A Review of the Current Landscape of SARS-CoV-2 Main Protease Inhibitors: Have We Hit the Bullseye Yet?

Ensemble docking based virtual screening of SARS-CoV-2 main protease inhibitors

During the first years of COVID-19 pandemic, X-ray structures of the coronavirus drug targets were acquired at an unprecedented rate, giving hundreds of PDB depositions in less than a year. The main protease (Mpro) of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) is the primary validated target of direct-acting antivirals. The selection of the optimal ensemble of structures of Mpro for the docking-driven virtual screening campaign was thus non-trivial and required a systematic and automated approach. Here we report a semi-automated active site RMSD based procedure of ensemble selection from the SARS-CoV-2 Mpro crystallographic data and virtual screening of its inhibitors. The procedure was compared with other approaches to ensemble selection and validated with the help of hand-picked and peer-reviewed activity-annotated libraries. Prospective virtual screening of non-covalent Mpro inhibitors resulted in a new chemotype of thienopyrimidinone derivatives with experimentally confirmed enzyme inhibition.

Breaking the Chain: Protease Inhibitors as Game Changers in Respiratory Viruses Management

Respiratory viral infections (VRTIs) rank among the leading causes of global morbidity and mortality, affecting millions of individuals each year across all age groups. These infections are caused by various pathogens, including rhinoviruses (RVs), adenoviruses (AdVs), and coronaviruses (CoVs), which are particularly prevalent during colder seasons. Although many VRTIs are self-limiting, their frequent recurrence and potential for severe health complications highlight the critical need for effective therapeutic strategies. Viral proteases are crucial for the maturation and replication of viruses, making them promising therapeutic targets. This review explores the pivotal role of viral proteases in the lifecycle of respiratory viruses and the development of protease inhibitors as a strategic response to these infections. Recent advances in antiviral therapy have highlighted the effectiveness of protease inhibitors in curtailing the spread and severity of viral diseases, especially during the ongoing COVID-19 pandemic. It also assesses the current efforts aimed at identifying and developing inhibitors targeting key proteases from major respiratory viruses, including human RVs, AdVs, and (severe acute respiratory syndrome coronavirus-2) SARS-CoV-2. Despite the recent identification of SARS-CoV-2, within the last five years, the scientific community has devoted considerable time and resources to investigate existing drugs and develop new inhibitors targeting the virus's main protease. However, research efforts in identifying inhibitors of the proteases of RVs and AdVs are limited. Therefore, herein, it is proposed to utilize this knowledge to develop new inhibitors for the proteases of other viruses affecting the respiratory tract or to develop dual inhibitors. Finally, by detailing the mechanisms of action and therapeutic potentials of these inhibitors, this review aims to demonstrate their significant role in transforming the management of respiratory viral diseases and to offer insights into future research directions.

Docking and other computing tools in drug design against SARS-CoV-2

The use of computer simulation methods has become an indispensable component in identifying drugs against the SARS-CoV-2 coronavirus. There is a huge body of literature on application of molecular modelling to predict inhibitors against target proteins of SARS-CoV-2. To keep our review clear and readable, we limited ourselves primarily to works that use computational methods to find inhibitors and test the predicted compounds experimentally either in target protein assays or in cell culture with live SARS-CoV-2. Some works containing results of experimental discovery of corresponding inhibitors without using computer modelling are included as examples of a success. Also, some computational works without experimental confirmations are also included if they attract our attention either by simulation methods or by databases used. This review collects studies that use various molecular modelling methods: docking, molecular dynamics, quantum mechanics, machine learning, and others. Most of these studies are based on docking, and other methods are used mainly for post-processing to select the best compounds among those found through docking. Simulation methods are presented concisely, information is also provided on databases of organic compounds that can be useful for virtual screening, and the review itself is structured in accordance with coronavirus target proteins.

