Drug Repurposing for Candidate SARS-CoV-2 Main Protease Inhibitors by a Novel In Silico Method

Molecular docking as a tool for the discovery of novel insight about the role of acid sphingomyelinase inhibitors in SARS- CoV-2 infectivity

Recently, COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants, caused > 6 million deaths. Symptoms included respiratory strain and complications, leading to severe pneumonia. SARS-CoV-2 attaches to the ACE-2 receptor of the host cell membrane to enter. Targeting the SARS-CoV-2 entry may effectively inhibit infection. Acid sphingomyelinase (ASMase) is a lysosomal protein that catalyzes the conversion of sphingolipid (sphingomyelin) to ceramide. Ceramide molecules aggregate/assemble on the plasma membrane to form "platforms" that facilitate the viral intake into the cell. Impairing the ASMase activity will eventually disrupt viral entry into the cell. In this review, we identified the metabolism of sphingolipids, sphingolipids' role in cell signal transduction cascades, and viral infection mechanisms. Also, we outlined ASMase structure and underlying mechanisms inhibiting viral entry 40 with the aid of inhibitors of acid sphingomyelinase (FIASMAs). In silico molecular docking analyses of FIASMAs with inhibitors revealed that dilazep (S = - 12.58 kcal/mol), emetine (S = - 11.65 kcal/mol), pimozide (S = - 11.29 kcal/mol), carvedilol (S = - 11.28 kcal/mol), mebeverine (S = - 11.14 kcal/mol), cepharanthine (S = - 11.06 kcal/mol), hydroxyzin (S = - 10.96 kcal/mol), astemizole (S = - 10.81 kcal/mol), sertindole (S = - 10.55 kcal/mol), and bepridil (S = - 10.47 kcal/mol) have higher inhibition activity than the candidate drug amiodarone (S = - 10.43 kcal/mol), making them better options for inhibition.

An in silico analysis of the interaction of marine sponge-derived bioactive compounds with type 2 diabetes mellitus targets DPP-4 and PTP1B

Type 2 diabetes is a medical condition involving elevated blood glucose levels resulting from impaired or improper insulin utilization. As the number of type 2 diabetes cases increases each year, there is an urgent need to develop novel drugs having new targets and/or complementing existing therapeutic protocols. In this regard, marine sponge-derived compounds hold great potential due to their potent biological activity and structural diversity. In this study, a small library of 50 marine sponge-derived compounds were examined for their activity towards type 2 diabetes targets, namely dipeptidyl peptidase-4 (DPP-4) and protein tyrosine phosphatase 1B (PTP1B). The compounds were first subjected to molecular docking on protein models based on their respective co-crystal structures to assess binding free energies (BFE) and conformations. Clustering analysis yielded BFE that ranged from 24.54 kcal/mol to -9.97 kcal/mol for DPP-4, and from -4.98 kcal/mol to -8.67 kcal/mol for PTP1B. Interaction analysis on the top ten compounds with the most negative BFE towards each protein target showed similar intermolecular interactions and key interacting residues as in the previously solved co-crystal structure. These compounds were subjected to absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiling to characterize drug-likeness and combining the results from these analyses, (S)-6'-debromohamacanthin B was identified as a potential multi-target inhibitor of DPP-4 and PTP1B, having favorable protein interaction, no Lipinski violations, good gastrointestinal (GI) tract absorption, blood-brain barrier (BBB) penetration, and no predicted toxicity. Finally, the interaction of (S)-6'-debromohamacanthin B with the two proteins was validated using molecular dynamics simulations over 100 ns through RMSD, radius of gyration, PCA, and molecular mechanics Poisson-Boltzmann surface area (MMPBSA) confirming favorable interactions with the respective proteins.Communicated by Ramaswamy H. Sarma.

In Silico molecular docking and dynamic analysis of natural compounds against major non-structural proteins of SARS-COV-2

COVID-19 has infected millions and significantly affected the global economy and healthcare systems. Despite continuous lockdowns, symptomatic management with currently available medications, and numerous vaccination drives, it is still far more difficult to control. Against COVID-19 infection, the pressure to develop vaccines and drugs has led to using some currently available medications like remdesivir, azithromycin, hydroxychloroquine and ritonavir. Understanding the importance and potential of harmless molecules to tackle SARS-COV-2, we designed the present study to identify potential natural phytocompounds. In the present study, we docked natural compounds and standard drugs against SARS-COV-2 proteins: papain-like protease, main protease and helicase. ADME/T and ProTox-II analyses were used to determine the toxicity of phytocompounds and drugs. The docking analysis revealed that podophyllotoxin gave the highest binding affinity scores of -8.1, -7.1 and -7.4 kcal/mol against PLpro, Mpro and helicase, respectively. Among the control drugs, doxycycline hydrochloride showed the highest binding affinity of -10.5, -8.4 and -8.8 kcal/mol against PLpro, Mpro and helicase. The results of this study revealed that podophyllotoxin and doxycycline hydrochloride could be promising inhibitors against SARS-Cov-2. Molecular dynamic simulations were executed for the best docked (PLpro-podophyllotoxin) complex, and the results displayed stable conformation and convergence. Energy plot results predicted a global minima average energy of -95 kcal/mol and indicated podophyllotoxin's role in stabilizing protein and making it compact and complex. FarPPI server used MM/GBSA approach to determine free binding affinity, and helicase-gallic acid complex showed the highest affinity, respectively. Therefore, it can be concluded that there is still a need for in vitro and in vivo studies to support further and validate these findings and validate these findings.Communicated by Ramaswamy H. Sarma.

Evaluating anti-viral effect of Ivermectin on porcine epidemic diarrhea virus and analyzing the related genes and signaling pathway by RNA-seq in vitro

Porcine epidemic diarrhea virus (PEDV) has catastrophic impacts on the global pig industry. However, there remains no effective drugs for PEDV infection. Ivermectin is an FDA-approved anthelmintic drug used to treat worm infections. In this study, we reported the broad-spectrum antiviral activity of Ivermectin in vitro. Ivermectin can inhibit PEDV infections of different genotypes. Avermectin derivatives can also inhibit PEDV infections. A time of addition assay showed that Ivermectin exhibited potent anti-PEDV activity when added simultaneously with or post virus infection. Furthermore, Ivermectin significantly inhibited the late stage of viral infection by affecting viral release. RNA sequencing indicates Ivermectin induces cell cycle arrest, which may be related to its ability to inhibit viral release. Interestingly, when combined with Niclosamide, Ivermectin demonstrated an enhanced anti-PEDV effect. These findings highlight Ivermectin as a novel antiviral agent with potential for the development of drugs against PEDV infection.

