A microscopic description of SARS-CoV-2 main protease inhibition with Michael acceptors. Strategies for improving inhibitor design

Synthesis and evaluation of hybrid sulfonamide-chalcones with potential antileishmanial activity

Leishmaniasis is an emerging tropical infectious disease caused by a protozoan parasite of the genus Leishmania. In this work, the molecular hybridization between a trimethoxy chalcone and a sulfonamide group was used to generate a series of sulfonamide-chalcones. A series of eight sulfonamide-chalcone hybrids were made with good yields (up to 95%). These sulfonamide-chalcones were tested against promastigotes of Leishmania amazonensis and cytotoxicity against mouse macrophages, which showed good antileishmanial activity with IC50  = 1.72-3.19 µM. Three of them (10c, 10g, and 10h) were also highly active against intracellular amastigotes and had a good selectivity index (SI > 9). Thus, those three compounds were docked in the cytosolic tryparedoxin peroxidase (cTXNPx) enzyme of the parasite, and molecular dynamics simulations were carried out. This enzyme was selected as a target protein for the sulfonamide-chalcones due to the fact of the anterior report, which identified a strong and stable interaction between the chalcone NAT22 (6) and the cTXNPx. In addition, a prediction of the drug-likeness, and the pharmacokinetic profile of all compounds were made, demonstrating a good profile of those chalcones.

Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development

Understanding enzyme mechanisms is essential for unraveling the complex molecular machinery of life. In this review, we survey the field of computational enzymology, highlighting key principles governing enzyme mechanisms and discussing ongoing challenges and promising advances. Over the years, computer simulations have become indispensable in the study of enzyme mechanisms, with the integration of experimental and computational exploration now established as a holistic approach to gain deep insights into enzymatic catalysis. Numerous studies have demonstrated the power of computer simulations in characterizing reaction pathways, transition states, substrate selectivity, product distribution, and dynamic conformational changes for various enzymes. Nevertheless, significant challenges remain in investigating the mechanisms of complex multistep reactions, large-scale conformational changes, and allosteric regulation. Beyond mechanistic studies, computational enzyme modeling has emerged as an essential tool for computer-aided enzyme design and the rational discovery of covalent drugs for targeted therapies. Overall, enzyme design/engineering and covalent drug development can greatly benefit from our understanding of the detailed mechanisms of enzymes, such as protein dynamics, entropy contributions, and allostery, as revealed by computational studies. Such a convergence of different research approaches is expected to continue, creating synergies in enzyme research. This review, by outlining the ever-expanding field of enzyme research, aims to provide guidance for future research directions and facilitate new developments in this important and evolving field.

Computational study on the mechanisms of inhibition of SARS-CoV-2 Mpro by aldehyde warheads based on DFT

SARS-CoV-2 main protease, Mpro, plays a crucial role in the virus replication cycle, making it an important target for antiviral research. In this study, a simplified model obtained through truncation is used to explore the reaction mechanism of aldehyde warhead compounds inhibiting Mpro at the level of density functional theory. According to the calculation results, proton transfer (P_T)-nucleophilic attack (N_A) is the rate-determining step in the entire reaction pathway. The water molecule that plays a catalytic role occupies the oxyanion hole, which is unfavorable for the aldehyde warhead to approach the Cys145 SH. Through a hypothetical study of substituting the main chain NH with methylene, it is further confirmed that the P_T-N_A is a proton transfer-dominated process accompanied by a nucleophilic attack reaction. In this process, the oxyanion hole serves only to stabilize the aldehyde oxygen anion and therefore does not have a significant impact on the activation free energy barrier of the step. Our research results provide a unique perspective for understanding the covalent inhibition reaction of the Mpro active site. This study also offers theoretical guidance for the design of new Mpro covalent inhibitors.