On the origins of SARS-CoV-2 main protease inhibitors

In order to address the world-wide health challenge caused by the COVID-19 pandemic, the 3CL protease/SARS-CoV-2 main protease (SARS-CoV-2-Mpro) coded by its nsp5 gene became one of the biochemical targets for the design of antiviral drugs. In less than 3 years of research, 4 inhibitors of SARS-CoV-2-Mpro have actually been authorized for COVID-19 treatment (nirmatrelvir, ensitrelvir, leritrelvir and simnotrelvir) and more such as EDP-235, FB-2001 and STI-1558/Olgotrelvir or five undisclosed compounds (CDI-988, ASC11, ALG-097558, QLS1128 and H-10517) are undergoing clinical trials. This review is an attempt to picture this quite unprecedented medicinal chemistry feat and provide insights on how these cysteine protease inhibitors were discovered. Since many series of covalent SARS-CoV-2-Mpro inhibitors owe some of their origins to previous work on other proteases, we first provided a description of various inhibitors of cysteine-bearing human caspase-1 or cathepsin K, as well as inhibitors of serine proteases such as human dipeptidyl peptidase-4 or the hepatitis C protein complex NS3/4A. This is then followed by a description of the results of the approaches adopted (repurposing, structure-based and high throughput screening) to discover coronavirus main protease inhibitors.

Molecular Mechanism of Labelling Functional Cysteines by Heterocyclic Thiones

Heterocyclic thiones have recently been identified as reversible covalent warheads, consistent with their mild electrophilic nature. Little is known so far about their mechanism of action in labelling nucleophilic sidechains, especially cysteines. The vast number of tractable cysteines promotes a wide range of target proteins to examine; however, our focus was put on functional cysteines. We chose the main protease of SARS-CoV-2 harboring Cys145 at the active site that is a structurally characterized and clinically validated target of covalent inhibitors. We screened an in-house, cysteine-targeting covalent inhibitor library which resulted in several covalent fragment hits with benzoxazole, benzothiazole and benzimidazole cores. Thione derivatives and Michael acceptors were selected for further investigations with the objective of exploring the mechanism of inhibition of the thiones and using the thoroughly characterized Michael acceptors for benchmarking our studies. Classical and hybrid quantum mechanical/molecular mechanical (QM/MM) molecular dynamics simulations were carried out that revealed a new mechanism of covalent cysteine labelling by thione derivatives, which was supported by QM and free energy calculations and by a wide range of experimental results. Our study shows that the molecular recognition step plays a crucial role in the overall binding of both sets of molecules.

Medicinal chemistry strategies towards the development of non-covalent SARS-CoV-2 Mpro inhibitors

The main protease (Mpro) of SARS-CoV-2 is an attractive target in anti-COVID-19 therapy for its high conservation and major role in the virus life cycle. The covalent Mpro inhibitor nirmatrelvir (in combination with ritonavir, a pharmacokinetic enhancer) and the non-covalent inhibitor ensitrelvir have shown efficacy in clinical trials and have been approved for therapeutic use. Effective antiviral drugs are needed to fight the pandemic, while non-covalent Mpro inhibitors could be promising alternatives due to their high selectivity and favorable druggability. Numerous non-covalent Mpro inhibitors with desirable properties have been developed based on available crystal structures of Mpro. In this article, we describe medicinal chemistry strategies applied for the discovery and optimization of non-covalent Mpro inhibitors, followed by a general overview and critical analysis of the available information. Prospective viewpoints and insights into current strategies for the development of non-covalent Mpro inhibitors are also discussed.

Molecular docking and MD simulations reveal protease inhibitors block the catalytic residues in Prp8 intein of Aspergillus fumigatus: a potential target for antimycotics

Resistance to azoles and amphotericin B especially in Aspergillus fumigatus is a growing concern towards the treatment of invasive fungal infection. At this critical juncture, intein splicing would be a productive, and innovative target to establish therapies against resistant strains. Intein splicing is the central event for the activation of host protein, essential for the growth and survival of various microorganisms including A. fumigatus. The splicing process is a four-step protease-like nucleophilic cascade. Thus, we hypothesise that protease inhibitors would successfully halt intein splicing and potentially restrict the growth of the aforementioned pathogen. Using Rosetta Fold and molecular dynamics simulations, we modelled Prp8 intein structure; resembling classic intein fold with horse shoe shaped splicing domain. To fully comprehend the active site of Afu Prp8 intein, C1, T62, H65, H818, N819 from intein sequences and S820, the first C-extein residue are selected. Molecular docking shows that two FDA-approved drugs, i.e. Lufotrelvir and Remdesivir triphosphate efficiently interact with Prp8 intein from the assortment of 212 protease inhibitors. MD simulation portrayed that Prp8 undergoes conformational change upon ligand binding, and inferred the molecular recognition and stability of the docked complexes. Per-residue decomposition analysis confirms the importance of F: block R802, V803, and Q807 binding pocket in intein splicing domain towards recognition of inhibitors, along with active site residues through strong hydrogen bonds and hydrophobic contacts. However, in vitro and in vivo assays are required to confirm the inhibitory action on Prp8 intein splicing; which may pave the way for the development of new antifungals for A. fumigatus.Communicated by Ramaswamy H. Sarma.

