Identification of potential inhibitors of three key enzymes of SARS-CoV2 using computational approach

Coronaviruses SARS-CoV, MERS-CoV, and SARS-CoV-2 helicase inhibitors: A systematic review of in vitro studies

Introduction

The recent outbreak of SARS-CoV-2 significantly increased the need to find inhibitors that target the essential enzymes for virus replication in the host cells. This systematic review was conducted to identify potential inhibitors of SARS-CoV, MERS-CoV, and SARS-CoV-2 helicases that have been tested by in vitro methods. The inhibition mechanisms of these compounds were discussed in this review, in addition to their cytotoxic and viral infection protection properties.

Methods

The databases PUBMED/MEDLINE, EMBASE, SCOPUS, and Web of Science were searched using different combinations of the keywords "helicase", "nsp13", "inhibitors", "coronaviridae", "coronaviruses", "virus replication", "replication", and "antagonists and inhibitors".

Results

By the end of this search, a total of 6854 articles had been identified. Thirty-one articles were included in this review. These studies reported the inhibitory effects of 309 compounds on SARS-CoV, MERS-CoV, and SARS-CoV-2 helicase activities measured by in vitro methods. Helicase inhibitors were categorized according to the type of coronavirus and the type of tested enzymatic activity, nature, approval, inhibition level, cytotoxicity, and viral infection protection effects. These inhibitors are classified according to the site of their interaction with the coronavirus helicases into four types: zinc-binding site inhibitors, nucleic acid binding site inhibitors, nucleotide-binding site inhibitors, and inhibitors with no clear interaction site.

Conclusion

Evidence from in vitro studies suggests that helicase inhibitors have a high potential as antiviral agents. Several helicase inhibitors tested in vitro showed good antiviral activities while maintaining moderate cytotoxicity. These inhibitors should be clinically investigated to determine their efficiency in treating different coronavirus infections, particularly COVID-19.

In silico study of novel niclosamide derivatives, SARS-CoV-2 nonstructural proteins catalytic residue-targeting small molecules drug candidates

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-mediated coronavirus disease 2019 (COVID-19) infection remains a global pandemic and health emergency with overwhelming social and economic impacts throughout the world. Therapeutics for COVID-19 are limited to only remdesivir; therefore, there is a need for combined, multidisciplinary efforts to develop new therapeutic molecules and explore the effectiveness of existing drugs against SARS-CoV-2. In the present study, we reported eight (SCOV-L-02, SCOV-L-09, SCOV-L-10, SCOV-L-11, SCOV-L-15, SCOV-L-18, SCOV-L-22, and SCOV-L-23) novel structurally related small-molecule derivatives of niclosamide (SCOV-L series) for their targeting potential against angiotensin-converting enzyme-2 (ACE2), type II transmembrane serine protease (TMPRSS2), and SARS-COV-2 nonstructural proteins (NSPs) including NSP5 (3CLpro), NSP3 (PLpro), and RdRp. Our correlation analysis suggested that ACE2 and TMPRSS2 modulate host immune response via regulation of immune-infiltrating cells at the site of tissue/organs entries. In addition, we identified some TMPRSS2 and ACE2 microRNAs target regulatory networks in SARS-CoV-2 infection and thus open up a new window for microRNAs-based therapy for the treatment of SARS-CoV-2 infection. Our in vitro study revealed that with the exception of SCOV-L-11 and SCOV-L-23 which were non-active, the SCOV-L series exhibited strict antiproliferative activities and non-cytotoxic effects against ACE2- and TMPRSS2-expressing cells. Our molecular docking for the analysis of receptor-ligand interactions revealed that SCOV-L series demonstrated high ligand binding efficacies (at higher levels than clinical drugs) against the ACE2, TMPRSS2, and SARS-COV-2 NSPs. SCOV-L-18, SCOV-L-15, and SCOV-L-09 were particularly found to exhibit strong binding affinities with three key SARS-CoV-2's proteins: 3CLpro, PLpro, and RdRp. These compounds bind to the several catalytic residues of the proteins, and satisfied the criteria of drug-like candidates, having good adsorption, distribution, metabolism, excretion, and toxicity (ADMET) pharmacokinetic profile. Altogether, the present study suggests the therapeutic potential of SCOV-L series for preventing and managing SARs-COV-2 infection and are currently under detailed investigation in our lab.