Artificial intelligence based virtual screening study for competitive and allosteric inhibitors of the SARS-CoV-2 main protease

SARS-CoV-2 is a highly contagious and dangerous coronavirus that first appeared in late 2019 causing COVID-19, a pandemic of acute respiratory illnesses that is still a threat to health and the general public safety. We performed deep docking studies of 800 M unique compounds in both the active and allosteric sites of the SARS-COV-2 Main Protease (Mpro) and the 15 M and 13 M virtual hits obtained were further taken for conventional docking and molecular dynamic (MD) studies. The best XP Glide docking scores obtained were -14.242 and -12.059 kcal/mol by CHEMBL591669 and the highest binding affinities were -10.5 kcal/mol (from 444215) and -11.2 kcal/mol (from NPC95421) for active and allosteric sites, respectively. Some hits can bind both sites making them a great area of concern. Re-docking of 8 random allosteric complexes in the active site shows a significant reduction in docking scores with a t-test P value of 2.532 × 10-11 at 95% confidence. Some specific interactions have higher elevations in docking scores. MD studies on 15 complexes show that single-ligand systems are stable as compared to double-ligand systems, and the allosteric binders identified are shown to modulate the active site binding as evidenced by the changes in the interaction patterns and stability of ligands and active site residues. When an allosteric complex was docked to the second monomer to check for homodimer formation, the validated homodimer could not be re-established, further supporting the potential of the identified allosteric binders. These findings could be important in developing novel therapeutics against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

High-Throughput Screening for the Potential Inhibitors of SARS-CoV-2 with Essential Dynamic Behavior

Global health security has been challenged by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. Due to the lengthy process of generating vaccinations, it is vital to reposition currently available drugs in order to relieve anti-epidemic tensions and accelerate the development of therapies for Coronavirus Disease 2019 (COVID-19), the public threat caused by SARS-CoV-2. High throughput screening techniques have established their roles in the evaluation of already available medications and the search for novel potential agents with desirable chemical space and more cost-effectiveness. Here, we present the architectural aspects of highthroughput screening for SARS-CoV-2 inhibitors, especially three generations of virtual screening methodologies with structural dynamics: ligand-based screening, receptor-based screening, and machine learning (ML)-based scoring functions (SFs). By outlining the benefits and drawbacks, we hope that researchers will be motivated to adopt these methods in the development of novel anti- SARS-CoV-2 agents.

Protein-ligand binding affinity prediction with edge awareness and supervised attention

Accurate prediction of protein-ligand binding affinity is crucial in structure-based drug design but remains some challenges even with recent advances in deep learning: (1) Existing methods neglect the edge information in protein and ligand structure data; (2) current attention mechanisms struggle to capture true binding interactions in the small dataset. Herein, we proposed SEGSA_DTA, a SuperEdge Graph convolution-based and Supervised Attention-based Drug-Target Affinity prediction method, where the super edge graph convolution can comprehensively utilize node and edge information and the multi-supervised attention module can efficiently learn the attention distribution consistent with real protein-ligand interactions. Results on the multiple datasets show that SEGSA_DTA outperforms current state-of-the-art methods. We also applied SEGSA_DTA in repurposing FDA-approved drugs to identify potential coronavirus disease 2019 (COVID-19) treatments. Besides, by using SHapley Additive exPlanations (SHAP), we found that SEGSA_DTA is interpretable and further provides a new quantitative analytical solution for structure-based lead optimization.

Dual-Reporter System for Real-Time Monitoring of SARS-CoV-2 Main Protease Activity in Live Cells Enables Identification of an Allosteric Inhibition Path

The SARS-CoV-2 pandemic is an ongoing threat to global health, and the continuing emergence of contagious variants highlights the urgent need for additional antiviral therapy to attenuate COVID-19 disease. The SARS-CoV-2 main protease (3CL^pro) presents an attractive target for such therapy due to its high sequence conservation and key role in the viral life cycle. In this study, we designed a fluorescent-luminescent cell-based reporter for the detection and quantification of 3CL^pro intracellular activity. Employing this platform, we examined the efficiency of known protease inhibitors against 3CL^pro and further identified potent inhibitors through high-throughput chemical screening. Computational analysis confirmed a direct interaction of the lead compounds with the protease catalytic site and identified a prototype for efficient allosteric inhibition. These developments address a pressing need for a convenient sensor and specific targets for both virus detection and rapid discovery of potential inhibitors.

A review on computer-aided chemogenomics and drug repositioning for rational COVID-19 drug discovery

Application of materials capable of energy harvesting to increase the efficiency and environmental adaptability is sometimes reflected in the ability of discovery of some traces in an environment-either experimentally or computationally-to enlarge practical application window. The emergence of computational methods, particularly computer-aided drug discovery (CADD), provides ample opportunities for the rapid discovery and development of unprecedented drugs. The expensive and time-consuming process of traditional drug discovery is no longer feasible, for nowadays the identification of potential drug candidates is much easier for therapeutic targets through elaborate in silico approaches, allowing the prediction of the toxicity of drugs, such as drug repositioning (DR) and chemical genomics (chemogenomics). Coronaviruses (CoVs) are cross-species viruses that are able to spread expeditiously from the into new host species, which in turn cause epidemic diseases. In this sense, this review furnishes an outline of computational strategies and their applications in drug discovery. A special focus is placed on chemogenomics and DR as unique and emerging system-based disciplines on CoV drug and target discovery to model protein networks against a library of compounds. Furthermore, to demonstrate the special advantages of CADD methods in rapidly finding a drug for this deadly virus, numerous examples of the recent achievements grounded on molecular docking, chemogenomics, and DR are reported, analyzed, and interpreted in detail. It is believed that the outcome of this review assists developers of energy harvesting materials and systems for detection of future unexpected kinds of CoVs or other variants.

Allosteric Binding Sites of the SARS-CoV-2 Main Protease: Potential Targets for Broad-Spectrum Anti-Coronavirus Agents

The current pandemic caused by the COVID-19 disease has reached everywhere in the world and has affected every aspect of our lives. As of the current data, the World Health Organization (WHO) has reported more than 300 million confirmed COVID-19 cases worldwide and more than 5 million deaths. M^pro is an enzyme that plays a key role in the life cycle of the SARS-CoV-2 virus, and it is vital for the disease progression. The M^pro enzyme seems to have several allosteric sites that can hinder the enzyme catalytic activity. Furthermore, some of these allosteric sites are located at or nearby the dimerization interface which is essential for the overall M^pro activity. In this review paper, we investigate the potential of the M^pro allosteric site to act as a drug target, especially since they interestingly appear to be resistant to mutation. The work is illustrated through three subsequent sections: First, the two main categories of M^pro allosteric sites have been explained and discussed. Second, a total of six pockets have been studied and evaluated for their druggability and cavity characteristics. Third, the experimental and computational attempts for the discovery of new allosteric inhibitors have been illustrated and discussed. To sum up, this review paper gives a detailed insight into the feasibility of developing new M^pro inhibitors to act as a potential treatment for the COVID-19 disease.

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.