Identification of sulphonamide-tethered N-((triazol-4-yl)methyl)isatin derivatives as inhibitors of SARS-CoV-2 main protease

SARS-CoV-2 pandemic in the end of 2019 led to profound consequences on global health and economy. Till producing successful vaccination strategies, the healthcare sectors suffered from the lack of effective therapeutic agents that could control the spread of infection. Thus, academia and the pharmaceutical sector prioritise SARS-CoV-2 antiviral drug discovery. Here, we exploited previous reports highlighting the anti-SARS-CoV-2 activities of isatin-based molecules to develop novel triazolo-isatins for inhibiting main protease (Mpro) of the virus, a crucial enzyme for its replication in the host cells. Particularly, sulphonamide 6b showed promising inhibitory activity with an IC50= 0.249 µM. Additionally, 6b inhibited viral cell proliferation with an IC50 of 4.33 µg/ml, and was non-toxic to VERO-E6 cells (CC50 = 564.74 µg/ml) displaying a selectivity index of 130.4. In silico analysis of 6b disclosed its ability to interact with key residues in the enzyme active site, supporting the obtained in vitro findings.

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

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

In Silico Discovery of Small-Molecule Inhibitors Targeting SARS-CoV-2 Main Protease

The COVID-19 pandemic has caused severe health threat globally, and novel SARS-Cov-2 inhibitors are urgently needed for antiviral treatment. The main protease (M^pro) of the virus is one of the most effective and conserved targets for anti-SARS-CoV-2 drug development. In this study, we utilized a molecular docking-based virtual screening approach against the conserved catalytic site to identify small-molecule inhibitors of SARS-CoV-2 M^pro. Further biological evaluation helped us identify two compounds, AF-399/40713777 and AI-942/42301830, with moderate inhibitory activity. Besides that, the in silico data, including molecular dynamics (MD) simulation, binding free energy calculations, and AMDET profiles, suggested that these two hits could serve as the starting point for the future development of COVID-19 intervention treatments.

Nirmatrelvir and ritonavir combination: an antiviral therapy for COVID-19

INTRODUCTION

The emergence of the Omicron SARS-CoV-2 variant of concern in late November 2021 presaged yet another stage of the COVID-19 pandemic. Paxlovid, a co-packaged dosage form of two antiviral drugs (nirmatrelvir and ritonavir) developed by Pfizer, received its first FDA Emergency Use Authorization (EUA) and conditional marketing by European Medical Agency in patients at high risk of developing severe COVID-19.

AREAS COVERED

We reviewed the timeline of the drug nirmatrelvir from its discovery to authorization by FDA. After 1 year of its authorization, numerous studies and reports on paxlovid's use and post-use consequences are available. This review summarizes the complete journey of paxlovid from its development, preclinical studies, clinical trials, regulatory approvals, ongoing clinical trials, and safety measures, followed by discussions on recent updates on drug-drug interactions, adverse effects, and relapse of COVID-19.

EXPERT OPINION

Paxlovid, a new oral antiviral therapy for COVID-19, has shown promising results in clinical trials and has the potential to be effective against the pandemic, particularly for individuals at high risk of severe illness. Comorbidity usage and pharmacovigilance will play a significant stake in the future of paxlovid development. Second-generation Mpro inhibitors play an important role in the upcoming problems associated with COVID-19.