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.

Deep learning application detecting SARS-CoV-2 key enzymes inhibitors

The fast spread of the COVID-19 over the world pressured scientists to find its cures. Especially, with the disastrous results, it engendered from human life losses to long-term impacts on infected people's health and the huge financial losses. In addition to the massive efforts made by researchers and medicals on finding safe, smart, fast, and efficient methods to accurately make an early diagnosis of the COVID-19. Some researchers focused on finding drugs to treat the disease and its symptoms, others worked on creating effective vaccines, while several concentrated on finding inhibitors for the key enzymes of the virus, to reduce its spreading and reproduction inside the human body. These enzymes' inhibitors are usually found in aliments, plants, fungi, or even in some drugs. Since these inhibitors slow and halt the replication of the virus in the human body, they can help fight it at an early stage saving the patient from death risk. Moreover, if the human body's immune system gets rid of the virus at the early stage it can be spared from the disastrous sequels it may leave inside the patient's body. Our research aims to find aliments and plants that are rich in these inhibitors. In this paper, we developed a deep learning application that is trained with various aliments, plants, and drugs to detect if a component contains SARS-CoV-2 key inhibitor(s) intending to help them find more sources containing these inhibitors. The application is trained to identify various sources rich in thirteen coronavirus-2 key inhibitors. The sources are currently just aliments, plants, and seeds and the identification is done by their names.

Molecular dynamics simulation, 3D-pharmacophore and scaffold hopping analysis in the design of multi-target drugs to inhibit potential targets of COVID-19

SARS-CoV-2 has posed serious threat to the health and has inflicted huge costs in the world. Discovering potent compounds is a critical step to inhibit coronavirus. 3CL^pro and RdRp are the most conserved targets associated with COVID-19. In this study, three-dimensional pharmacophore modeling, scaffold hopping, molecular docking, structure-based virtual screening, QSAR-based ADMET predictions and molecular dynamics analysis were used to identify inhibitors for these targets. Binding free energies estimated by molecular docking for each ligand in different binding sites of RdRp were used to predict the active site. Previously reported active 3CL^pro and RdRp inhibitors were used to build a pharmacophore model to develop different scaffolds. Structure-based simulations and pharmacophore modeling based on Hip Hop algorithm converged in a state that suggest hydrogen bond acceptor and donor features have a critical role in the two binding sites. Further validations indicated that the best pharmacophore model has fairly good correlation values compared with approved inhibitors. Structure-based simulation results approved that GLu166 and Gln189 in 3CL^pro and Lys551 and Glu811 in RdRp, are critical residues for dual activities. Ten compounds were extracted from pharmacophore-based virtual screening in six databases. The results, gained by repurposing approach, suggest the effectiveness of these ten compounds with different scaffolds as possible inhibitors of the two targets. Some quinoline-based hybrid derivatives also were designed. QSAR descriptors plot predicted that the scaffolds have had accepted pharmacokinetic profiles. Multiple molecular dynamics simulations in 100 ns and MM/PBSA studies of some reference inhibitors and the novel compounds in complex with both targets demonstrated stable complexes and confirmed the interaction modes. Based on different computational methods, COVID-19 multi-target inhibitors are proposed. Communicated by Ramaswamy H. Sarma.

Therapeutic potential of compounds targeting SARS-CoV-2 helicase

The economical and societal impact of COVID-19 has made the development of vaccines and drugs to combat SARS-CoV-2 infection a priority. While the SARS-CoV-2 spike protein has been widely explored as a drug target, the SARS-CoV-2 helicase (nsp13) does not have any approved medication. The helicase shares 99.8% similarity with its SARS-CoV-1 homolog and was shown to be essential for viral replication. This review summarizes and builds on existing research on inhibitors of SARS-CoV-1 and SARS-CoV-2 helicases. Our analysis on the toxicity and specificity of these compounds, set the road going forward for the repurposing of existing drugs and the development of new SARS-CoV-2 helicase inhibitors.

Novel Drug Design for Treatment of COVID-19: A Systematic Review of Preclinical Studies

Background

Since the beginning of the novel coronavirus (SARS-CoV-2) disease outbreak, there has been an increasing interest in discovering potential therapeutic agents for this disease. In this regard, we conducted a systematic review through an overview of drug development (in silico, in vitro, and in vivo) for treating COVID-19.