Multiscale Simulations of the Covalent Inhibition of the SARS-CoV-2 Main Protease: Four Compounds and Three Reaction Mechanisms

We report the results of computational modeling of the reactions of the SARS-CoV-2 main protease (MPro) with four potential covalent inhibitors. Two of them, carmofur and nirmatrelvir, have shown experimentally the ability to inhibit MPro. Two other compounds, X77A and X77C, were designed computationally in this work. They were derived from the structure of X77, a non-covalent inhibitor forming a tight surface complex with MPro. We modified the X77 structure by introducing warheads capable of reacting with the catalytic cysteine residue in the MPro active site. The reaction mechanisms of the four molecules with MPro were investigated by quantum mechanics/molecular mechanics (QM/MM) simulations. The results show that all four compounds form covalent adducts with the catalytic cysteine Cys 145 of MPro. From the chemical perspective, the reactions of these four molecules with MPro follow three distinct mechanisms. The reactions are initiated by a nucleophilic attack of the thiolate group of the deprotonated cysteine residue from the catalytic dyad Cys145-His41 of MPro. In the case of carmofur and X77A, the covalent binding of the thiolate to the ligand is accompanied by the formation of the fluoro-uracil leaving group. The reaction with X77C follows the nucleophilic aromatic substitution SNAr mechanism. The reaction of MPro with nirmatrelvir (which has a reactive nitrile group) leads to the formation of a covalent thioimidate adduct with the thiolate of the Cys145 residue in the enzyme active site. Our results contribute to the ongoing search for efficient inhibitors of the SARS-CoV-2 enzymes.

Unraveling the catalytic mechanism of SARS-CoV-2 papain-like protease with allosteric modulation of C270 mutation using multiscale computational approaches

Papain-like protease (PL^pro) is a promising therapeutic target against SARS-CoV-2, but its restricted S1/S2 subsites pose an obstacle in developing active site-directed inhibitors. We have recently identified C270 as a novel covalent allosteric site for SARS-CoV-2 PL^pro inhibitors. Here we present a theoretical investigation of the proteolysis reaction catalyzed by the wild-type SARS-CoV-2 PL^pro as well as the C270R mutant. Enhanced sampling MD simulations were first performed to explore the influence of C270R mutation on the protease dynamics, and sampled thermodynamically favorable conformations were then submitted to MM/PBSA and QM/MM MD simulations for thorough characterization of the protease-substrate binding and covalent reactions. The disclosed proteolysis mechanism of PL^pro, as characterized by the occurrence of proton transfer from the catalytic C111 to H272 prior to the substrate binding and with deacylation being the rate-determining step of the whole proteolysis process, is not completely identical to that of the 3C-like protease, another key cysteine protease of coronaviruses. The C270R mutation alters the structural dynamics of the BL2 loop that indirectly impairs the catalytic function of H272 and reduces the binding of the substrate with the protease, ultimately showing an inhibitory effect on PL^pro. Together, these results provide a comprehensive understanding at the atomic level of the key aspects of SARS-CoV-2 PL^pro proteolysis, including the catalytic activity allosterically regulated by C270 modification, which is crucial to the follow-up inhibitor design and development.

Unveiling the Mechanistic Singularities of Caspases: A Computational Analysis of the Reaction Mechanism in Human Caspase-1

Caspases are cysteine proteases in charge of breaking a peptide bond next to an aspartate residue. Caspases constitute an important family of enzymes involved in cell death and inflammatory processes. A plethora of diseases, including neurological and metabolic diseases and cancer, are associated with the poor regulation of caspase-mediated cell death and inflammation. Human caspase-1 in particular carries out the transformation of the pro-inflammatory cytokine pro-interleukin-1β into its active form, a key process in the inflammatory response and then in many diseases, such as Alzheimer's disease. Despite its importance, the reaction mechanism of caspases has remained elusive. The standard mechanistic proposal valid for other cysteine proteases and that involves the formation of an ion pair in the catalytic dyad is not supported by experimental evidence. Using a combination of classical and hybrid DFT/MM simulations, we propose a reaction mechanism for the human caspase-1 that explains experimental observations, including mutagenesis, kinetic, and structural data. In our mechanistic proposal, the catalytic cysteine, Cys285, is activated after a proton transfer to the amide group of the scissile peptide bond, a process facilitated by hydrogen-bond interactions with Ser339 and His237. The catalytic histidine does not directly participate in any proton transfer during the reaction. After formation of the acylenzyme intermediate, the deacylation step takes place through the activation of a water molecule by the terminal amino group of the peptide fragment formed during the acylation step. The overall activation free energy obtained from our DFT/MM simulations is in excellent agreement with the value derived from the experimental rate constant, 18.7 vs 17.9 kcal·mol^-1, respectively. Simulations of the H237A mutant support our conclusions and agree with the reported reduced activity observed for this caspase-1 variant. We propose that this mechanism can explain the reactivity of all cysteine proteases belonging to the CD clan and that differences with respect to other clans could be related to the larger preference showed by enzymes of the CD clan for charged residues at position P1. This mechanism would avoid the free energy penalty associated with the formation of an ion pair. Finally, our structural description of the reaction process can be useful to assist in the design of inhibitors of caspase-1, a target in the treatment of several human diseases.

