Lead Discovery of SARS-CoV-2 Main Protease Inhibitors through Covalent Docking-Based Virtual Screening

Discovery of pyrimidoindol and benzylpyrrolyl inhibitors targeting SARS-CoV-2 main protease (Mpro) through pharmacophore modelling, covalent docking, and biological evaluation

The main protease (Mpro) enzyme has an imperative function in disease progression and the life cycle of the SARS-CoV-2 virus. Although the orally active drug nirmatrelvir (co-administered with ritonavir as paxlovid) has been approved for emergency use as the frontline antiviral agent, there are a number of limitations that necessitate the discovery of new drug scaffolds, such as poor pharmacokinetics and susceptibility to proteolytic degradation due to its peptidomimetic nature. This study utilized a novel virtual screening workflow that combines pharmacophore modelling, multiple-receptor covalent docking, and biological evaluation in order to find new Mpro inhibitors. After filtering and analysing ∼66,000 ligands from three different electrophilic libraries, 29 compounds were shortlisted for experimental testing, and two of them exhibited ≥20% inhibition at 100 μM. Our top candidate, GF04, is a benzylpyrrolyl compound that exhibited the highest inhibition activity of 38.3%, with a relatively small size (<350 Da) and leadlike character. Interestingly, our approach also identified another hit, DR07, a pyrimidoindol with a non-peptide character, and a molecular weight of 438.9 Da, reporting an inhibition of 26.3%. The established approach detailed in this study, in conjunction with the discovered inhibitors, has the capacity to yield novel perspectives for devising covalent inhibitors targeting the COVID-19 Mpro enzyme and other comparable targets.

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

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

Structure and function of SARS-CoV and SARS-CoV-2 main proteases and their inhibition: A comprehensive review

Severe acute respiratory syndrome-associated coronavirus (SARS-CoV) identified in 2003 infected ∼8000 people in 26 countries with 800 deaths, which was soon contained and eradicated by syndromic surveillance and enhanced quarantine. A closely related coronavirus SARS-CoV-2, the causative agent of COVID-19 identified in 2019, has been dramatically more contagious and catastrophic. It has infected and caused various flu-like symptoms of billions of people in >200 countries, including >6 million people died of or with the virus. Despite the availability of several vaccines and antiviral drugs against SARS-CoV-2, finding new therapeutics is needed because of viral evolution and a possible emerging coronavirus in the future. The main protease (Mpro) of these coronaviruses plays important roles in their life cycle and is essential for the viral replication. This article represents a comprehensive review of the function, structure and inhibition of SARS-CoV and -CoV-2 Mpro, including structure-activity relationships, protein-inhibitor interactions and clinical trial status.

Next Generation of Fluorometric Protease Assays: 7-Nitrobenz-2-oxa-1,3-diazol-4-yl-amides (NBD-Amides) as Class-Spanning Protease Substrates

Fluorometric assays are one of the most frequently used methods in medicinal chemistry. Over the last 50 years, the reporter molecules for the detection of protease activity have evolved from first-generation colorimetric p-nitroanilides, through FRET substrates, and 7-amino-4-methyl coumarin (AMC)-based substrates. The aim of further substrate development is to increase sensitivity and reduce vulnerability to assay interferences. Herein, we describe a new generation of substrates for protease assays based on 7-nitrobenz-2-oxa-1,3-diazol-4-yl-amides (NBD-amides). In this study, we synthesized and tested substrates for 10 different proteases from the serine-, cysteine-, and metalloprotease classes. Enzyme- and substrate-specific parameters as well as the inhibitory activity of literature-known inhibitors confirmed their suitability for application in fluorometric assays. Hence, we were able to present NBD-based alternatives for common protease substrates. In conclusion, these NBD substrates are not only less susceptible to common assay interference, but they are also able to replace FRET-based substrates with the requirement of a prime site amino acid residue.

Recent Advances in SARS-CoV-2 Main Protease Inhibitors: From Nirmatrelvir to Future Perspectives

The main protease (Mpro) plays a pivotal role in the replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is considered a highly conserved viral target. Disruption of the catalytic activity of Mpro produces a detrimental effect on the course of the infection, making this target one of the most attractive for the treatment of COVID-19. The current success of the SARS-CoV-2 Mpro inhibitor Nirmatrelvir, the first oral drug for the treatment of severe forms of COVID-19, has further focused the attention of researchers on this important viral target, making the search for new Mpro inhibitors a thriving and exciting field for the development of antiviral drugs active against SARS-CoV-2 and related coronaviruses.