Mpropred: A machine learning (ML) driven Web-App for bioactivity prediction of SARS-CoV-2 main protease (Mpro) antagonists

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic emerged in 2019 and still requiring treatments with fast clinical translatability. Frequent occurrence of mutations in spike glycoprotein of SARS-CoV-2 led the consideration of an alternative therapeutic target to combat the ongoing pandemic. The main protease (Mpro) is such an attractive drug target due to its importance in maturating several polyproteins during the replication process. In the present study, we used a classification structure-activity relationship (CSAR) model to find substructures that leads to to anti-Mpro activities among 758 non-redundant compounds. A set of 12 fingerprints were used to describe Mpro inhibitors, and the random forest approach was used to build prediction models from 100 distinct data splits. The data set's modelability (MODI index) was found to be robust, with a value of 0.79 above the 0.65 threshold. The accuracy (89%), sensitivity (89%), specificity (73%), and Matthews correlation coefficient (79%) used to calculate the prediction performance, was also found to be statistically robust. An extensive analysis of the top significant descriptors unveiled the significance of methyl side chains, aromatic ring and halogen groups for Mpro inhibition. Finally, the predictive model is made publicly accessible as a web-app named Mpropred in order to allow users to predict the bioactivity of compounds against SARS-CoV-2 Mpro. Later, CMNPD, a marine compound database was screened by our app to predict bioactivity of all the compounds and results revealed significant correlation with their binding affinity to Mpro. Molecular dynamics (MD) simulation and molecular mechanics/Poisson Boltzmann surface area (MM/PBSA) analysis showed improved properties of the complexes. Thus, the knowledge and web-app shown herein can be used to develop more effective and specific inhibitors against the SARS-CoV-2 Mpro. The web-app can be accessed from https://share.streamlit.io/nadimfrds/mpropred/Mpropred_app.py.

Antiviral Therapy of COVID-19

Since the beginning of the COVID-19 pandemic, the scientific community has focused on prophylactic vaccine development. In parallel, the experience of the pharmacotherapy of this disease has increased. Due to the declining protective capacity of vaccines against new strains, as well as increased knowledge about the structure and biology of the pathogen, control of the disease has shifted to the focus of antiviral drug development over the past year. Clinical data on safety and efficacy of antivirals acting at various stages of the virus life cycle has been published. In this review, we summarize mechanisms and clinical efficacy of antiviral therapy of COVID-19 with drugs based on plasma of convalescents, monoclonal antibodies, interferons, fusion inhibitors, nucleoside analogs, and protease inhibitors. The current status of the drugs described is also summarized in relation to the official clinical guidelines for the treatment of COVID-19. In addition, here we describe innovative drugs whose antiviral effect is provided by antisense oligonucleotides targeting the SARS-CoV-2 genome. Analysis of laboratory and clinical data suggests that current antivirals successfully combat broad spectra of emerging strains of SARS-CoV-2 providing reliable defense against COVID-19.

Drug Potency Prediction of SARS-CoV-2 Main Protease Inhibitors Based on a Graph Generative Model

The prediction of a ligand potency to inhibit SARS-CoV-2 main protease (M-pro) would be a highly helpful addition to a virtual screening process. The most potent compounds might then be the focus of further efforts to experimentally validate their potency and improve them. A computational method to predict drug potency, which is based on three main steps, is defined: (1) defining the drug and protein in only one 3D structure; (2) applying graph autoencoder techniques with the aim of generating a latent vector; and (3) using a classical fitting model to the latent vector to predict the potency of the drug. Experiments in a database of 160 drug-M-pro pairs, from which the pIC50 is known, show the ability of our method to predict their drug potency with high accuracy. Moreover, the time spent to compute the pIC50 of the whole database is only some seconds, using a current personal computer. Thus, it can be concluded that a computational tool that predicts, with high reliability, the pIC50 in a cheap and fast way is achieved. This tool, which can be used to prioritize which virtual screening hits, will be further examined in vitro.

