synthesis, processing and modification, virus replication, and infection of the host. As such, understanding of the structure and function of these two proteases is unavoidable as platforms for the development of inhibitors targeting this protein which further arrest the infection and spread of the virus. While the abundance of reports on the screening of natural compounds such as SARS-CoV-2 proteases inhibitors are available, the microorganisms-based compounds (peptides and non-peptides) remain less studied. Indeed, microorganisms-based compounds are also one of the potent antiviral candidates against COVID-19. Microbes, especially bacteria and fungi, are other resources to produce new drugs as well as nucleosides, nucleotides, and nucleic acids. Thus, we have compiled various reported literature in detail on the structures, functions of the SARS-CoV-2 proteases, and potential inhibitors from microbial sources as assistance to other researchers working with COVID-19. The compounds are also compared to HIV protease inhibitors which suggested the microorganisms-based compounds are advantageous as SARS-CoV2 proteases inhibitors. The information should serve as a platform for further development of COVID-19 drug design strategies.

Reactivities of the Front Pocket N-Terminal Cap Cysteines in Human Kinases

The front pocket (FP) N-terminal cap (Ncap) cysteine is the most popular site of covalent modification in kinases. A long-standing hypothesis associates the Ncap position with cysteine hyper-reactivity; however, traditional computational predictions suggest that the FP Ncap cysteines are predominantly unreactive. Here we applied the state-of-the-art continuous constant pH molecular dynamics (CpHMD) to test the Ncap hypothesis. Simulations found that the Ncap cysteines of BTK/BMX/TEC/ITK/TXK, JAK3, and MKK7 are reactive to varying degrees; however, those of BLK and EGFR/ERBB2/ERBB4 possessing a Ncap+3 aspartate are unreactive. Analysis suggested that hydrogen bonding and electrostatic interactions drive the reactivity, and their absence renders the Ncap cysteine unreactive. To further test the Ncap hypothesis, we examined the FP Ncap+2 cysteines in JNK1/JNK2/JNK3 and CASK. Our work offers a systematic understanding of the cysteine structure-reactivity relationship and illustrates the use of CpHMD to differentiate cysteines toward the design of targeted covalent inhibitors with reduced chemical reactivities.

Analyzing the Effect of Mutations in SARS-CoV2 Papain-Like Protease from Saudi Isolates on Protein Structure and Drug-Protein Binding: Molecular Modelling and Dynamics Studies

The continuous and rapid development of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus remains a health concern especially with the emergence of numerous variants and mutations worldwide. As with other RNA viruses, SARS-CoV-2 has a genetically high mutation rate. These mutations have an impact on the virus characteristics, including transmissibility, antigenicity and development of drug and vaccine resistance. This work was pursued to identify the differences that exist in the papain-like protease (PL^Pro) from 58 Saudi isolates in comparison to the first reported sequence from Wuhan, China and determine their implications on protein structure and the inhibitor binding. PL^pro is a key protease enzyme for the host cells invasion and viral proteolytic cleavage, hence, it emerges as a valuable antiviral therapeutic target. Two mutations were identified including D108G and A249V and shown to increase the molecular flexibility of PL^Pro protein and alter the protein stability, particularly with D108G mutation. The effect of these mutations on the stability and dynamic behavior of PL^Pro structures as well as their effect on the binding of a known inhibitor; GRL0617 were further investigated by molecular docking and dynamic simulation.

Perturbation of ACE2 Structural Ensembles by SARS-CoV-2 Spike Protein Binding

The human ACE2 enzyme serves as a critical first recognition point of coronaviruses, including SARS-CoV-2. In particular, the extracellular domain of ACE2 interacts directly with the S1 tailspike protein of the SARS-CoV-2 virion through a broad protein-protein interface. Although this interaction has been characterized by X-ray crystallography, these structures do not reveal significant differences in the ACE2 structure upon S1 protein binding. In this work, using several all-atom molecular dynamics simulations, we show persistent differences in the ACE2 structure upon binding. These differences are determined with the linear discriminant analysis (LDA) machine learning method and validated using independent training and testing datasets, including long trajectories generated by D. E. Shaw Research on the Anton 2 supercomputer. In addition, long trajectories for 78 potent ACE2-binding compounds, also generated by D. E. Shaw Research, were projected onto the LDA classification vector in order to determine whether the ligand-bound ACE2 structures were compatible with S1 protein binding. This allows us to predict which compounds are "apo-like" versus "complex-like" and to pinpoint long-range ligand-induced allosteric changes in the ACE2 structure.