Methods

A systematic search was carried out in major databases including PubMed, Web of Science, Scopus, EMBASE, and Google Scholar from December 2019 to March 2021. A combination of the following terms was used: coronavirus, COVID-19, SARS-CoV-2, drug design, drug development, In silico, In vitro, and In vivo. A narrative synthesis was performed as a qualitative method for the data synthesis of each outcome measure.

Results

A total of 2168 articles were identified through searching databases. Finally, 315 studies (266 in silico, 34 in vitro, and 15 in vivo) were included. In studies with in silico approach, 98 article study repurposed drug and 91 studies evaluated herbal medicine on COVID-19. Among 260 drugs repurposed by the computational method, the best results were observed with saquinavir (n = 9), ritonavir (n = 8), and lopinavir (n = 6). Main protease (n = 154) following spike glycoprotein (n = 62) and other nonstructural protein of virus (n = 45) was among the most studied targets. Doxycycline, chlorpromazine, azithromycin, heparin, bepridil, and glycyrrhizic acid showed both in silico and in vitro inhibitory effects against SARS-CoV-2.

Conclusion

The preclinical studies of novel drug design for COVID-19 focused on main protease and spike glycoprotein as targets for antiviral development. From evaluated structures, saquinavir, ritonavir, eucalyptus, Tinospora cordifolia, aloe, green tea, curcumin, pyrazole, and triazole derivatives in in silico studies and doxycycline, chlorpromazine, and heparin from in vitro and human monoclonal antibodies from in vivo studies showed promised results regarding efficacy. It seems that due to the nature of COVID-19 disease, finding some drugs with multitarget antiviral actions and anti-inflammatory potential is valuable and some herbal medicines have this potential.

Virtual screening of substances used in the treatment of SARS-CoV-2 infection and analysis of compounds with known action on structurally similar proteins from other viruses

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is considered the etiological agent of the disease that caused the COVID-19 pandemic, and for which there is currently no effective treatment. This pandemic has shown that the rapid identification of therapeutic compounds is critical (when a new virus with high transmissibility occurs) to prevent or reduce as much as possible the loss of human lives. To meet the urgent need for drugs, many strategies were applied for the discovery, respectively the identification of potential therapies / drugs for SARS-CoV-2. Molecular docking and virtual screening are two of the in silico tools/techniques that provided the identification of few SARS-CoV-2 inhibitors, removing ineffective or less effective drugs and thus preventing the loss of resources such as time and additional costs. The main target of this review is to provide a comprehensive overview of how in-silico tools have been used in the crisis management of anti-SARS-CoV-2 drugs, especially in virtual screening of substances used in the treatment of SARS-CoV-2 infection and analysis of compounds with known action on structurally similar proteins from other viruses; also, completions were added to the way in which these methods came to meet the requirements of biomedical research in the field. Moreover, the importance and impact of the topic approached for researchers was highlighted by conducting an extensive bibliometric analysis.

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.

Targeting SARS-CoV-2 non-structural protein 13 via helicase-inhibitor-repurposing and non-structural protein 16 through pharmacophore-based screening

Novel drug compound hunting was carried out for SARS-CoV-2 proteins with low mutation susceptibility. The probability of escape mutation and drug resistance is lower if conserved microbial proteins are targeted by therapeutic drugs. Mutation rate of all SARS-CoV-2 proteins were analyzed via multiple sequence alignment Non-Structural Protein 13 and Non-Structural Protein 16 were selected for the current study due to low mutation rate among viral strains and significant functionality. Cross-species mutation rate analysis for NSP13 and NSP16 showed these are well-conserved proteins among four coronaviral species. Viral helicase inhibitors, identified using literature-mining, were docked against NSP13. Pharmacophore-based screening of 11,375 natural compounds was conducted for NSP16. Stabilities of top compounds inside human body were confirmed via molecular dynamic simulation. ADME properties and LD₅₀ values of the helicase inhibitors and Ambinter natural compounds were analyzed. Compounds against NSP13 showed binding affinities between −10 and −5.9 kcal/mol whereby ivermectin and scutellarein showed highest binding energies of −10 and −9.9 kcal/mol. Docking of 18 hit compounds against NSP16 yielded binding affinities between −8.9 and −4.1 kcal/mol. Hamamelitannin and deacyltunicamycin were the top compounds with binding affinities of −8.9 kcal/mol and −8.4 kcal/mol. The top compounds showed stable ligand–protein interactions in molecular dynamics simulation. The analyses revealed two hit compounds against each targeted protein displaying stable behavior, high binding affinity and molecular interactions. Conversion of these compounds into drugs after in vitro experimentation can become better treatment options to elevate COVID management.