Development of 2-chloroquinoline based heterocyclic frameworks as dual inhibitors of SARS-CoV-2 MPro and PLPro

Evolution of new variants of SARS-CoV-2 warrant the need for the continued efforts in identifying target-oriented new drugs. Dual targeting agents against M^Pro and PL^Pro not only overcome the incomplete efficacy but also the drug resistance, which is common problem. Since both these are cysteine proteases, we designed 2-chloroquinoline based molecules with additional imine moiety in the middle as possible nucleophilic warheads. In the first round of design and synthesis, three molecules (C3, C4 and C5) inhibited (Ki < 2 μM) only M^Pro by binding covalently to C145 and one molecule (C10) inhibited both the proteases non-covalently (Ki < 2 μM) with negligible cytotoxicity. Further conversion of the imine in C10 to azetidinone (C11) improved the potency against both the enzymes in the nanomolar range (820 nM against M^Pro and 350 nM against PL^Pro) with no cytotoxicity. Conversion of imine to thiazolidinone (C12), reduced the inhibition by 3-5 folds against both the enzymes. Biochemical and computational studies suggest that C10-C12 bind in the substrate binding pocket of M^Pro and in the BL2 loop of the PL^Pro. Since these dual inhibitors have least cytotoxicity, they could be further explored as therapeutics against the SARS-CoV-2 and other analogous viruses.

Chemical Space Virtual Screening against Hard-to-Drug RNA Methyltransferases DNMT2 and NSUN6

Targeting RNA methyltransferases with small molecules as inhibitors or tool compounds is an emerging field of interest in epitranscriptomics and medicinal chemistry. For two challenging RNA methyltransferases that introduce the 5-methylcytosine (m⁵C) modification in different tRNAs, namely DNMT2 and NSUN6, an ultra-large commercially available chemical space was virtually screened by physicochemical property filtering, molecular docking, and clustering to identify new ligands for those enzymes. Novel chemotypes binding to DNMT2 and NSUN6 with affinities down to K_D,app = 37 µM and K_D,app = 12 µM, respectively, were identified using a microscale thermophoresis (MST) binding assay. These compounds represent the first molecules with a distinct structure from the cofactor SAM and have the potential to be developed into activity-based probes for these enzymes. Additionally, the challenges and strategies of chemical space docking screens with special emphasis on library focusing and diversification are discussed.

Peptide valence-induced breaks in plasmonic coupling

Electrostatic interactions are a key driving force that mediates colloidal assembly. The Schulze-Hardy rule states that nanoparticles have a higher tendency to coagulate in the presence of counterions with high charge valence. However, it is unclear how the Schulze-Hardy rule works when the simple electrolytes are replaced with more sophisticated charge carriers. Here, we designed cationic peptides of varying valencies and demonstrate that their charge screening behaviors on anionic gold nanoparticles (AuNPs) follow the six-power relationship in the Schulze-Hardy rule. This finding further inspires a simple yet effective strategy for measuring SARS-CoV-2 main protease (Mpro) via naked eyes. This work provides a unique avenue for fundamental NP disassembly based on the Schulze-Hardy rule and can help design versatile substrates for colorimetric sensing of other proteases.

Exploration of SARS-CoV-2 Mpro Noncovalent Natural Inhibitors Using Structure-Based Approaches

With the emergence of antibody-evasive omicron subvariants (BA.2.12.1, BA.4, and BA.5), which can compromise the efficacy of vaccination, it is of utmost importance to widen the finite therapeutic options for COVID-19. Although more than 600 co-crystal complexes of Mpro with inhibitors have been revealed, utilizing them to search for novel Mpro inhibitors remains limited. Although there were two major groups of Mpro inhibitors, covalent and noncovalent inhibitors, noncovalent inhibitors were our main focus due to the safety concerns with their covalent counterparts. Hence, this study aimed to explore Mpro noncovalent inhibition ability of phytochemicals extracted from Vietnamese herbals by combining multiple structure-based approaches. By closely inspecting 223 complexes of Mpro with noncovalent inhibitors, a 3D-pharmacophore model representing typical chemical features of Mpro noncovalent inhibitors was generated with good validation scores (sensitivity = 92.11%, specificity = 90.42%, accuracy = 90.65%, and goodness-of-hit score = 0.61). Afterward, the pharmacophore model was applied to explore the potential Mpro inhibitors from our in-house Vietnamese phytochemical database, revealing 18 substances, 5 of which were in vitro assayed. The remaining 13 substances were then examined by induced-fit molecular docking, revealing 12 suitable compounds. A machine-learning activity prediction model was developed to rank the hit, suggesting nigracin and calycosin-7-O-β-glucopyranoside as promising Mpro natural noncovalent inhibitors.