Predicted pH-dependent stability of SARS-CoV-2 spike protein trimer from interfacial acidic groups

Transition between receptor binding domain (RBD) up and down forms of the SARS-CoV-2 spike protein trimer is coupled to receptor binding and is one route by which variants can alter viral properties. It is becoming apparent that key roles in the transition are played by pH and a more compact closed form, termed locked. Calculations of pH-dependence are made for a large set of spike trimers, including locked form trimer structures that have recently become available. Several acidic sidechains become sufficiently buried in the locked form to give a predicted pH-dependence in the mild acidic range, with stabilisation of the locked form as pH reduces from 7.5 to 5, consistent with emerging characterisation by cryo-electron microscopy. The calculated pH effects in pre-fusion spike trimers are modulated mainly by aspartic acid residues, rather than the more familiar histidine role at mild acidic pH. These acidic sidechains are generally surface located and weakly interacting when not in a locked conformation. According to this model, their replacement (perhaps with asparagine) would remove the pH-dependent destabilisation of locked spike trimer conformations, and increase their recovery at neutral pH. This would provide an alternative or supplement to the insertion of disulphide linkages for stabilising spike protein trimers, with potential relevance for vaccine design.

Evaluating Stability and Activity of SARS-CoV-2 PLpro for High-throughput Screening of Inhibitors

Because of the essential roles of SARS-CoV-2 papain-like protease (PLpro) in the viral polyprotein processing and suppression of host immune responses, it is a crucial target for drug discovery against COVID-19. To develop robust biochemical methodologies for inhibitor screening against PLpro, extensive characterization of recombinant protein is important. Here we report cloning, expression, and purification of the recombinant SARS-CoV-2 PLpro, and explore various parameters affecting its stability and the catalytic activity. We also report the optimum conditions which should be used for high-throughput inhibitor screening using a fluorogenic tetrapeptide substrate.

Rapid response to emerging biomedical challenges and threats

As part of the global mobilization to combat the present pandemic, almost 100 000 COVID-19-related papers have been published and nearly a thousand models of macromolecules encoded by SARS-CoV-2 have been deposited in the Protein Data Bank within less than a year. The avalanche of new structural data has given rise to multiple resources dedicated to assessing the correctness and quality of structural data and models. Here, an approach to evaluate the massive amounts of such data using the resource https://covid19.bioreproducibility.org is described, which offers a template that could be used in large-scale initiatives undertaken in response to future biomedical crises. Broader use of the described methodology could considerably curtail information noise and significantly improve the reproducibility of biomedical research.

In Silico Identification of Multi-target Anti-SARS-CoV-2 Peptides from Quinoa Seed Proteins

Peptides are promising antagonists against severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2). To expedite drug discovery, a computational approach is widely employed for the initial screening of anti-SARS-CoV-2 candidates. This study aimed to investigate the potential of peptides from quinoa seed proteins as multi-target antagonists against SARS-CoV-2 spike glycoprotein receptor-binding domain, main protease, and papain-like protease. Five quinoa proteins were hydrolyzed in silico by papain and subtilisin. Among the 1465 peptides generated, seven could interact stably with the key binding residues and catalytic residues of the viral targets, mainly via hydrogen bonds and hydrophobic interactions. The seven peptides were comparable or superior to previously reported anti-SARS-CoV-2 peptides based on docking scores. Key residues in the seven peptides contributing to binding to viral targets were determined by computational alanine scanning. The seven peptides were predicted in silico to be non-toxic and non-allergenic. The peptides ranged between 546.66 and 3974.87 g/mol in molecular mass, besides exhibiting basic and cationic properties (isoelectric points: 8.26-12.10; net charges: 0.1-4.0). Among the seven peptides, VEDKGMMHQQRMMEKAMNIPRMCGTMQRKCRMS was found to bind the largest number of key residues on the targets. In conclusion, seven putative non-toxic, non-allergenic, multi-target anti-SARS-CoV-2 peptides were identified from quinoa seed proteins. The in vitro and in vivo efficacies of the seven peptides against SARS-CoV-2 deserve attention in future bench-top testing.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10989-021-10214-y.

Covalent and non-covalent binding free energy calculations for peptidomimetic inhibitors of SARS-CoV-2 main protease

COVID-19, the disease caused by the newly discovered coronavirus-SARS-CoV-2, has created a global health, social, and economic crisis. As of mid-January 2021, there are over 90 million confirmed cases and more than 2 million reported deaths due to COVID-19. Currently, there are very limited therapeutics for the treatment or prevention of COVID-19. For this reason, it is important to find drug targets that will lead to the development of safe and effective therapeutics against the disease. The main protease (M^pro) of the virus is an attractive target for the development of effective antiviral therapeutics because it is required for proteolytic cleavage of viral polyproteins. Furthermore, the M^pro has no human homologues, so drugs designed to bind to this target directly have less risk for off-target effects. Recently, several high-resolution crystallographic structures of the M^pro in complex with inhibitors have been determined-to guide drug development and to spur efforts in structure-based drug design. One of the primary objectives of modern structure-based drug design is the accurate prediction of receptor-ligand binding affinities for rational drug design and discovery. Here, we perform rigorous alchemical absolute binding free energy calculations and QM/MM calculations to give insight into the total binding energy of two recently crystallized inhibitors of SARS-CoV-2 M^pro, namely, N3 and α-ketoamide 13b. The total binding energy consists of both covalent and non-covalent binding components since both compounds are covalent inhibitors of the M^pro. Our results indicate that the covalent and non-covalent binding free energy contributions of both inhibitors to the M^pro target differ significantly. The N3 inhibitor has more favourable non-covalent interactions, particularly hydrogen bonding, in the binding site of the M^pro than the α-ketoamide inhibitor. Also, the Gibbs energy of reaction for the M^pro-N3 covalent adduct is greater than the Gibbs reaction energy for the M^pro-α-ketoamide covalent adduct. These differences in the covalent and non-covalent binding free energy contributions for both inhibitors could be a plausible explanation for their in vitro differences in antiviral activity. Our findings are consistent with the reversible and irreversible character of both inhibitors as reported by experiment and highlight the importance of both covalent and non-covalent binding free energy contributions to the absolute binding affinity of a covalent inhibitor towards its target. This information could prove useful in the rational design, discovery, and evaluation of potent SARS-CoV-2 M^pro inhibitors for targeted antiviral therapy.