Identification of prospective covalent inhibitors for SARS-CoV-2 main protease using structure-based approach

The rapid global spread of SARS-CoV-2 has recently caused havoc and forced the world into a state of the pandemic causing respiratory, gastrointestinal, hepatic, and neurologic diseases. It persistently, through mutation, develops into new variants of the virus that have appeared over time. As main protease (Mpro) is involved in proteolysis of two overlapping polyproteins pp1a and pp1ab to produce 16 non-structural proteins having a paramount factor in the virus replication that have a cysteine-histidine catalytic dyad. A computational approach, guiding a covalent docking as it offers higher potency, long duration of action and decreased drug resistance advantages over the conventional docking of the ligands on a catalytic dyad, is applied for SARS-CoV-2 main protease (Mpro) in this manuscript to divulge better molecules. Mpro active site contains Cys145 residue which act as a nucleophile and can donate its electron to an electrophilic molecule by interacting covalently. Furthermore, the ligand-protein complexes are allowed to simulate their dynamic studies to look into their time-based interaction stability and also, a parallel study of ADME properties for the hit molecules is also performed. Important insights from the studies revealed that the interactions are persistent and molecules may be considered for further optimization in clinical investigation.Communicated by Ramaswamy H. Sarma.

Docking covalent targets for drug discovery: stimulating the computer-aided drug design community of possible pitfalls and erroneous practices

The continuous approval of covalent drugs in recent years for the treatment of diseases has led to an increased search for covalent agents by medicinal chemists and computational scientists worldwide. In the computational parlance, molecular docking which is a popular tool to investigate the interaction of a ligand and a protein target, does not account for the formation of covalent bond, and the increasing application of these conventional programs to covalent targets in early drug discovery practice is a matter of utmost concern. Thus, in this comprehensive review, we sought to educate the docking community about the realization of covalent docking and the existence of suitable programs to make their future virtual-screening events on covalent targets worthwhile and scientifically rational. More interestingly, we went beyond the classical description of the functionality of covalent-docking programs down to selecting the 'best' program to consult with during a virtual-screening campaign based on receptor class and covalent warhead chemistry. In addition, we made a highlight on how covalent docking could be achieved using random conventional docking software. And lastly, we raised an alert on the growing erroneous molecular docking practices with covalent targets. Our aim is to guide scientists in the rational docking pursuit when dealing with covalent targets, as this will reduce false-positive results and also increase the reliability of their work for translational research.

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

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

Investigation of the Compatibility between Warheads and Peptidomimetic Sequences of Protease Inhibitors-A Comprehensive Reactivity and Selectivity Study

Covalent peptidomimetic protease inhibitors have gained a lot of attention in drug development in recent years. They are designed to covalently bind the catalytically active amino acids through electrophilic groups called warheads. Covalent inhibition has an advantage in terms of pharmacodynamic properties but can also bear toxicity risks due to non-selective off-target protein binding. Therefore, the right combination of a reactive warhead with a well-suited peptidomimetic sequence is of great importance. Herein, the selectivities of well-known warheads combined with peptidomimetic sequences suited for five different proteases were investigated, highlighting the impact of both structure parts (warhead and peptidomimetic sequence) for affinity and selectivity. Molecular docking gave insights into the predicted binding modes of the inhibitors inside the binding pockets of the different enzymes. Moreover, the warheads were investigated by NMR and LC-MS reactivity assays against serine/threonine and cysteine nucleophile models, as well as by quantum mechanics simulations.

Computational Design, Synthesis, and Biophysical Evaluation of β-Amido Boronic Acids as SARS-CoV-2 Mpro Inhibitors

The COVID-19 pandemic has given a strong impetus to the search for antivirals active on SARS-associated coronaviruses. Over these years, numerous vaccines have been developed and many of these are effective and clinically available. Similarly, small molecules and monoclonal antibodies have also been approved by the FDA and EMA for the treatment of SARS-CoV-2 infection in patients who could develop the severe form of COVID-19. Among the available therapeutic tools, the small molecule nirmatrelvir was approved in 2021. It is a drug capable of binding to the M^pro protease, an enzyme encoded by the viral genome and essential for viral intracellular replication. In this work, by virtual screening of a focused library of β-amido boronic acids, we have designed and synthesized a focused library of compounds. All of them were biophysically tested by microscale thermophoresis, attaining encouraging results. Moreover, they also displayed M^pro protease inhibitory activity, as demonstrated by performing enzymatic assays. We are confident that this study will pave the way for the design of new drugs potentially useful for the treatment of SARS-CoV-2 viral infection.