SperoPredictor: An Integrated Machine Learning and Molecular Docking-Based Drug Repurposing Framework With Use Case of COVID-19

The global spread of the SARS coronavirus 2 (SARS-CoV-2), its manifestation in human hosts as a contagious disease, and its variants have induced a pandemic resulting in the deaths of over 6,000,000 people. Extensive efforts have been devoted to drug research to cure and refrain the spread of COVID-19, but only one drug has received FDA approval yet. Traditional drug discovery is inefficient, costly, and unable to react to pandemic threats. Drug repurposing represents an effective strategy for drug discovery and reduces the time and cost compared to de novo drug discovery. In this study, a generic drug repurposing framework (SperoPredictor) has been developed which systematically integrates the various types of drugs and disease data and takes the advantage of machine learning (Random Forest, Tree Ensemble, and Gradient Boosted Trees) to repurpose potential drug candidates against any disease of interest. Drug and disease data for FDA-approved drugs (n = 2,865), containing four drug features and three disease features, were collected from chemical and biological databases and integrated with the form of drug-disease association tables. The resulting dataset was split into 70% for training, 15% for testing, and the remaining 15% for validation. The testing and validation accuracies of the models were 99.3% for Random Forest and 99.03% for Tree Ensemble. In practice, SperoPredictor identified 25 potential drug candidates against 6 human host-target proteomes identified from a systematic review of journals. Literature-based validation indicated 12 of 25 predicted drugs (48%) have been already used for COVID-19 followed by molecular docking and re-docking which indicated 4 of 13 drugs (30%) as potential candidates against COVID-19 to be pre-clinically and clinically validated. Finally, SperoPredictor results illustrated the ability of the platform to be rapidly deployed to repurpose the drugs as a rapid response to emergent situations (like COVID-19 and other pandemics).

Antiviral Activity of Repurposing Ivermectin against a Panel of 30 Clinical SARS-CoV-2 Strains Belonging to 14 Variants

Over the past two years, several variants of SARS-CoV-2 have emerged and spread all over the world. However, infectivity, clinical severity, re-infection, virulence, transmissibility, vaccine responses and escape, and epidemiological aspects have differed between SARS-CoV-2 variants. Currently, very few treatments are recommended against SARS-CoV-2. Identification of effective drugs among repurposing FDA-approved drugs is a rapid, efficient and low-cost strategy against SARS-CoV-2. One of those drugs is ivermectin. Ivermectin is an antihelminthic agent that previously showed in vitro effects against a SARS-CoV-2 isolate (Australia/VI01/2020 isolate) with an IC50 of around 2 µM. We evaluated the in vitro activity of ivermectin on Vero E6 cells infected with 30 clinically isolated SARS-CoV-2 strains belonging to 14 different variants, and particularly 17 strains belonging to six variants of concern (VOC) (variants related to Wuhan, alpha, beta, gamma, delta and omicron). The in vitro activity of ivermectin was compared to those of chloroquine and remdesivir. Unlike chloroquine (EC50 from 4.3 ± 2.5 to 29.3 ± 5.2 µM) or remdesivir (EC50 from 0.4 ± 0.3 to 25.2 ± 9.4 µM), ivermectin showed a relatively homogeneous in vitro activity against SARS-CoV-2 regardless of the strains or variants (EC50 from 5.1 ± 0.5 to 6.7 ± 0.4 µM), except for one omicron strain (EC50 = 1.3 ± 0.5 µM). Ivermectin (No. EC50 = 219, mean EC50 = 5.7 ± 1.0 µM) was, overall, more potent in vitro than chloroquine (No. EC50 = 214, mean EC50 = 16.1 ± 9.0 µM) (p = 1.3 × 10-34) and remdesivir (No. EC50 = 201, mean EC50 = 11.9 ± 10.0 µM) (p = 1.6 × 10-13). These results should be interpreted with caution regarding the potential use of ivermectin in SARS-CoV-2-infected patients: it is difficult to translate in vitro study results into actual clinical treatment in patients.

Identification of potential biological targets of oxindole scaffolds via in silico repositioning strategies

Background: Drug repurposing is an alternative strategy to traditional drug discovery that aims at predicting new uses for already existing drugs or clinical candidates. Drug repurposing has many advantages over traditional drug development, such as reduced attrition rates, time and costs. This is especially the case considering that most drugs investigated for repurposing have already been assessed for their safety in clinical trials. Repurposing campaigns can also be designed for libraries of already synthesized molecules at different levels of biological experimentation, from null to in vitro and in vivo. Such an extension of the "repurposing" concept is expected to provide significant advantages for the identification of novel drugs, as the synthetic accessibility of the desired compounds is often one of the limiting factors in the traditional drug discovery pipeline. Methods: In this work, we performed a computational repurposing campaign on a library of previously synthesized oxindole-based compounds, in order to identify potential new targets for this versatile scaffold. To this aim, ligand-based approaches were firstly applied to evaluate the similarity degree of the investigated compound library, with respect to ligands extracted from the DrugBank, Protein Data Bank (PDB) and ChEMBL databases. In particular, the 2D fingerprint-based and 3D shape-based similarity profiles were evaluated and compared for the oxindole derivates. Results: The analyses predicted a set of potential candidate targets for repurposing, some of them emerging by consensus of different computational analyses. One of the identified targets, i.e., the vascular endothelial growth factor receptor 2 (VEGFR-2) kinase, was further investigated by means of docking calculations, followed by biological testing of one candidate. Conclusions: While the compound did not show potent inhibitory activity towards VEGFR-2, the study highlighted several other possibilities of therapeutically relevant targets that may be worth of consideration for drug repurposing.

Identification of SARS-CoV-2 Papain-like Protease (PLpro) Inhibitors Using Combined Computational Approach

In the current pandemic, finding an effective drug to prevent or treat the infection is the highest priority. A rapid and safe approach to counteract COVID-19 is in silico drug repurposing. The SARS-CoV-2 PLpro promotes viral replication and modulates the host immune system, resulting in inhibition of the host antiviral innate immune response, and therefore is an attractive drug target. In this study, we used a combined in silico virtual screening for candidates for SARS-CoV-2 PLpro protease inhibitors. We used the Informational spectrum method applied for Small Molecules for searching the Drugbank database followed by molecular docking. After in silico screening of drug space, we identified 44 drugs as potential SARS-CoV-2 PLpro inhibitors that we propose for further experimental testing.

Identification of potential therapeutic targets and mechanisms of COVID-19 through network analysis and screening of chemicals and herbal ingredients

After experiencing the COVID-19 pandemic, it is widely acknowledged that a rapid drug repurposing method is highly needed. A series of useful drug repurposing tools have been developed based on data-driven modeling and network pharmacology. Based on the disease module, we identified several hub proteins that play important roles in the onset and development of the COVID-19, which are potential targets for repositioning approved drugs. Moreover, different network distance metrics were applied to quantify the relationship between drug targets and COVID-19 disease targets in the protein-protein-interaction (PPI) network and predict COVID-19 therapeutic effects of bioactive herbal ingredients and chemicals. Furthermore, the tentative mechanisms of candidates were illustrated through molecular docking and gene enrichment analysis. We obtained 15 chemical and 15 herbal ingredient candidates and found that different drugs may play different roles in the process of virus invasion and the onset and development of the COVID-19 disease. Given pandemic outbreaks, our method has an undeniable immense advantage in the feasibility analysis of drug repurposing or drug screening, especially in the analysis of herbal ingredients.