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.

Michael acceptor molecules in natural products and their mechanism of action

Purpose: Michael receptor molecules derived from plants are biologically active due to electrophilic groups in their structure. They can target nucleophilic residues on disease-related proteins, with significant therapeutic effects and low toxicity for many diseases. They provide a good option for relevant disease treatment. The aim of this study is to summarize the existing MAMs and their applications, and lay a foundation for the application of Michael receptor molecules in life science in the future. Methods: This review summarizes the published studies on Michael receptor molecules isolated from plants in literature databases such as CNKI, Wanfang Data, PubMed, Web of Science, ScienceDirect, and Wiley. Latin names of plants were verified through https://www.iplant.cn/. All relevant compound structures were verified through PubChem and literature, and illustrated with ChemDraw 20.0. Result: A total of 50 Michael receptor molecules derived from various plants were discussed. It was found that these compounds have similar pharmacological potential, most of them play a role through the Keap1-Nrf2-ARE pathway and the NF-κB pathway, and have biological activities such as antioxidant and anti-inflammatory. They can be used to treat inflammatory diseases and tumors. Conclusion: The Michael receptor molecule has electrophilicity due to its unsaturated aldehyde ketone structure, which can combine with nucleophilic residues on the protein to form complexes and activate or inhibit the protein pathway to play a physiological role. Michael receptor molecules can regulate the Keap1-Nrf2-ARE pathway and the NF-κB pathway. Michael receptor molecules can be used to treat diseases such as inflammation, cancer, oxidative stress, etc.

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

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

Assessment of Reversibility for Covalent Cysteine Protease Inhibitors Using Quantum Mechanics/Molecular Mechanics Free Energy Surfaces

We have used molecular dynamics (MD) simulations with hybrid quantum mechanics/molecular mechanics (QM/MM) potentials to investigate the reaction mechanism for covalent inhibition of cathepsin K and assess the reversibility of inhibition. The computed free energy profiles suggest that a nucleophilic attack by the catalytic cysteine on the inhibitor warhead and proton transfer from the catalytic histidine occur in a concerted manner. The results indicate that the reaction is more strongly exergonic for the alkyne-based inhibitors, which bind irreversibly to cathepsin K, than for the nitrile-based inhibitor odanacatib, which binds reversibly. Gas-phase energies were also calculated for the addition of methanethiol to structural prototypes for a number of warheads of interest in cysteine protease inhibitor design in order to assess electrophilicity. The approaches presented in this study are particularly applicable to assessment of novel warheads, and computed transition state geometries can be incorporated into molecular models for covalent docking.

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.

How Reproducible Are QM/MM Simulations? Lessons from Computational Studies of the Covalent Inhibition of the SARS-CoV-2 Main Protease by Carmofur

This work explores the level of transparency in reporting the details of computational protocols that is required for practical reproducibility of quantum mechanics/molecular mechanics (QM/MM) simulations. Using the reaction of an essential SARS-CoV-2 enzyme (the main protease) with a covalent inhibitor (carmofur) as a test case of chemical reactions in biomolecules, we carried out QM/MM calculations to determine the structures and energies of the reactants, the product, and the transition state/intermediate using analogous QM/MM models implemented in two software packages, NWChem and Q-Chem. Our main benchmarking goal was to reproduce the key energetics computed with the two packages. Our results indicate that quantitative agreement (within the numerical thresholds used in calculations) is difficult to achieve. We show that rather minor details of QM/MM simulations must be reported in order to ensure the reproducibility of the results and offer suggestions toward developing practical guidelines for reporting the results of biosimulations.