In silico bioprospecting of antiviral compounds from marine fungi and mushroom for rapid development of nutraceuticals against SARS-CoV-2

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) affects human respiratory function that causes COVID-19 disease. COVID-19 has spread rapidly all over the world and became a pandemic within no time. Therefore, it is the need of hour to screen potential lead candidates from natural resources like edible mushrooms and marine fungi. These natural resources are very less explored till now and known to be the source for many medicinal compounds with several health benefits. These medicinal compounds can be easily exploited for the faster development of nutraceuticals for controlling SARS-CoV-2 infections. Our Insilico research suggests, bioactive compounds originating from mushroom and marine fungi shows strong potential to interact with ACE2 receptor or main protease of SARS-CoV-2, showing the inhibition activity towards the enzymatic protease. We performed a series of Insilico studies for the validation of our results, which includes Molecular docking, drug likeness property investigation by Swiss ADME tools, MD simulation, and thermodynamically stable free binding energy calculation. Overall, these results suggest that Ganodermadiol and Heliantriol F bioactive compounds originating from edible mushroom has strong potential to be developed as low-cost nutraceutical against SARS-CoV-2 viral infection. The drug candidate isolated from marine fungi and edible mushroom are highly unexplored for the development of potential alternative drug against SARS-CoV-2 virus with minimum side effects. Though our in silico studies of these compounds are showing a promising results against SARS-CoV-2 main protease and ACE2 receptor binding domain, the effectiveness of these bioactive compounds should be further validated by proper clinical trials.Communicated by Ramaswamy H. Sarma.

Structure-based lead optimization of peptide-based vinyl methyl ketones as SARS-CoV-2 main protease inhibitors

Despite several major achievements in the development of vaccines and antivirals, the fight against SARS-CoV-2 and the health problems accompanying COVID-19 are still ongoing. SARS-CoV-2 main protease (M^pro), an essential viral cysteine protease, is a crucial target for the development of antiviral agents. A virtual screening analysis of in-house cysteine protease inhibitors against SARS-CoV-2 M^pro allowed us to identify two hits (i.e., 1 and 2) bearing a methyl vinyl ketone warhead. Starting from these compounds, we herein report the development of Michael acceptors targeting SARS-CoV-2 M^pro, which differ from each other for the warhead and for the amino acids at the P2 site. The most promising vinyl methyl ketone-containing analogs showed sub-micromolar activity against the viral protease. SPR38, SPR39, and SPR41 were fully characterized, and additional inhibitory properties towards hCatL, which plays a key role in the virus entry into host cells, were observed. SPR39 and SPR41 exhibited single-digit micromolar EC₅₀ values in a SARS-CoV-2 infection model in cell culture.

Discovery of a Novel Trifluoromethyl Diazirine Inhibitor of SARS-CoV-2 Mpro

SARS-CoV-2 M^pro is a chymotrypsin-like cysteine protease playing a relevant role during the replication and infectivity of SARS-CoV-2, the coronavirus responsible for COVID-19. The binding site of M^pro is characterized by the presence of a catalytic Cys145 which carries out the hydrolytic activity of the enzyme. As a consequence, several M^pro inhibitors have been proposed to date in order to fight the COVID-19 pandemic. In our work, we designed, synthesized and biologically evaluated MPD112, a novel inhibitor of SARS-CoV-2 M^pro bearing a trifluoromethyl diazirine moiety. MPD112 displayed in vitro inhibition activity against SARS-CoV-2 M^pro at a low micromolar level (IC₅₀ = 4.1 μM) in a FRET-based assay. Moreover, an inhibition assay against PL^pro revealed lack of inhibition, assuring the selectivity of the compound for the M^pro. Furthermore, the target compound MPD112 was docked within the binding site of the enzyme to predict the established intermolecular interactions in silico. MPD112 was subsequently tested on the HCT-8 cell line to evaluate its effect on human cells' viability, displaying good tolerability, demonstrating the promising biological compatibility and activity of a trifluoromethyl diazirine moiety in the design and development of SARS-CoV-2 M^pro binders.

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.

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.