Inhibitor binding influences the protonation states of histidines in SARS-CoV-2 main protease

The main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an attractive target for antiviral therapeutics. Recently, many high-resolution apo and inhibitor-bound structures of Mpro, a cysteine protease, have been determined, facilitating structure-based drug design. Mpro plays a central role in the viral life cycle by catalyzing the cleavage of SARS-CoV-2 polyproteins. In addition to the catalytic dyad His41-Cys145, Mpro contains multiple histidines including His163, His164, and His172. The protonation states of these histidines and the catalytic nucleophile Cys145 have been debated in previous studies of SARS-CoV Mpro, but have yet to be investigated for SARS-CoV-2. In this work we have used molecular dynamics simulations to determine the structural stability of SARS-CoV-2 Mpro as a function of the protonation assignments for these residues. We simulated both the apo and inhibitor-bound enzyme and found that the conformational stability of the binding site, bound inhibitors, and the hydrogen bond networks of Mpro are highly sensitive to these assignments. Additionally, the two inhibitors studied, the peptidomimetic N3 and an α-ketoamide, display distinct His41/His164 protonation-state-dependent stabilities. While the apo and the N3-bound systems favored N δ (HD) and N ϵ (HE) protonation of His41 and His164, respectively, the α-ketoamide was not stably bound in this state. Our results illustrate the importance of using appropriate histidine protonation states to accurately model the structure and dynamics of SARS-CoV-2 Mpro in both the apo and inhibitor-bound states, a necessary prerequisite for drug-design efforts.

Proton-Coupled Conformational Activation of SARS Coronavirus Main Proteases and Opportunity for Designing Small-Molecule Broad-Spectrum Targeted Covalent Inhibitors

The SARS coronavirus 2 (SARS-CoV-2) main protease (Mpro) is an attractive broad-spectrum antiviral drug target. Despite the enormous progress in structure elucidation, the Mpro's structure-function relationship remains poorly understood. Recently, a peptidomimetic inhibitor has entered clinical trial; however, small-molecule orally available antiviral drugs have yet to be developed. Intrigued by a long-standing controversy regarding the existence of an inactive state, we explored the proton-coupled dynamics of the Mpros of SARS-CoV-2 and the closely related SARS-CoV using a newly developed continuous constant pH molecular dynamics (MD) method and microsecond fixed-charge all-atom MD simulations. Our data supports a general base mechanism for Mpro's proteolytic function. The simulations revealed that protonation of His172 alters a conserved interaction network that upholds the oxyanion loop, leading to a partial collapse of the conserved S1 pocket, consistent with the first and controversial crystal structure of SARS-CoV Mpro determined at pH 6. Interestingly, a natural flavonoid binds SARS-CoV-2 Mpro in the close proximity to a conserved cysteine (Cys44), which is hyper-reactive according to the CpHMD titration. This finding offers an exciting new opportunity for small-molecule targeted covalent inhibitor design. Our work represents a first step toward the mechanistic understanding of the proton-coupled structure-dynamics-function relationship of CoV Mpros; the proposed strategy of designing small-molecule covalent inhibitors may help accelerate the development of orally available broad-spectrum antiviral drugs to stop the current pandemic and prevent future outbreaks.

Papain-Like Proteases as Coronaviral Drug Targets: Current Inhibitors, Opportunities, and Limitations

Papain-like proteases (PLpro) of coronaviruses (CoVs) support viral reproduction and suppress the immune response of the host, which makes CoV PLpro perspective pharmaceutical targets. Their inhibition could both prevent viral replication and boost the immune system of the host, leading to the speedy recovery of the patient. Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the third CoV outbreak in the last 20 years. Frequent mutations of the viral genome likely lead to the emergence of more CoVs. Inhibitors for CoV PLpro can be broad-spectrum and can diminish present and prevent future CoV outbreaks as PLpro from different CoVs have conservative structures. Several inhibitors have been developed to withstand SARS-CoV and Middle East respiratory syndrome CoV (MERS-CoV). This review summarizes the structural features of CoV PLpro, the inhibitors that have been identified over the last 20 years, and the compounds that have the potential to become novel effective therapeutics against CoVs in the near future.