Systems pharmacology-based drug discovery and active mechanism of natural products for coronavirus pneumonia (COVID-19): An example using flavonoids

BACKGROUND

Recently, the value of natural products has been extensively considered because these resources can potentially be applied to prevent and treat coronavirus pneumonia 2019 (COVID-19). However, the discovery of nature drugs is problematic because of their complex composition and active mechanisms.

METHODS

This comprehensive study was performed on flavonoids, which are compounds with anti-inflammatory and antiviral effects, to show drug discovery and active mechanism from natural products in the treatment of COVID-19 via a systems pharmacological model. First, a chemical library of 255 potential flavonoids was constructed. Second, the pharmacodynamic basis and mechanism of action between flavonoids and COVID-19 were explored by constructing a compound-target and target-disease network, targets protein-protein interaction (PPI), MCODE analysis, gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment.

RESULTS

In total, 105 active flavonoid components were identified, of which 6 were major candidate compounds (quercetin, epigallocatechin-3-gallate (EGCG), luteolin, fisetin, wogonin, and licochalcone A). 152 associated targets were yielded based on network construction, and 7 family proteins (PTGS, GSK3β, ABC, NOS, EGFR, and IL) were included as central hub targets. Moreover, 528 GO items and 178 KEGG pathways were selected through enrichment of target functions. Lastly, molecular docking demonstrated good stability of the combination of selected flavonoids with 3CL Pro and ACEⅡ.

CONCLUSION

Natural flavonoids could enable resistance against COVID-19 by regulating inflammatory, antiviral, and immune responses, and repairing tissue injury. This study has scientific significance for the selective utilization of natural products, medicinal value enhancement of flavonoids, and drug screening for the treatment of COVID-19 induced by SARS-COV-2.

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.

Mutational landscape of SARS-CoV-2 genome in Turkey and impact of mutations on spike protein structure

The Coronavirus Disease 2019 (COVID-19) was declared a pandemic in March 2020 by the World Health Organization (WHO). As of May 25th, 2021 there were 2.059.941 SARS-COV2 genome sequences that have been submitted to the GISAID database, with numerous variations. Here, we aim to analyze the SARS-CoV-2 genome data submitted to the GISAID database from Turkey and to determine the variant and clade distributions by the end of May 2021, in accordance with their appearance timeline. We compared these findings to USA, Europe, and Asia data as well. We have also evaluated the effects of spike protein variations, detected in a group of genome sequences of 13 patients who applied to our clinic, by using 3D modeling algorithms. For this purpose, we analyzed 4607 SARS-CoV-2 genome sequences submitted by different lab centers from Turkey to the GISAID database between March 2020 and May 2021. Described mutations were also introduced in silico to the spike protein structure to analyze their isolated impacts on the protein structure. The most abundant clade was GR followed by G, GH, and GRY and we did not detect any V clade. The most common variant was B.1, followed by B.1.1, and the UK variant, B.1.1.7. Our results clearly show a concordance between the variant distributions, the number of cases, and the timelines of different variant accumulations in Turkey. The 3D simulations indicate an increase in the surface hydrophilicity of the reference spike protein and the detected mutations. There was less surface hydrophilicity increase in the Asp614Gly mutation, which exhibits a more compact conformation around the ACE-2 receptor binding domain region, rendering the structure in a “down” conformation. Our genomic findings can help to model vaccination programs and protein modeling may lead to different approaches for COVID-19 treatment strategies.