Advances in the computational landscape for repurposed drugs against COVID-19

The COVID-19 pandemic has caused millions of deaths and massive societal distress worldwide. Therapeutic solutions are urgently needed, but de novo drug development remains a lengthy process. One promising alternative is computational drug repurposing, which enables the prioritization of existing compounds through fast in silico analyses. Recent efforts based on molecular docking, machine learning, and network analysis have produced actionable predictions. Some predicted drugs, targeting viral proteins and pathological host pathways are undergoing clinical trials. Here, we review this work, highlight drugs with high predicted efficacy and classify their mechanisms of action. We discuss the strengths and limitations of the published methodologies and outline possible future directions. Finally, we curate a list of COVID-19 data portals and other repositories that could be used to accelerate future research.

NMR Spectroscopy of the Main Protease of SARS-CoV-2 and Fragment-Based Screening Identify Three Protein Hotspots and an Antiviral Fragment

The main protease (3CLp) of the SARS-CoV-2, the causative agent for the COVID-19 pandemic, is one of the main targets for drug development. To be active, 3CLp relies on a complex interplay between dimerization, active site flexibility, and allosteric regulation. The deciphering of these mechanisms is a crucial step to enable the search for inhibitors. In this context, using NMR spectroscopy, we studied the conformation of dimeric 3CLp from the SARS-CoV-2 and monitored ligand binding, based on NMR signal assignments. We performed a fragment-based screening that led to the identification of 38 fragment hits. Their binding sites showed three hotspots on 3CLp, two in the substrate binding pocket and one at the dimer interface. F01 is a non-covalent inhibitor of the 3CLp and has antiviral activity in SARS-CoV-2 infected cells. This study sheds light on the complex structure-function relationships of 3CLp and constitutes a strong basis to assist in developing potent 3CLp inhibitors.

Drug repurposing against SARS-CoV-1, SARS-CoV-2 and MERS-CoV

Since the beginning of the COVID-19 pandemic, large in silico screening studies and numerous in vitro studies have assessed the antiviral activity of various drugs on SARS-CoV-2. In the context of health emergency, drug repurposing represents the most relevant strategy because of the reduced time for approval by international medicines agencies, the low cost of development and the well-known toxicity profile of such drugs. Herein, we aim to review drugs with in vitro antiviral activity against SARS-CoV-2, combined with molecular docking data and results from preliminary clinical studies. Finally, when considering all these previous findings, as well as the possibility of oral administration, 11 molecules consisting of nelfinavir, favipiravir, azithromycin, clofoctol, clofazimine, ivermectin, nitazoxanide, amodiaquine, heparin, chloroquine and hydroxychloroquine, show an interesting antiviral activity that could be exploited as possible drug candidates for COVID-19 treatment.

A survey on computational methods in discovering protein inhibitors of SARS-CoV-2

The outbreak of acute respiratory disease in 2019, namely Coronavirus Disease-2019 (COVID-19), has become an unprecedented healthcare crisis. To mitigate the pandemic, there are a lot of collective and multidisciplinary efforts in facilitating the rapid discovery of protein inhibitors or drugs against COVID-19. Although many computational methods to predict protein inhibitors have been developed [ 1– 5], few systematic reviews on these methods have been published. Here, we provide a comprehensive overview of the existing methods to discover potential inhibitors of COVID-19 virus, so-called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). First, we briefly categorize and describe computational approaches by the basic algorithms involved in. Then we review the related biological datasets used in such predictions. Furthermore, we emphatically discuss current knowledge on SARS-CoV-2 inhibitors with the latest findings and development of computational methods in uncovering protein inhibitors against COVID-19.

Phenothiazines as dual inhibitors of SARS-CoV-2 main protease and COVID-19 inflammation

COVID-19, caused by the severe acute respiratory coronavirus 2 (SARS-CoV-2), currently has no treatment for acute infection. The main protease (Mpro) of SARS-CoV-2 is an essential enzyme for viral replication and an attractive target for disease intervention. The phenothiazine moiety has demonstrated drug versatility for biological systems, including inhibition of butyrylcholinesterase, a property important in the cholinesterase anti-inflammatory cascade. Nineteen phenothiazine drugs were investigated using in silico modelling techniques to predict binding energies and inhibition constants (Ki values) with SARS-CoV-2 Mpro. Because most side-effects of phenothiazines are due to interactions with various neurotransmitter receptors and transporters, phenothiazines with few such interactions were also investigated. All compounds were found to bind to the active site of SARS-CoV-2 Mpro and showed Ki values ranging from 1.30 to 52.4 µM in a rigid active site. Nine phenothiazines showed inhibition constants <10 µM. The compounds with limited interactions with neurotransmitter receptors and transporters showed micromolar (µM) Ki values. Docking results were compared with remdesivir and showed similar interactions with key residues Glu-166 and Gln-189 in the active site. This work has identified several phenothiazines with limited neurotransmitter receptor and transporter interactions and that may provide the dual action of inhibiting SARS-CoV-2 Mpro to prevent viral replication and promote the release of anti-inflammatory cytokines to curb viral-induced inflammation. These compounds are promising candidates for further investigation against SARS-CoV-2.

Repurposing functional inhibitors of acid sphingomyelinase (fiasmas): an opportunity against SARS-CoV-2 infection?

WHAT IS KNOWN AND OBJECTIVE

Infection by SARS-CoV-2, the virus responsible of COVID-19, is associated with limited treatment options. The purpose of this study was to evaluate the rationale for repurposing functional inhibitors of acid sphingomyelinase (FIASMAs), several of which are approved medicines, for the treatment of SAR-CoV-2 infections.

COMMENT

We propose and discuss the FIASMAs' lysosomotropism as a possible explanation for their observed in vitro activities against viruses, and more specifically against infections caused by coronaviruses such as SARS-CoV-2. Successful in vitro-to-in vivo translation of FIASMAs requires that their pharmacokinetics (dosing regimen and drug-drug interactions) are matched with viral kinetics.

WHAT IS NEW AND CONCLUSION

Drug repurposing to ensure rapid patient access to effective treatment has garnered much attention in this era of the COVID-19 pandemic. The observed lysosomotropic activity of small-molecule FIASMA compounds suggests that their repurposing as potential drugs against SARS-CoV-2 is promising.