Allosteric Modulation of the Main Protease (MPro) of SARS-CoV-2 by Casticin—Insights from Molecular Dynamics Simulations

Inhibition of the main protease (M^pro) of SARS-CoV-2 has been suggested to be vital in shutting down viral replication in a host. Most efforts aimed at inhibiting M^Pro activity have been channeled into competitive inhibition at the active site, but this strategy will require a high inhibitor concentration and impressive inhibitor-M^Pro binding affinity. Allosteric inhibition can potentially serve as an effective strategy for alleviating these limitations. In this study, the ability of antiviral natural products to inhibit M^Pro in an allosteric fashion was explored with in silico techniques. Molecular docking revealed a strong interaction between casticin, an antiviral flavonoid, and M^pro at a site distant from the active site. This site, characterized as a distal site, has been shown to have an interdependent dynamic effect with the active site region. M^pro only, M^pro-peptide (binary) and M^pro-peptide-casticin (ternary) complexes were subjected to molecular dynamics simulations for 50 ns to investigate the modulatory activity of casticin binding on M^pro. Molecular dynamic simulations revealed that binding of casticin at the distal site interferes with the proper orientation of the peptide substrate in the oxyanion hole of the active site, and this could lead to a halt or decrease in catalytic activity. This study therefore highlights casticin as a potential allosteric modulator of the SARS-CoV-2 main protease, which could be optimized and developed into a potential lead compound for anti-SARS-CoV-2 chemotherapy.

Testing Affordable Strategies for the Computational Study of Reactivity in Cysteine Proteases: The Case of SARS-CoV-2 3CL Protease Inhibition

Cysteine proteases are an important target for the development of inhibitors that could be used as drugs to regulate the activity of these kinds of enzymes involved in many diseases, including COVID-19. For this reason, it is important to have methodological tools that allow a detailed study of their activity and inhibition, combining computational efficiency and accuracy. We here explore the performance of different quantum mechanics/molecular mechanics methods to explore the inhibition reaction mechanism of the SARS-CoV-2 3CL protease with a hydroxymethyl ketone derivative. We selected two density functional theory (DFT) functionals (B3LYP and M06-2X), two semiempirical Hamiltonians (AM1d and PM6), and two tight-binding DFT methods (DFTB3 and GFN2-xTB) to explore the free energy landscape associated with this reaction. We show that it is possible to obtain an accurate description combining molecular dynamics simulations performed using tight-binding DFT methods and single-point energy corrections at a higher QM description. The use of a computational strategy that provides reliable results at a reasonable computational cost could assist the in silico screening of possible candidates during the design of new drugs directed against cysteine proteases.

Multiple protonation states in ligand-free SARS-CoV-2 main protease revealed by large-scale quantum molecular dynamics simulations

The main protease (M^pro) in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) catalyzes the cleavage of polyproteins for viral replication. Here, large-scale quantum molecular dynamics and metadynamics simulations for ligand-free M^pro were performed, where all the atoms were treated quantum-mechanically, focusing on elucidation of the controversial active-site protonation state. The simulations clarified that the interconverting multiple protonation states exist in unliganded M^pro, and the catalytically relevant ion-pair state is more stable than the neutral state, which is consistent with neutron crystallography. The results highlight the importance of the ion-pair state for repurposing or discovering antiviral drugs that target M^pro.

SERS-PCR assays of SARS-CoV-2 target genes using Au nanoparticles-internalized Au nanodimple substrates

The reverse transcription-polymerase chain reaction (RT-PCR) method has been adopted worldwide to diagnose severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although this method has good sensitivity and specificity, there is a need to develop a more rapid diagnostic technology, given the virus’s rapid spread. However, the RT-PCR method takes a long time to diagnose SARS-CoV-2 because of the required thermocycling steps. Therefore, we developed a surface-enhanced Raman scattering (SERS)-PCR detection method using an AuNP-internalized Au nanodimple substrate (AuNDS) to shorten the diagnosis time by reducing the number of thermocycling steps needed to amplify the DNA. For the representative target markers, namely, the envelope protein (E) and RNA-dependent RNA polymerase (RdRp) genes of SARS-CoV-2, 25 RT-PCR thermocycles are required to reach a detectable threshold value, while 15 cycles are needed for magnetic bead-based SERS-PCR when the initial DNA concentration was 1.00× 10⁵ copies/μL. However, only 8 cycles are needed for the AuNDS-based SERS-PCR. The corresponding detectable target DNA concentrations were 3.36 × 10¹², 3.28 × 10⁹, and 2.56 × 10⁷ copies/μL, respectively. Therefore, AuNDS-based SERS-PCR is seen as being a new molecular diagnostic platform that can shorten the time required for the thermocycling steps relative to the conventional RT-PCR.