Surely you are joking, Mr Docking!

In the wake of recent COVID-19 pandemics scientists around the world rushed to deliver numerous CADD (Computer-Aided Drug Discovery) methods and tools that could be reliably used to discover novel drug candidates against the SARS-CoV-2 virus. With that, there emerged a trend of a significant democratization of CADD that contributed to the rapid development of various COVID-19 drug candidates currently undergoing different stages of validation. On the other hand, this democratization also inadvertently led to the surge rapidly performed molecular docking studies to nominate multiple scores of novel drug candidates supported by computational arguments only. Albeit driven by best intentions, most of such studies also did not follow best practices in the field that require experience and expertise learned through multiple rigorously designed benchmarking studies and rigorous experimental validation. In this Viewpoint we reflect on recent disbalance between small number of rigorous and comprehensive studies and the proliferation of purely computational studies enabled by the ease of docking software availability. We further elaborate on the hyped oversale of CADD methods' ability to rapidly yield viable drug candidates and reiterate the critical importance of rigor and adherence to the best practices of CADD in view of recent emergence of AI and Big Data in the field.

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.

Computer-Aided Screening for Potential Coronavirus 3-Chymotrypsin-like Protease (3CLpro) Inhibitory Peptides from Putative Hemp Seed Trypsinized Peptidome

To control the COVID-19 pandemic, antivirals that specifically target the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are urgently required. The 3-chymotrypsin-like protease (3CLpro) is a promising drug target since it functions as a catalytic dyad in hydrolyzing polyprotein during the viral life cycle. Bioactive peptides, especially food-derived peptides, have a variety of functional activities, including antiviral activity, and also have a potential therapeutic effect against COVID-19. In this study, the hemp seed trypsinized peptidome was subjected to computer-aided screening against the 3CLpro of SARS-CoV-2. Using predictive trypsinized products of the five major proteins in hemp seed (i.e., edestin 1, edestin 2, edestin 3, albumin, and vicilin), the putative hydrolyzed peptidome was established and used as the input dataset. To select the Cannabis sativa antiviral peptides (csAVPs), a predictive bioinformatic analysis was performed by three webserver screening programs: iAMPpred, AVPpred, and Meta-iAVP. The amino acid composition profile comparison was performed by COPid to screen for the non-toxic and non-allergenic candidates, ToxinPred and AllerTOP and AllergenFP, respectively. GalaxyPepDock and HPEPDOCK were employed to perform the molecular docking of all selected csAVPs to the 3CLpro of SARS-CoV-2. Only the top docking-scored candidate (csAVP4) was further analyzed by molecular dynamics simulation for 150 nanoseconds. Molecular docking and molecular dynamics revealed the potential ability and stability of csAVP4 to inhibit the 3CLpro catalytic domain with hydrogen bond formation in domain 2 with short bonding distances. In addition, these top ten candidate bioactive peptides contained hydrophilic amino acid residues and exhibited a positive net charge. We hope that our results may guide the future development of alternative therapeutics against COVID-19.

A comprehensive review on pharmacologic agents, immunotherapies and supportive therapeutics for COVID-19

The emergence of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has affected many countries throughout the world. As urgency is a necessity, most efforts have focused on identifying small molecule drugs that can be repurposed for use as anti-SARS-CoV-2 agents. Although several drug candidates have been identified using in silico method and in vitro studies, most of these drugs require the support of in vivo data before they can be considered for clinical trials. Several drugs are considered promising therapeutic agents for COVID-19. In addition to the direct-acting antiviral drugs, supportive therapies including traditional Chinese medicine, immunotherapies, immunomodulators, and nutritional therapy could contribute a major role in treating COVID-19 patients. Some of these drugs have already been included in the treatment guidelines, recommendations, and standard operating procedures. In this article, we comprehensively review the approved and potential therapeutic drugs, immune cells-based therapies, immunomodulatory agents/drugs, herbs and plant metabolites, nutritional and dietary for COVID-19.