Efficacy and safety of dihydroorotate dehydrogenase (DHODH) inhibitors "leflunomide" and "teriflunomide" in Covid-19: A narrative review

Dihydroorotate dehydrogenase (DHODH) is rate-limiting enzyme in biosynthesis of pyrimidone which catalyzes the oxidation of dihydro-orotate to orotate. Orotate is utilized in the biosynthesis of uridine-monophosphate. DHODH inhibitors have shown promise as antiviral agent against Cytomegalovirus, Ebola, Influenza, Epstein Barr and Picornavirus. Anti-SARS-CoV-2 action of DHODH inhibitors are also coming up. In this review, we have reviewed the safety and efficacy of approved DHODH inhibitors (leflunomide and teriflunomide) against COVID-19. In target-centered in silico studies, leflunomide showed favorable binding to active site of MPro and spike: ACE2 interface. In artificial-intelligence/machine-learning based studies, leflunomide was among the top 50 ligands targeting spike: ACE2 interaction. Leflunomide is also found to interact with differentially regulated pathways [identified by KEGG (Kyoto Encyclopedia of Genes and Genomes) and reactome pathway analysis of host transcriptome data] in cogena based drug-repurposing studies. Based on GSEA (gene set enrichment analysis), leflunomide was found to target pathways enriched in COVID-19. In vitro, both leflunomide (EC50 41.49 ± 8.8 μmol/L) and teriflunomide (EC50 26 μmol/L) showed SARS-CoV-2 inhibition. In clinical studies, leflunomide showed significant benefit in terms of decreasing the duration of viral shredding, duration of hospital stay and severity of infection. However, no advantage was seen while combining leflunomide and IFN alpha-2a among patients with prolonged post symptomatic viral shredding. Common adverse effects of leflunomide were hyperlipidemia, leucopenia, neutropenia and liver-function alteration. Leflunomide/teriflunomide may serve as an agent of importance to achieve faster virological clearance in COVID-19, however, findings needs to be validated in bigger sized placebo controlled studies.

Drugs repurposing against SARS-CoV2 and the new variant B.1.1.7 (alpha strain) targeting the spike protein: molecular docking and simulation studies

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) is responsible for the global COVID-19 pandemic and millions of deaths worldwide. In December 2020, a new alpha strain of SARS-CoV2 was identified in the United Kingdom. It was referred to as VUI 202012/01 (Alpha strain modelled under investigation, 2020, month 12, number 01). The interaction between spike protein and ACE2 receptor is a prerequisite for entering virion into the host cell. The present study is focussed on the spike protein of the SARS-COV 2, involving the comparison of binding affinity of new alpha strain modelled spike with previous strain spike (PDB ID:7DDN) using in silico molecular docking, dynamics and simulation studies. The molecular docking studies of the alpha strain modelled spike protein confirmed its higher affinity for the ACE2 receptor than the spike protein of the dominant strain. Similar computational approaches have also been used to investigate the potency of FDA approved drugs from the ZINC Database against the spike protein of new alpha strain modelled and old ones. The drug molecules which showed strong affinity for both the spike proteins are then subjected to ADME analysis. The overall binding energy of Conivaptan (-107.503 kJ/mol) and Trosec (-94.029 kJ/mol) is indicative of their strong binding affinities, well supported by interactions with critical residues.

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We investigated the potential FDA drugs for repurposing against the spike protein of alpha strain modelled of SARS-CoV-2.

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Spike protein of alpha strain modelled of SARS-CoV-2 has more affinity for the ACE2 receptor of host cell than previous strains and, therefore, is more contagious.

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Conivaptan, Ecamsule and Trosec are common drugs that bind strongly with spike protein of both the strains .

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Molecular Docking and simulation studies show that Conivaptan and Trosec emerged as potential inhibitors of the alpha strain modelled spike protein.

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.

Comprehensive Consensus Analysis of SARS-CoV-2 Drug Repurposing Campaigns

The current COVID-19 pandemic has elicited extensive repurposing efforts (both small and large scale) to rapidly identify COVID-19 treatments among approved drugs. Herein, we provide a literature review of large-scale SARS-CoV-2 antiviral drug repurposing efforts and highlight a marked lack of consistent potency reporting. This variability indicates the importance of standardizing best practices-including the use of relevant cell lines, viral isolates, and validated screening protocols. We further surveyed available biochemical and virtual screening studies against SARS-CoV-2 targets (Spike, ACE2, RdRp, PLpro, and Mpro) and discuss repurposing candidates exhibiting consistent activity across diverse, triaging assays and predictive models. Moreover, we examine repurposed drugs and their efficacy against COVID-19 and the outcomes of representative repurposed drugs in clinical trials. Finally, we propose a drug repurposing pipeline to encourage the implementation of standard methods to fast-track the discovery of candidates and to ensure reproducible results.

Elucidation of Cryptic and Allosteric Pockets within the SARS-CoV-2 Main Protease

The SARS-CoV-2 pandemic has rapidly spread across the globe, posing an urgent health concern. Many quests to computationally identify treatments against the virus rely on in silico small molecule docking to experimentally determined structures of viral proteins. One limit to these approaches is that protein dynamics are often unaccounted for, leading to overlooking transient, druggable conformational states. Using Gaussian accelerated molecular dynamics to enhance sampling of conformational space, we identified cryptic pockets within the SARS-CoV-2 main protease, including some within regions far from the active site. These simulations sampled comparable dynamics and pocket volumes to conventional brute force simulations carried out on two orders of magnitude greater timescales.

Update on Functional Inhibitors of Acid Sphingomyelinase (FIASMAs) in SARS-CoV-2 Infection

The SARS-CoV-2 outbreak is characterized by the need of the search for curative drugs for treatment. In this paper, we present an update of knowledge about the interest of the functional inhibitors of acid sphingomyelinase (FIASMAs) in SARS-CoV-2 infection. Forty-nine FIASMAs have been suggested in the treatment of SARS-CoV-2 infection using in silico, in vitro or in vivo studies. Further studies using large-sized, randomized and double-blinded controlled clinical trials are needed to evaluate FIASMAs in SARS-CoV-2 infection as off-label therapy.

Blue Biotechnology: Computational Screening of Sarcophyton Cembranoid Diterpenes for SARS-CoV-2 Main Protease Inhibition

The coronavirus pandemic has affected more than 150 million people, while over 3.25 million people have died from the coronavirus disease 2019 (COVID-19). As there are no established therapies for COVID-19 treatment, drugs that inhibit viral replication are a promising target; specifically, the main protease (Mpro) that process CoV-encoded polyproteins serves as an Achilles heel for assembly of replication-transcription machinery as well as down-stream viral replication. In the search for potential antiviral drugs that target Mpro, a series of cembranoid diterpenes from the biologically active soft-coral genus Sarcophyton have been examined as SARS-CoV-2 Mpro inhibitors. Over 360 metabolites from the genus were screened using molecular docking calculations. Promising diterpenes were further characterized by molecular dynamics (MD) simulations based on molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations. According to in silico calculations, five cembranoid diterpenes manifested adequate binding affinities as Mpro inhibitors with ΔGbinding < -33.0 kcal/mol. Binding energy and structural analyses of the most potent Sarcophyton inhibitor, bislatumlide A (340), was compared to darunavir, an HIV protease inhibitor that has been recently subjected to clinical-trial as an anti-COVID-19 drug. In silico analysis indicates that 340 has a higher binding affinity against Mpro than darunavir with ΔGbinding values of -43.8 and -34.8 kcal/mol, respectively throughout 100 ns MD simulations. Drug-likeness calculations revealed robust bioavailability and protein-protein interactions were identified for 340; biochemical signaling genes included ACE, MAPK14 and ESR1 as identified based on a STRING database. Pathway enrichment analysis combined with reactome mining revealed that 340 has the capability to re-modulate the p38 MAPK pathway hijacked by SARS-CoV-2 and antagonize injurious effects. These findings justify further in vivo and in vitro testing of 340 as an antiviral agent against SARS-CoV-2.