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 Mpro. Initially, 5 μs of steered-molecular dynamics simulations were carried out to evaluate the ligand-binding process to SARS-CoV-2 Mpro. 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 Mpro and the PF-07321332 inhibitor. We found that the catalytic triad Cys145-His41-Asp187 of SARS-CoV-2 Mpro 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 Mpro.

Applications of density functional theory in COVID-19 drug modeling

The rapidly evolving Coronavirus 2019 (COVID-19) pandemic has led to millions of deaths around the world, highlighting the pressing need to develop effective antiviral pharmaceuticals. Recent efforts with computer-aided rational drug discovery have allowed detailed examination of drug–macromolecule interactions primarily by molecular mechanics (MM) techniques. Less widely applied in COVID-19 drug modeling is density functional theory (DFT), a quantum mechanics (QM) method that enables electronic structure calculations and elucidations of reaction mechanisms. Here, we review recent advances in applying DFT in molecular modeling studies of COVID-19 pharmaceuticals. We start by providing an overview of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) drugs and targets, followed by a brief introduction to DFT. We then provide a discussion of different approaches by which DFT has been applied. Finally, we discuss essential factors to consider when incorporating DFT in future drug modeling research.

Inhibition Mechanism of SARS-CoV-2 Main Protease with Ketone-Based Inhibitors Unveiled by Multiscale Simulations: Insights for Improved Designs*

We present the results of classical and QM/MM simulations for the inhibition of SARS‐CoV‐2 3CL protease by a hydroxymethylketone inhibitor, PF‐00835231. In the noncovalent complex the carbonyl oxygen atom of the warhead is placed in the oxyanion hole formed by residues 143 to 145, while P1–P3 groups are accommodated in the active site with interactions similar to those observed for the peptide substrate. According to alchemical free energy calculations, the P1′ hydroxymethyl group also contributes to the binding free energy. Covalent inhibition of the enzyme is triggered by the proton transfer from Cys145 to His41. This step is followed by the nucleophilic attack of the Sγ atom on the carbonyl carbon atom of the inhibitor and a proton transfer from His41 to the carbonyl oxygen atom mediated by the P1′ hydroxyl group. Computational simulations show that the addition of a chloromethyl substituent to the P1′ group may lower the activation free energy for covalent inhibition

Mechanism-Based and Computational-Driven Covalent Drug Design

Covalent drugs offer higher efficacy and longer duration of action than their noncovalent counterparts. Significant advances in computational methods for modeling covalent drugs are poised to shift the paradigm of small molecule therapeutics within the next decade. This viewpoint discusses the advantages of a two-state model for ranking reversible and irreversible covalent ligands and of more complex models for dissecting reaction mechanisms. The relation between these models highlights the complexity and diversity of covalent drug binding and provides opportunities for mechanism-based rational design.

Microscopic interactions between ivermectin and key human and viral proteins involved in SARS-CoV-2 infection

The identification of chemical compounds able to bind specific sites of the human/viral proteins involved in the SARS-CoV-2 infection cycle is a prerequisite to design effective antiviral drugs. Here we conduct a molecular dynamics study with the aim to assess the interactions of ivermectin, an antiparasitic drug with broad-spectrum antiviral activity, with the human Angiotensin-Converting Enzyme 2 (ACE2), the viral 3CL^pro and PL^pro proteases, and the viral SARS Unique Domain (SUD). The drug/target interactions have been characterized in silico by describing the nature of the non-covalent interactions found and by measuring the extent of their time duration along the MD simulation. Results reveal that the ACE2 protein and the ACE2/RBD aggregates form the most persistent interactions with ivermectin, while the binding with the remaining viral proteins is more limited and unspecific.

Modelling the active SARS-CoV-2 helicase complex as a basis for structure-based inhibitor design

The RNA helicase (non-structural protein 13, NSP13) of SARS-CoV-2 is essential for viral replication, and it is highly conserved among the coronaviridae family, thus a prominent drug target to treat COVID-19. We present here structural models and dynamics of the helicase in complex with its native substrates based on thorough analysis of homologous sequences and existing experimental structures. We performed and analysed microseconds of molecular dynamics (MD) simulations, and our model provides valuable insights to the binding of the ATP and ssRNA at the atomic level. We identify the principal motions characterising the enzyme and highlight the effect of the natural substrates on this dynamics. Furthermore, allosteric binding sites are suggested by our pocket analysis. Our obtained structural and dynamical insights are important for subsequent studies of the catalytic function and for the development of specific inhibitors at our characterised binding pockets for this promising COVID-19 drug target.