Development of Urea-Bond-Containing Michael Acceptors as Antitrypanosomal Agents Targeting Rhodesain

Human African Trypanosomiasis (HAT) is a neglected tropical disease widespread in sub-Saharan Africa. Rhodesain, a cysteine protease of Trypanosoma brucei rhodesiense, has been identified as a valid target for the development of anti-HAT agents. Herein, we report a series of urea-bond-containing Michael acceptors, which were demonstrated to be potent rhodesain inhibitors with K_i values ranging from 0.15 to 2.51 nM, and five of them showed comparable k_2nd values to that of K11777, a potent antitrypanosomal agent. Moreover, most of the urea derivatives exhibited single-digit micromolar activity against the protozoa, and the presence of substituents at the P3 position appears to be essential for the antitrypanosomal effect. Replacement of Phe with Leu at the P2 site kept unchanged the inhibitory properties. Compound 7 (SPR7) showed the best compromise in terms of rhodesain inhibition, selectivity, and antiparasitic activity, thus representing a new lead compound for future SAR studies.

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

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

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

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

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

Combined Computational NMR and Molecular Docking Scrutiny of Potential Natural SARS-CoV-2 Mpro Inhibitors

In continuation of the search for potential drugs that inhibit the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), in this work, a combined approach based on the modeling of NMR chemical shifts and molecular docking is suggested to identify the possible suppressors of the main protease of this virus among a number of natural products of diverse nature. Primarily, with the aid of an artificial neural network, the problem of the reliable determination of the stereochemical structure of a number of studied compounds was solved. Complementary to the main goal of this study, theoretical modeling of NMR spectral parameters made it feasible to perform a number of signal reassignments together with introducing some missing NMR data. Finally, molecular docking formalism was applied to the analysis of several natural products that could be chosen as prospective candidates for the role of potential inhibitors of the main protease. The results of this study are believed to assist in further research aimed at the development of specific drugs based on the natural products against COVID-19.

In silico screening-based discovery of novel covalent inhibitors of the SARS-CoV-2 3CL protease

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 3CL protease (3CL^pro) has been regarded as an extremely promising antiviral target for the treatment of coronavirus disease 2019 (COVID-19). Here, we carried out a virtual screening based on commercial compounds database to find novel covalent non-peptidomimetic inhibitors of this protease. It allowed us to identify 3 hit compounds with potential covalent binding modes, which were evaluated through an enzymatic activity assay of the SARS-CoV-2 3CL^pro. Moreover, an X-ray crystal structure of the SARS-CoV-2 3CL^pro in complex with compound 8, the most potent hit with an IC₅₀ value of 8.50 μM, confirmed the covalent binding of the predicted warhead to the catalytic residue C145, as well as portrayed interactions of the compound with S1’ and S2 subsites at the ligand binding pocket. Overall, the present work not merely provided an experiment-validated covalent hit targeting the SARS-CoV-2 3CL^pro, but also displayed a prime example to seeking new covalent small molecules by a feasible and effective computational approach.

A Comparison between Enrichment Optimization Algorithm (EOA)-Based and Docking-Based Virtual Screening

Virtual screening (VS) is a well-established method in the initial stages of many drug and material design projects. VS is typically performed using structure-based approaches such as molecular docking, or various ligand-based approaches. Most docking tools were designed to be as global as possible, and consequently only require knowledge on the 3D structure of the biotarget. In contrast, many ligand-based approaches (e.g., 3D-QSAR and pharmacophore) require prior development of project-specific predictive models. Depending on the type of model (e.g., classification or regression), predictive ability is typically evaluated using metrics of performance on either the training set (e.g.,QCV2) or the test set (e.g., specificity, selectivity or QF1/F2/F32). However, none of these metrics were developed with VS in mind, and consequently, their ability to reliably assess the performances of a model in the context of VS is at best limited. With this in mind we have recently reported the development of the enrichment optimization algorithm (EOA). EOA derives QSAR models in the form of multiple linear regression (MLR) equations for VS by optimizing an enrichment-based metric in the space of the descriptors. Here we present an improved version of the algorithm which better handles active compounds and which also takes into account information on inactive (either known inactive or decoy) compounds. We compared the improved EOA in small-scale VS experiments with three common docking tools, namely, Glide-SP, GOLD and AutoDock Vina, employing five molecular targets (acetylcholinesterase, human immunodeficiency virus type 1 protease, MAP kinase p38 alpha, urokinase-type plasminogen activator, and trypsin I). We found that EOA consistently outperformed all docking tools in terms of the area under the ROC curve (AUC) and EF1% metrics that measured the overall and initial success of the VS process, respectively. This was the case when the docking metrics were calculated based on a consensus approach and when they were calculated based on two different sets of single crystal structures. Finally, we propose that EOA could be combined with molecular docking to derive target-specific scoring functions.