In Vitro Evaluation of the Antiviral Activity of Methylene Blue Alone or in Combination against SARS-CoV-2

A new severe acute respiratory syndrome coronavirus (SARS-CoV-2) causing coronavirus diseases 2019 (COVID-19), which emerged in Wuhan, China in December 2019, has spread worldwide. Currently, very few treatments are officially recommended against SARS-CoV-2. Identifying effective, low-cost antiviral drugs with limited side effects that are affordable immediately is urgently needed. Methylene blue, a synthesized thiazine dye, may be a potential antiviral drug. Antiviral activity of methylene blue used alone or in combination with several antimalarial drugs or remdesivir was assessed against infected Vero E6 cells infected with two clinically isolated SARS-CoV-2 strains (IHUMI-3 and IHUMI-6). Effects both on viral entry in the cell and on post-entry were also investigated. After 48 h post-infection, the viral replication was estimated by RT-PCR. The median effective concentration (EC₅₀) and 90% effective concentration (EC₉₀) of methylene blue against IHUMI-3 were 0.41 ± 0.34 µM and 1.85 ± 1.41 µM, respectively; 1.06 ± 0.46 µM and 5.68 ± 1.83 µM against IHUMI-6. Methylene blue interacted at both entry and post-entry stages of SARS-CoV-2 infection in Vero E6 cells as retrieved for hydroxychloroquine. The effects of methylene blue were additive with those of quinine, mefloquine and pyronaridine. The combinations of methylene blue with chloroquine, hydroxychloroquine, desethylamodiaquine, piperaquine, lumefantrine, ferroquine, dihydroartemisinin and remdesivir were antagonist. These results support the potential interest of methylene blue to treat COVID-19.

The Repurposed Drugs Suramin and Quinacrine Cooperatively Inhibit SARS-CoV-2 3CLpro In Vitro

Since the first report of a new pneumonia disease in December 2019 (Wuhan, China) the WHO reported more than 148 million confirmed cases and 3.1 million losses globally up to now. The causative agent of COVID-19 (SARS-CoV-2) has spread worldwide, resulting in a pandemic of unprecedented magnitude. To date, several clinically safe and efficient vaccines (e.g., Pfizer-BioNTech, Moderna, Johnson & Johnson, and AstraZeneca COVID-19 vaccines) as well as drugs for emergency use have been approved. However, increasing numbers of SARS-Cov-2 variants make it imminent to identify an alternative way to treat SARS-CoV-2 infections. A well-known strategy to identify molecules with inhibitory potential against SARS-CoV-2 proteins is repurposing clinically developed drugs, e.g., antiparasitic drugs. The results described in this study demonstrated the inhibitory potential of quinacrine and suramin against SARS-CoV-2 main protease (3CLpro). Quinacrine and suramin molecules presented a competitive and noncompetitive inhibition mode, respectively, with IC50 values in the low micromolar range. Surface plasmon resonance (SPR) experiments demonstrated that quinacrine and suramin alone possessed a moderate or weak affinity with SARS-CoV-2 3CLpro but suramin binding increased quinacrine interaction by around a factor of eight. Using docking and molecular dynamics simulations, we identified a possible binding mode and the amino acids involved in these interactions. Our results suggested that suramin, in combination with quinacrine, showed promising synergistic efficacy to inhibit SARS-CoV-2 3CLpro. We suppose that the identification of effective, synergistic drug combinations could lead to the design of better treatments for the COVID-19 disease and repurposable drug candidates offer fast therapeutic breakthroughs, mainly in a pandemic moment.

Are vanadium complexes druggable against the main protease Mpro of SARS-CoV-2? - A computational approach

In silico techniques helped explore the binding capacities of the SARS-CoV-2 main protease (M^pro) for a series of metalloorganic compounds. Along with small size vanadium complexes a vanadium-containing derivative of the peptide-like inhibitor N3 (N-[(5-methylisoxazol-3-yl)carbonyl]alanyl-l-valyl-N1-((1R,2Z)-4-(benzyloxy)-4-oxo-1-{[(3R)-2-oxopyrrolidin-3-yl] methyl }but-2-enyl)-l-leucinamide) was designed from the crystal structure with PDB entry code 6LU7. On theoretical grounds our consensus docking studies evaluated the binding affinities at the hitherto known binding site of Chymotrypsin-like protease (3CLpro) of SARS-CoV-2 for existing and designed vanadium complexes. This main virus protease (M^pro) has a Cys-His dyad at the catalytic site that is characteristic of metal-dependent or metal-inhibited hydrolases. M^pro was compared to the human protein-tyrosine phosphatase 1B (hPTP1B) with a comparable catalytic dyad. HPTP1B is a key regulator at an early stage in the signalling cascade of the insulin hormone for glucose uptake into cells. The vanadium-ligand binding site of hPTP1B is located in a larger groove on the surface of M^pro. Vanadium constitutes a well-known phosphate analogue. Hence, its study offers possibilities to design promising vanadium-containing binders to SARS-CoV-2. Given the favourable physicochemical properties of vanadium nuclei, such organic vanadium complexes could become drugs not only for pharmacotherapy but also diagnostic tools for early infection detection in patients. This work presents the in silico design of a potential lead vanadium compound. It was tested along with 20 other vanadium-containing complexes from the literature in a virtual screening test by docking to inhibit M^pro of SARS-CoV-2.

A review on drug repurposing applicable to COVID-19

Drug repurposing involves the identification of new applications for existing drugs at a lower cost and in a shorter time. There are different computational drug-repurposing strategies and some of these approaches have been applied to the coronavirus disease 2019 (COVID-19) pandemic. Computational drug-repositioning approaches applied to COVID-19 can be broadly categorized into (i) network-based models, (ii) structure-based approaches and (iii) artificial intelligence (AI) approaches. Network-based approaches are divided into two categories: network-based clustering approaches and network-based propagation approaches. Both of them allowed to annotate some important patterns, to identify proteins that are functionally associated with COVID-19 and to discover novel drug–disease or drug–target relationships useful for new therapies. Structure-based approaches allowed to identify small chemical compounds able to bind macromolecular targets to evaluate how a chemical compound can interact with the biological counterpart, trying to find new applications for existing drugs. AI-based networks appear, at the moment, less relevant since they need more data for their application.