Characterization of Phytochemicals in Ulva intestinalis L. and Their Action Against SARS-CoV-2 Spike Glycoprotein Receptor-Binding Domain

Coronavirus disease-2019 (COVID-19) has caused a severe impact on almost all aspects of human life and economic development. Numerous studies are being conducted to find novel therapeutic strategies to overcome COVID-19 pandemic in a much effective way. Ulva intestinalis L. (Ui), a marine microalga, known for its antiviral property, was considered for this study to determine the antiviral efficacy against severe acute respiratory syndrome-associated Coronavirus-2 (SARS-CoV-2). The algal sample was dried and subjected to ethanolic extraction, followed by purification and analysis using gas chromatography-coupled mass spectrometry (GC-MS). Forty-three known compounds were identified and docked against the S1 receptor binding domain (RBD) of the spike (S) glycoprotein. The compounds that exhibited high binding affinity to the RBD of S1 protein were further analyzed for their chemical behaviour using conceptual density-functional theory (C-DFT). Finally, pharmacokinetic properties and drug-likeliness studies were carried out to test if the compounds qualified as potential leads. The results indicated that mainly phenols, polyenes, phytosteroids, and aliphatic compounds from the extract, such as 2,4-di-tert-butylphenol (2,4-DtBP), doconexent, 4,8,13-duvatriene-1,3-diol (DTD), retinoyl-β-glucuronide 6',3'-lactone (RBGUL), and retinal, showed better binding affinity to the target. Pharmacokinetic validation narrowed the list to 2,4-DtBP, retinal and RBGUL as the possible antiviral candidates that could inhibit the viral spike protein effectively.

The Se-S Bond Formation in the Covalent Inhibition Mechanism of SARS-CoV-2 Main Protease by Ebselen-like Inhibitors: A Computational Study

The inhibition mechanism of the main protease (Mpro) of SARS-CoV-2 by ebselen (EBS) and its analog with a hydroxyl group at position 2 of the benzisoselenazol-3(2H)-one ring (EBS-OH) was studied by using a density functional level of theory. Preliminary molecular dynamics simulations on the apo form of Mpro were performed taking into account both the hydrogen donor and acceptor natures of the Nδ and Nε of His41, a member of the catalytic dyad. The potential energy surfaces for the formation of the Se-S covalent bond mediated by EBS and EBS-OH on Mpro are discussed in detail. The EBS-OH shows a distinctive behavior with respect to EBS in the formation of the noncovalent complex. Due to the presence of canonical H-bonds and noncanonical ones involving less electronegative atoms, such as sulfur and selenium, the influence on the energy barriers and reaction energy of the Minnesota hybrid meta-GGA functionals M06, M06-2X and M08HX, and the more recent range-separated hybrid functional wB97X were also considered. The knowledge of the inhibition mechanism of Mpro by the small protease inhibitors EBS or EBS-OH can enlarge the possibilities for designing more potent and selective inhibitor-based drugs to be used in combination with other antiviral therapies.

Computational simulations on the binding and reactivity of a nitrile inhibitor of the SARS-CoV-2 main protease

We present a detailed computational analysis of the binding mode and reactivity of the novel oral inhibitor PF-07321332 developed against the SARS-CoV-2 3CL protease. Alchemical free energy calculations suggest that positions P3 and P4 could be susceptible to improvement in order to get a larger binding strength. QM/MM simulations unveil the reaction mechanism for covalent inhibition, showing that the nitrile warhead facilitates the recruitment of a water molecule for the proton transfer step.

Benchmarking the Ability of Common Docking Programs to Correctly Reproduce and Score Binding Modes in SARS-CoV-2 Protease Mpro

The coronavirus SARS-CoV-2 main protease, Mpro, is conserved among coronaviruses with no human homolog and has therefore attracted significant attention as an enzyme drug target for COVID-19. The number of studies targeting Mpro for in silico screening has grown rapidly, and it would be of great interest to know in advance how well docking methods can reproduce the correct ligand binding modes and rank these correctly. Clearly, current attempts at designing drugs targeting Mpro with the aid of computational docking would benefit from a priori knowledge of the ability of docking programs to predict correct binding modes and score these correctly. In the current work, we tested the ability of several leading docking programs, namely, Glide, DOCK, AutoDock, AutoDock Vina, FRED, and EnzyDock, to correctly identify and score the binding mode of Mpro ligands in 193 crystal structures. None of the codes were able to correctly identify the crystal structure binding mode (lowest energy pose with root-mean-square deviation < 2 Å) in more than 26% of the cases for noncovalently bound ligands (Glide: top performer), whereas for covalently bound ligands the top score was 45% (EnzyDock). These results suggest that one should perform in silico campaigns of Mpro with care and that more comprehensive strategies including ligand free energy perturbation might be necessary in conjunction with virtual screening and docking.