Searching and designing potential inhibitors for SARS-CoV-2 Mpro from natural sources using atomistic and deep-learning calculations

The spread of severe acute respiratory syndrome coronavirus 2 novel coronavirus (SARS-CoV-2) worldwide has caused the coronavirus disease 2019 (COVID-19) pandemic. A hundred million people were infected, resulting in several millions of death worldwide. In order to prevent viral replication, scientists have been aiming to prevent the biological activity of the SARS-CoV-2 main protease (3CL pro or Mpro). In this work, we demonstrate that using a reasonable combination of deep-learning calculations and atomistic simulations could lead to a new approach for developing SARS-CoV-2 main protease (Mpro) inhibitors. Initially, the binding affinities of the natural compounds to SARS-CoV-2 Mpro were estimated via atomistic simulations. The compound tomatine, thevetine, and tribuloside could bind to SARS-CoV-2 Mpro with nanomolar/high-nanomolar affinities. Secondly, the deep-learning (DL) calculations were performed to chemically alter the top-lead natural compounds to improve ligand-binding affinity. The obtained results were then validated by free energy calculations using atomistic simulations. The outcome of the research will probably boost COVID-19 therapy.

The hybrid DeepFrag/atomistic simulation approach could lead to a new scheme for developing SARS-CoV-2 3CLpro/Mpro inhibitors.

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.

Haste makes waste: A critical review of docking-based virtual screening in drug repurposing for SARS-CoV-2 main protease (M-pro) inhibition

This review makes a critical evaluation of 61 peer‐reviewed manuscripts that use a docking step in a virtual screening (VS) protocol to predict SARS‐CoV‐2 M‐pro (M‐pro) inhibitors in approved or investigational drugs. Various manuscripts predict different compounds, even when they use a similar initial dataset and methodology, and most of them do not validate their methodology or results. In addition, a set of known 150 SARS‐CoV‐2 M‐pro inhibitors extracted from the literature and a second set of 81 M‐pro inhibitors and 113 inactive compounds obtained from the COVID Moonshot project were used to evaluate the reliability of using docking scores as feasible predictors of the potency of a SARS‐CoV‐2 M‐pro inhibitor. Using two SARS‐CoV‐2 M‐pro structures and five protein‐ligand docking programs, we proved that the correlation between the pIC₅₀ and docking scores is not good. Neither was any correlation found between the pIC₅₀ and the ∆G calculated with an MM‐GBSA method. When a group of experimentally known inactive compounds was added, neither the docking scores or the ∆G were able to distinguish between compounds with or without M‐pro experimental inhibitory activity. Performances improved when covalent and noncovalent inhibitors were treated separately, but were not good enough to fully support using a docking score as a cutoff value for selecting new putative M‐pro inhibitors or predicting the relative bioactivity of a compound by comparison with a reference compound. The two sets of known SARS‐CoV‐2 M‐pro inhibitors presented here could be used for validating future VS protocols which aim to predict M‐pro inhibitors.

SAR of novel benzothiazoles targeting an allosteric pocket of DENV and ZIKV NS2B/NS3 proteases

In recent years, dengue virus (DENV) and Zika virus (ZIKV), both mosquito-borne members of the Flaviviridae family, have emerged as intercontinental health issues since their vectors have spread from their tropical origins to temperate climate zones due to climate change and increasing globalization. DENV and ZIKV are positive-sense, single-stranded RNA viruses, whose genomes consist of three structural (capsid, membrane precursor, envelope) and seven non-structural (NS) proteins, all of which are initially expressed as a single precursor polyprotein. For virus maturation, the polyprotein processing is accomplished by host proteases and the viral NS2B/NS3 protease complex, whose inhibitors have been shown to be effective antiviral agents with loss of viral pathogenicity. In this work, we elucidate new structure-activity relationships of benzo[d]thiazole-based allosteric NS2B/NS3 inhibitors. We developed a new series of Y-shaped inhibitors, which, with its larger hydrophobic contact surface, should bind to previously unaddressed regions of the allosteric NS2B/NS3 binding pocket. By scaffold-hopping, we varied the benzo[d]thiazole core and identified benzofuran as a new lead scaffold shifting the selectivity of initially ZIKV-targeting inhibitors to higher activities towards the DENV protease. In addition, we were able to increase the ligand efficiency from 0.27 to 0.41 by subsequent inhibitor truncation and identified N-(5,6-dihydroxybenzo[d]thiazol-2-yl)-4-iodobenzamide as a novel sub-micromolar NS2B/NS3 inhibitor. Utilizing cell-based assays, we could prove the antiviral activity in cellulo. Overall, we report new series of sub-micromolar allosteric DENV and ZIKV inhibitors with good efficacy profile in terms of cytotoxicity and protease inhibition selectivity.