Rutin and flavone analogs as prospective SARS-CoV-2 main protease inhibitors: In silico drug discovery study

Coronavirus disease 2019 (COVID-19) is a new pandemic characterized by quick spreading and illness of the respiratory system. To date, there is no specific therapy for Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2). Flavonoids, especially rutin, have attracted considerable interest as a prospective SARS-CoV-2 main protease (M^pro) inhibitor. In this study, a database containing 2017 flavone analogs was prepared and screened against SARS-CoV-2 M^pro using the molecular docking technique. According to the results, 371 flavone analogs exhibited good potency towards M^pro with docking scores less than −9.0 kcal/mol. Molecular dynamics (MD) simulations, followed by molecular mechanics-generalized Born surface area (MM/GBSA) binding energy calculations, were performed for the top potent analogs in complex with M^pro. Compared to rutin, PubChem-129-716-607 and PubChem-885-071-27 showed better binding affinities against SARS-CoV-2 M^pro over 150 ns MD course with ΔG_binding values of −69.0 and −68.1 kcal/mol, respectively. Structural and energetic analyses demonstrated high stability of the identified analogs inside the SARS-CoV-2 M^pro active site over 150 ns MD simulations. The oral bioavailabilities of probable SARS-CoV-2 M^pro inhibitors were underpinned using drug-likeness parameters. A comparison of the binding affinities demonstrated that the MM/GBSA binding energies of the identified flavone analogs were approximately three and two times less than those of lopinavir and baicalein, respectively. In conclusion, PubChem-129-716-607 and PubChem-885-071-27 are promising anti-COVID-19 drug candidates that warrant further clinical investigations.

In Vitro Effects of Doxycycline on Replication of Feline Coronavirus

Feline infectious peritonitis (FIP) is a sporadic fatal disease of cats caused by a virulent variant of feline coronavirus (FCoV), referred to as FIP virus (FIPV). Treatment options are limited, and most of the affected cats die or are euthanized. Anecdotally, doxycycline has been used to treat FIP-affected cats, but there are currently no data to support or discourage such treatment. The aim of this study was to establish whether doxycycline inhibits replication of FIPV in vitro. The virus was cultured in Crandell-Rees feline kidney cells with various concentrations of doxycycline (0 to 50 µg/mL). The level of FIPV in cultures was determined by virus titration and FCoV-specific reverse-transcription quantitative PCR. Cell viability was also monitored. There was no difference in the level of infectious virus or viral RNA between doxycycline-treated and untreated cultures at 3, 12- and 18-hours post-infection. However, at 24 h, the growth of FIPV was inhibited by approximately two logs in cultures with >10 µg/mL doxycycline. This inhibition was dose-dependent, with inhibitory concentration 50% (IC₅₀) 4.1 µg/mL and IC₉₀ 5.4 µg/mL. Our data suggest that doxycycline has some inhibitory effect on FIPV replication in vitro, which supports future clinical trials of its use for the treatment of FIP-affected cats.

n-Propyl 6-amino-2,6-dideoxy-2,2-difluoro-β-d-glucopyranoside is a good inhibitor for the β-galactosidase from E. coli

A convenient route has been developed for the synthesis of novel 6-amino-2,2-(or 3,3-difluoro)-2-(or 3),6-dideoxy-hexopyranoses. Biological screening showed these compounds as good inhibitors for several glycosidases. Especially n-propyl 6-amino-2,6-dideoxy-2,2-difluoro-β-d-glucopyranoside (8) was an excellent competitive inhibitor for the β-galactosidase from E. coli holding a K_i of 0.50 μM.

Targeting allosteric pockets of SARS-CoV-2 main protease Mpro

Repurposing of antivirals is an attractive therapeutic option for the treatment of COVID-19. Main protease (M^pro), also called 3 C-like protease (3CL^pro) is a key protease of SARS-CoV-2 involved in viral replication, and is a promising drug target for antivirals. A major challenge to test the efficacy of antivirals is the conformational plasticity of M^pro and its future mutation prone flexibility. Suitable choice of drugs in catalytic and allosteric pockets appear to be essential for combination therapy. Current study, based on docking and extensive set of MD simulations, finds the combination of Elbasvir, Glecaprevir and Ritonavir to be a viable candidate for further experimental drug testing/pharmacophore design for M^pro.Communicated by Ramaswamy H. Sarma.

Factual insights of the allosteric inhibition mechanism of SARS-CoV-2 main protease by quercetin: an in silico analysis

SARS-CoV-2 main protease (Mpro) cleaves the viral polypeptide 1a and 1ab in a site-specific ((L-Q|(S, A, G)) manner and produce functional enzymes for mediating viral replication. Numerous studies have reported synthetic competitive inhibitors against this target enzyme but increase in substrate concentration often reduces the effectiveness of such inhibitors. Allosteric inhibition by natural compound can provide safe and effective treatment by alleviating this limitation. Present study deals with in silico allosteric inhibition analysis of quercetin, against SARS-CoV-2-Mpro. Molecular docking of quercetin with Mpro revealed consistent binding of quercetin at a site other than active site in multiple runs, with the highest binding energy of - 8.31 kcal/mol, forming 6 H-bonds with residues Gln127, Cys128, Lys137, Asp289 and Glu290. Molecular dynamic simulation of 50 ns revealed high stability of Mpro-quercetin complex with RMSD values ranging from 0.1 to 0.25 nm. Moreover, native-Mpro and Mpro-quercetin complex conformations extracted at different time points from simulation trajectories were subjected to active site-specific docking with modelled substrate peptide (AVLQSGFR) by ZDOCK server. Results displayed site-specific cleavage of peptide when docked with native-Mpro. While substrate peptide remained intact when docked with Mpro-quercetin complex, also the binding energy of peptide reduced from 785 to 86 from 1 to 50 ns as quercetin induced alterations in the active site cavity reducing its affinity for the substrate. Further, no interactions were noticed between peptide and active site residues of Mpro-quercetin complex conformations at 40 and 50 ns. Hence, quercetin displayed effective allosteric inhibition potential against SARS-CoV-2 Mpro, and can be developed into an efficient treatment for COVID-19.

A Revisit to the Research Updates of Drugs, Vaccines, and Bioinformatics Approaches in Combating COVID-19 Pandemic

A new strain of coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) responsible for the coronavirus disease 2019 (COVID-19) pandemic was first detected in the city of Wuhan in Hubei province, China in late December 2019. To date, more than 1 million deaths and nearly 57 million confirmed cases have been recorded across 220 countries due to COVID-19, which is the greatest threat to global public health in our time. Although SARS-CoV-2 is genetically similar to other coronaviruses, i.e., SARS and Middle East respiratory syndrome coronavirus (MERS-CoV), no confirmed therapeutics are yet available against COVID-19, and governments, scientists, and pharmaceutical companies worldwide are working together in search for effective drugs and vaccines. Repurposing of relevant therapies, developing vaccines, and using bioinformatics to identify potential drug targets are strongly in focus to combat COVID-19. This review deals with the pathogenesis of COVID-19 and its clinical symptoms in humans including the most recent updates on candidate drugs and vaccines. Potential drugs (remdesivir, hydroxychloroquine, azithromycin, dexamethasone) and vaccines [mRNA-1273; measles, mumps and rubella (MMR), bacille Calmette-Guérin (BCG)] in human clinical trials are discussed with their composition, dosage, mode of action, and possible release dates according to the trial register of US National Library of Medicines (clinicaltrials.gov), European Union (clinicaltrialsregister.eu), and Chinese Clinical Trial Registry (chictr.org.cn) website. Moreover, recent reports on in silico approaches like molecular docking, molecular dynamics simulations, network-based identification, and homology modeling are included, toward repurposing strategies for the use of already approved drugs against newly emerged pathogens. Limitations of effectiveness, side effects, and safety issues of each approach are also highlighted. This review should be useful for the researchers working to find out an effective strategy for defeating SARS-CoV-2.