New insights into the catalytic mechanism of the SARS-CoV-2 main protease: an ONIOM QM/MM approach

SARS-CoV-2 M^pro, also known as the main protease or 3C-like protease, is a key enzyme involved in the replication process of the virus that is causing the COVID-19 pandemic. It is also the most promising antiviral drug target targeting SARS-CoV-2 virus. In this work, the catalytic mechanism of M^pro was studied using the full model of the enzyme and a computational QM/MM methodology with a 69/72-atoms QM region treated at DLPNO-CCSD(T)/CBS//B3LYP/6-31G(d,p):AMBER level and including the catalytic important oxyanion-hole residues. The transition state of each step was fully characterized and described together with the related reactants and products. The rate-limiting step of the catalytic process is the hydrolysis of the thioester-enzyme adduct, and the calculated barrier closely agrees with the available kinetic data. The calculated Gibbs free energy profile, together with the full atomistic detail of the structures involved in catalysis, can now serve as valuable models for the rational drug design of transition state analogs as new inhibitors targeting the SARS-CoV-2 virus.

Tuning Proton Transfer Thermodynamics in SARS-CoV-2 Main Protease: Implications for Catalysis and Inhibitor Design

The catalytic reaction in SARS-CoV-2 main protease is activated by a proton transfer (PT) from Cys145 to His41. The same PT is likely also required for the covalent binding of some inhibitors. Here we use a multiscale computational approach to investigate the PT thermodynamics in the apo enzyme and in complex with two potent inhibitors, N3 and the α-ketoamide 13b. We show that with the inhibitors the free energy cost to reach the charge-separated state of the active-site dyad is lower, with N3 inducing the most significant reduction. We also show that a few key sites (including specific water molecules) significantly enhance or reduce the thermodynamic feasibility of the PT reaction, with selective desolvation of the active site playing a crucial role. The approach presented is a cost-effective procedure to identify the enzyme regions that control the activation of the catalytic reaction and is thus also useful to guide the design of inhibitors.

Multiscale Simulations of SARS-CoV-2 3CL Protease Inhibition with Aldehyde Derivatives. Role of Protein and Inhibitor Conformational Changes in the Reaction Mechanism

We here investigate the mechanism of SARS-CoV-2 3CL protease inhibition by one of the most promising families of inhibitors, those containing an aldehyde group as a warhead. These compounds are covalent inhibitors that inactivate the protease, forming a stable hemithioacetal complex. Inhibitor 11a is a potent inhibitor that has been already tested in vitro and in animals. Using a combination of classical and QM/MM simulations, we determined the binding mode of the inhibitor into the active site and the preferred rotameric state of the catalytic histidine. In the noncovalent complex, the aldehyde group is accommodated into the oxyanion hole formed by the NH main-chain groups of residues 143 to 145. In this pose, P1-P3 groups of the inhibitor mimic the interactions established by the natural peptide substrate. The reaction is initiated with the formation of the catalytic dyad ion pair after a proton transfer from Cys145 to His41. From this activated state, covalent inhibition proceeds with the nucleophilic attack of the deprotonated Sγ atom of Cys145 to the aldehyde carbon atom and a water-mediated proton transfer from the Nε atom of His41 to the aldehyde oxygen atom. Our proposed reaction transition-state structure is validated by comparison with X-ray data of recently reported inhibitors, while the activation free energy obtained from our simulations agrees with the experimentally derived value, supporting the validity of our findings. Our study stresses the interplay between the conformational dynamics of the inhibitor and the protein with the inhibition mechanism and the importance of including conformational diversity for accurate predictions about the inhibition of the main protease of SARS-CoV-2. The conclusions derived from our work can also be used to rationalize the behavior of other recently proposed inhibitor compounds, including aldehydes and ketones with high inhibitory potency.

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.