Prediction of Recurrent Mutations in SARS-CoV-2 Using Artificial Neural Networks

Predicting SARS-CoV-2 mutations is difficult, but predicting recurrent mutations driven by the host, such as those caused by host deaminases, is feasible. We used machine learning to predict which positions from the SARS-CoV-2 genome will hold a recurrent mutation and which mutations will be the most recurrent. We used data from April 2021 that we separated into three sets: a training set, a validation set, and an independent test set. For the test set, we obtained a specificity value of 0.69, a sensitivity value of 0.79, and an Area Under the Curve (AUC) of 0.8, showing that the prediction of recurrent SARS-CoV-2 mutations is feasible. Subsequently, we compared our predictions with updated data from January 2022, showing that some of the false positives in our prediction model become true positives later on. The most important variables detected by the model's Shapley Additive exPlanation (SHAP) are the nucleotide that mutates and RNA reactivity. This is consistent with the SARS-CoV-2 mutational bias pattern and the preference of some host deaminases for specific sequences and RNA secondary structures. We extend our investigation by analyzing the mutations from the variants of concern Alpha, Beta, Delta, Gamma, and Omicron. Finally, we analyzed amino acid changes by looking at the predicted recurrent mutations in the M-pro and spike proteins.

Synthesis and In Silico Study of Some New bis-[1,3,4]thiadiazolimines and bis-Thiazolimines as Potential Inhibitors for SARS-CoV-2 Main Protease

A novel series of bis-[1,3,4]thiadiazolimines, and bis-thiazolimines, with alkyl linker, were synthesized through general routes from cyclization of 1,1′-(hexane-1,6-diyl)bis(3-phenylthiourea) and hydrazonoyl halides or α-haloketones, respectively. Docking studies were applied to test the binding affinity of the synthesized products against the M^pro of SARS-CoV-2. The best compound, 5h, has average binding energy (−7.50 ± 0.58 kcal/mol) better than that of the positive controls O6K and N3 (−7.36 ± 0.34 and −6.36 ± 0.31 kcal/mol). Additionally, the docking poses (H-bonds and hydrophobic contacts) of the tested compounds against the M^pro using the PLIP web server were analyzed.

Recent Drug Development and Medicinal Chemistry Approaches for the Treatment of SARS-CoV-2 Infection and COVID-19

COVID-19, caused by SARS-CoV-2 infection, continues to be a major public health crisis around the globe. Development of vaccines and the first cluster of antiviral drugs has brought promise and hope for prevention and treatment of severe coronavirus disease. However, continued development of newer, safer, and more effective antiviral drugs are critically important to combat COVID-19 and counter the looming pathogenic variants. Studies of the coronavirus life cycle revealed several important biochemical targets for drug development. In the present review, we focus on recent drug design and medicinal chemistry efforts in small molecule drug discovery, including the development of nirmatrelvir that targets viral protein synthesis and remdesivir and molnupiravir that target viral RdRp. These are recent FDA approved drugs for the treatment of COVID-19.

Development of a novel peptide inhibitor of subtilisin BPN'

Proteinaceous protease inhibitors can strongly and specifically inhibit cognate proteases, but their use as pharmaceuticals is limited by their size. As such, the development of effective protease peptide inhibitors would be beneficial for biochemical studies and drug discovery. In this study, we applied a phage display system to select subtilisin BPN'-binding peptides and evaluated their inhibitory activities against subtilisin BPN'. A 12mer peptide with an intramolecular disulfide bond inhibited subtilisin BPN' (K_i value of 13.0 nm). Further mutational analyses of the peptide resulted in the development of a short peptide inhibitor against subtilisin BPN' that showed high inhibitory activity and binding affinity (K_i value of 0.30 nm). This activity was found to be derived from the conformational rigidity caused by the intramolecular disulfide bond and the small residue at the P1' site and from the interaction of the P4 and P6' residues with subtilisin BPN'.