Discovery of new TLR7 agonists by a combination of statistical learning-based QSAR, virtual screening, and molecular dynamics

Search for new antiviral medications has surged in the past two years due to the COVID-19 crisis. Toll-like receptor 7 (TLR7) is among one of the most important TLR proteins of innate immunity that is responsible for broad antiviral response and immune system control. TLR7 agonists, as both vaccine adjuvants and immune response modulators, are among the top drug candidates for not only our contemporary viral pandemic but also other diseases. The agonists of TLR7 have been utilized as vaccine adjuvants and antiviral agents. In this study, we hybridized a statistical learning-based QSAR model with molecular docking and molecular dynamics simulation to extract new antiviral drugs by drug repurposing of the DrugBank database. First, we manually curated a dataset consisting of TLR7 agonists. The molecular descriptors of these compounds were extracted, and feature engineering was done to restrict the number of features to 45. We applied a statistically inspired modification of the partial least squares (SIMPLS) method to build our QSAR model. In the next stage, the DrugBank database was virtually screened structurally using molecular docking, and the top compounds for the guanosine binding site of TLR were identified. The result of molecular docking was again screened by the ligand-based approach of QSAR to eliminate compounds that do not display strong EC₅₀ values by the previously trained model. We then subjected the final results to molecular dynamics simulation and compared our compounds with imiquimod (an FDA-approved TLR7 agonist) and compound 1 (the most active compound against TLR7 in vitro, EC₅₀ = 0.2 nM). Our results evidently demonstrate that cephalosporins and nucleotide analogues (especially acyclic nucleotide analogues such as adefovir and cidofovir) are computationally potent agonists of TLR7. We finally reviewed some publications about cephalosporins that, just like pieces of a puzzle, completed our conclusion.

Structure-Based Virtual Screening and Biochemical Validation to Discover a Potential Inhibitor of the SARS-CoV-2 Main Protease

The recent pandemic caused by SARS-CoV-2 has led the world to a standstill, causing a medical and economic crisis worldwide. This crisis has triggered an urgent need to discover a possible treatment strategy against this novel virus using already-approved drugs. The main protease (Mpro) of this virus plays a critical role in cleaving the translated polypeptides that makes it a potential drug target against COVID-19. Taking advantage of the recently discovered three-dimensional structure of Mpro, we screened approved drugs from the Drug Bank to find a possible inhibitor against Mpro using computational methods and further validating them with biochemical studies. The docking and molecular dynamics study revealed that DB04983 (denufosol) showed the best glide docking score, -11.884 kcal/mol, and MM-PBSA binding free energy, -10.96 kcal/mol. Cobicistat, cangrelor (previous computational studies in our lab), and denufosol (current study) were tested for the in vitro inhibitory effects on Mpro. The IC50 values of these drugs were ∼6.7 μM, 0.9 mM, and 1.3 mM, respectively, while the values of dissociation constants calculated using surface plasmon resonance were ∼2.1 μM, 0.7 mM, and 1.4 mM, respectively. We found that cobicistat is the most efficient inhibitor of Mpro both in silico and in vitro. In conclusion, cobicistat, which is already an FDA-approved drug being used against HIV, may serve as a good inhibitor against the main protease of SARS-CoV-2 that, in turn, can help in combating COVID-19, and these results can also form the basis for the rational structure-based drug design against COVID-19.

In Vitro Antiviral Activity of Doxycycline against SARS-CoV-2

In December 2019, a new severe acute respiratory syndrome coronavirus (SARS-CoV-2), causing coronavirus disease 2019 (COVID-19), emerged in Wuhan, China. Despite containment measures, SARS-CoV-2 spread in Asia, Southern Europe, then in America and currently in Africa. Identifying effective antiviral drugs is urgently needed. An efficient approach to drug discovery is to evaluate whether existing approved drugs can be efficient against SARS-CoV-2. Doxycycline, which is a second-generation tetracycline with broad-spectrum antimicrobial, antimalarial and anti-inflammatory activities, showed in vitro activity on Vero E6 cells infected with a clinically isolated SARS-CoV-2 strain (IHUMI-3) with median effective concentration (EC₅₀) of 4.5 ± 2.9 µM, compatible with oral uptake and intravenous administrations. Doxycycline interacted both on SARS-CoV-2 entry and in replication after virus entry. Besides its in vitro antiviral activity against SARS-CoV-2, doxycycline has anti-inflammatory effects by decreasing the expression of various pro-inflammatory cytokines and could prevent co-infections and superinfections due to broad-spectrum antimicrobial activity. Therefore, doxycycline could be a potential partner of COVID-19 therapies. However, these results must be taken with caution regarding the potential use in SARS-CoV-2-infected patients: it is difficult to translate in vitro study results to actual clinical treatment in patients. In vivo evaluation in animal experimental models is required to confirm the antiviral effects of doxycycline on SARS-CoV-2 and more trials of high-risk patients with moderate to severe COVID-19 infections must be initiated.

Progress in Developing Inhibitors of SARS-CoV-2 3C-Like Protease

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The viral outbreak started in late 2019 and rapidly became a serious health threat to the global population. COVID-19 was declared a pandemic by the World Health Organization in March 2020. Several therapeutic options have been adopted to prevent the spread of the virus. Although vaccines have been developed, antivirals are still needed to combat the infection of this virus. SARS-CoV-2 is an enveloped virus, and its genome encodes polyproteins that can be processed into structural and nonstructural proteins. Maturation of viral proteins requires cleavages by proteases. Therefore, the main protease (3 chymotrypsin-like protease (3CLpro) or Mpro) encoded by the viral genome is an attractive drug target because it plays an important role in cleaving viral polyproteins into functional proteins. Inhibiting this enzyme is an efficient strategy to block viral replication. Structural studies provide valuable insight into the function of this protease and structural basis for rational inhibitor design. In this review, we describe structural studies on the main protease of SARS-CoV-2. The strategies applied in developing inhibitors of the main protease of SARS-CoV-2 and currently available protein inhibitors are summarized. Due to the availability of high-resolution structures, structure-guided drug design will play an important role in developing antivirals. The availability of high-resolution structures, potent peptidic inhibitors, and diverse compound scaffolds indicate the feasibility of developing potent protease inhibitors as antivirals for COVID-19.