Structure-Based Discovery of Novel Nonpeptide Inhibitors Targeting SARS-CoV-2 Mpro

The continual spread of novel coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), posing a severe threat to the health worldwide. The main protease (Mpro, alias 3CLpro) of SARS-CoV-2 is a crucial enzyme for the maturation of viral particles and is a very attractive target for designing drugs to treat COVID-19. Here, we propose a multiple conformation-based virtual screening strategy to discover inhibitors that can target SARS-CoV-2 Mpro. Based on this strategy, nine Mpro structures and a protein mimetics library with 8960 commercially available compounds were prepared to carry out ensemble docking for the first time. Five of the nine structures are apo forms presented in different conformations, whereas the other four structures are holo forms complexed with different ligands. The surface plasmon resonance assay revealed that 6 out of 49 compounds had the ability to bind to SARS-CoV-2 Mpro. The fluorescence resonance energy transfer experiment showed that the biochemical half-maximal inhibitory concentration (IC50) values of the six compounds could hamper Mpro activities ranged from 0.69 ± 0.05 to 2.05 ± 0.92 μM. Evaluation of antiviral activity using the cell-based assay indicated that two compounds (Z1244904919 and Z1759961356) could strongly inhibit the cytopathic effect and reduce replication of the living virus in Vero E6 cells with the half-maximal effective concentrations (EC50) of 4.98 ± 1.83 and 8.52 ± 0.92 μM, respectively. The mechanism of the action for the two inhibitors were further elucidated at the molecular level by molecular dynamics simulation and subsequent binding free energy analysis. As a result, the discovered noncovalent reversible inhibitors with novel scaffolds are promising antiviral drug candidates, which may be used to develop the treatment of COVID-19.

In silico studies of selected xanthophylls as potential candidates against SARS-CoV-2 targeting main protease (Mpro) and papain-like protease (PLpro)

Introduction: The main protease (Mpro) and the papain-like protease (PLpro) are essential for the replication of SARS-CoV-2. Both proteases can be targets for drugs acting against SARS-CoV-2.

Objective: This paper aims to investigate the in silico activity of nine xanthophylls as inhibitors of Mpro and PLpro.

Methods: The structures of Mpro (PDB-ID: 6LU7) and PLpro (PDB-ID: 6W9C) were obtained from RCSB Protein Data Bank and developed with BIOVIA Discovery Studio. Active sites of proteins were performed using CASTp. For docking the PyRx was used. Pharmacokinetic parameters of ADMET were evaluated using SwissADME and pkCSM.

Results: β-cryptoxanthin exhibited the highest binding energy: –7.4 kcal/mol in the active site of Mpro. In PLpro active site, the highest binding energy had canthaxanthin of –9.4 kcal/mol, astaxanthin –9.3 kcal/mol, flavoxanthin –9.2 kcal/mol and violaxanthin –9.2 kcal/mol. ADMET studies presented lower toxicity of xanthophylls in comparison to ritonavir and ivermectin.

Conclusion: Our findings suggest that xanthophylls can be used as potential inhibitors against SARS-CoV-2 main protease and papain-like protease.

SARS-CoV-PLpro-Inhibitoren als mögliche Breitspektrum-Virostatika

The SARS-CoV-encoded papain-like cysteine protease (PLpro) plays crucial roles in viral replication and maturation processes. It is required to cleave the precursor polyproteins into functional proteins. Thus, it is considered to be a promising target for developing specific drugs. For rational optimization of hit compounds, information about the structure-activity relationship (SAR) is fundamental. Herein, we characterize isoindolines as a new class of PLpro inhibitors.