Interaction of panduratin A and derivatives with the SARS-CoV-2 main protease (mpro): a molecular docking study

Panduratin A (Pa-A) is a prenylated cyclohexenyl chalcone isolated from the rhizomes of the medicinal and culinary plant Boesenbergia rotunda (L.) Mansf., commonly called fingerroots. Both an ethanolic plant extract and Pa-A have shown a marked antiviral activity against the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), responsible for the COVID-19 pandemic disease. Pa-A functions as a protease inhibitor inhibiting infection of human cells by the virus. We have modeled the interaction of Pa-A, and 26 panduratin analogues with the main protease (M^pro) of SARS-CoV-2 using molecular docking. The natural product 4-hydroxypanduratin showed a higher M^pro binding capacity than Pa-A and isopanduratin A. The interaction with M^Pro of all known panduratin derivatives (Pa-A to Pa-Y) have been compared, together with more than 60 reference products. Three compounds emerged as potential robust M^Pro binders: Pa-R, Pa-V, Pa-S, with a binding capacity significantly higher than 4-OH-Pa-A and Pa-A. The empirical energy of interaction (ΔE) calculated with the best compound in the panduratin series, Pa-R bound to M^pro, surpassed that measured with the top reference protease inhibitors such a ruprintrivir, lufotrelvir, and glecaprevir. Structure-binding relationships are discussed. Compounds with a flavanone moiety (PA-R/S) are the best binders, better than those with a chromene unit (Pa-F/G). The extended molecules (such as Pa-V) exhibit good M^pro binding, but the dimeric compound Pa-Y is too long and protrudes outside the binding cavity. The work provides novel ideas to guide the design of new molecules interacting with M^pro.Communicated by Ramaswamy H. Sarma.

In Silico Analysis Using SARS-CoV-2 Main Protease and a Set of Phytocompounds to Accelerate the Development of Therapeutic Components against COVID-19

SARS-CoV-2, the virus that caused the widespread COVID-19 pandemic, is homologous to SARS-CoV. It would be ideal to develop antivirals effective against SARS-CoV-2. In this study, we chose one therapeutic target known as the main protease (Mpro) of SARS-CoV-2. A crystal structure (Id: 6LU7) from the protein data bank (PDB) was used to accomplish the screening and docking studies. A set of phytocompounds was used for the docking investigation. The nature of the interaction and the interacting residues indicated the molecular properties that are essential for significant affinity. Six compounds were selected, based on the docking as well as the MM-GBSA score. Pentagalloylglucose, Shephagenin, Isoacteoside, Isoquercitrin, Kappa-Carrageenan, and Dolabellin are the six compounds with the lowest binding energies (−12 to −8 kcal/mol) and show significant interactions with the target Mpro protein. The MMGBSA scores of these compounds are highly promising, and they should be investigated to determine their potential as Mpro inhibitors, beneficial for COVID-19 treatment. In this study, we highlight the crucial role of in silico technologies in the search for novel therapeutic components. Computational biology, combined with structural biology, makes drug discovery studies more rigorous and reliable, and it creates a scenario where researchers can use existing drug components to discover new roles as modulators or inhibitors for various therapeutic targets. This study demonstrated that computational analyses can yield promising findings in the search for potential drug components. This work demonstrated the significance of increasing in silico and wetlab research to generate improved structure-based medicines.

Potential Resistance of SARS-CoV-2 Main Protease (Mpro) against Protease Inhibitors: Lessons Learned from HIV-1 Protease

Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome 2 (SARS-CoV-2), has been one of the most devastating pandemics of recent times. The lack of potent novel antivirals had led to global health crises; however, emergence and approval of potent inhibitors of the viral main protease (Mpro), such as Pfizer's newly approved nirmatrelvir, offers hope not only in the therapeutic front but also in the context of prophylaxis against the infection. By their nature, RNA viruses including human immunodeficiency virus (HIV) have inherently high mutation rates, and lessons learnt from previous and currently ongoing pandemics have taught us that these viruses can easily escape selection pressure through mutation of vital target amino acid residues in monotherapeutic settings. In this paper, we review nirmatrelvir and its binding to SARS-CoV-2 Mpro and draw a comparison to inhibitors of HIV protease that were rendered obsolete by emergence of resistance mutations, emphasizing potential pitfalls in the design of inhibitors that may be of important relevance to the long-term use of novel inhibitors against SARS-CoV-2.