Efficacy of Ion-Channel Inhibitors Amantadine, Memantine and Rimantadine for the Treatment of SARS-CoV-2 In Vitro

We report the in vitro efficacy of ion-channel inhibitors amantadine, memantine and rimantadine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In VeroE6 cells, rimantadine was most potent followed by memantine and amantadine (50% effective concentrations: 36, 80 and 116 µM, respectively). Rimantadine also showed the highest selectivity index, followed by amantadine and memantine (17.3, 12.2 and 7.6, respectively). Similar results were observed in human hepatoma Huh7.5 and lung carcinoma A549-hACE2 cells. Inhibitors interacted in a similar antagonistic manner with remdesivir and had a similar barrier to viral escape. Rimantadine acted mainly at the viral post-entry level and partially at the viral entry level. Based on these results, rimantadine showed the most promise for treatment of SARS-CoV-2.

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.

Drug repurposing against coronavirus disease 2019 (COVID-19): A review

Since December 2019, severe acute respiratory syndrome coronavirus 2 has been found to be the culprit in the coronavirus disease 2019 (COVID-19), causing a global pandemic. Despite the existence of many vaccine programs, the number of confirmed cases and fatalities due to COVID-19 is still increasing. Furthermore, a number of variants have been reported. Because of the absence of approved anti-coronavirus drugs, the treatment and management of COVID-19 has become a global challenge. Under these circumstances, drug repurposing is an effective method to identify candidate drugs with a shorter cycle of clinical trials. Here, we summarize the current status of the application of drug repurposing in COVID-19, including drug repurposing based on virtual computer screening, network pharmacology, and bioactivity, which may be a beneficial COVID-19 treatment.

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Mechanism of SARS-CoV-2 infection and drug targets were reviewed.

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Drug repurposing against COVID-19 based on computer virtual screening, network pharmacology, bioactivity were summarized.

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The use of drug repurposing in COVID-19 was addressed.

Comparative assessment of RNA-dependent RNA polymerase (RdRp) inhibitors under clinical trials to control SARS-CoV2 using rigorous computational workflow

The devastating effect of SARS-CoV2 continues and the scientific community is pursuing to find the strategy to combat the spread of the virus. The approach is adapted to target this virus with medicine in combination with existing vaccines. For this, the medications that can specifically inhibit an enzyme essential for viral replication 'RNA-dependant-RNA polymerase (RdRp)' of SARS-CoV2 are being developed. RdRp is the enzyme commonly found in all RNA viruses but is absent in humans. There are in total 60 different RdRp inhibitors already under clinical trials for combating other RNA viruses, which are sought to even work for SARS-CoV2. These inhibitors are classified as nucleoside/nucleotide analogues and nonnucleoside/nonnucleotide analogues. In this study, all the known RdRp inhibitors were computationally targeted in the native form and their active form making the use of molecular docking, MM-GBSA and molecular dynamics (MD) simulations to find the top two of each nucleoside/nucleotide analogues and nonnucleoside/nonnucleotide analogues. The results showed ribavirin 5'-triphosphate and favipiravir ribonucleoside triphosphate (favipiravir-RTP) to be the top two nucleotide analogues while pimodivir and dihydropyrazolopyridinone analogue 8d were the top two nonnucleosides/non-nucleotide analogues.

Hepatitis C Virus Protease Inhibitors Show Differential Efficacy and Interactions with Remdesivir for Treatment of SARS-CoV-2 In Vitro

Antivirals targeting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could improve treatment of COVID-19. We evaluated the efficacy of clinically relevant hepatitis C virus (HCV) NS3 protease inhibitors (PIs) against SARS-CoV-2 and their interactions with remdesivir, the only direct-acting antiviral approved for COVID-19 treatment. HCV PIs showed differential potency in short-term treatment assays based on the detection of SARS-CoV-2 spike protein in Vero E6 cells. Linear PIs boceprevir, telaprevir, and narlaprevir had 50% effective concentrations (EC₅₀) of ∼40 μM. Among the macrocyclic PIs, simeprevir had the highest (EC₅₀, 15 μM) and glecaprevir the lowest (EC₅₀, >178 μM) potency, with paritaprevir, grazoprevir, voxilaprevir, vaniprevir, danoprevir, and deldeprevir in between. Acyclic PIs asunaprevir and faldaprevir had EC₅₀s of 72 and 23 μM, respectively. ACH-806, inhibiting the HCV NS4A protease cofactor, had an EC₅₀ of 46 μM. Similar and slightly increased PI potencies were found in human hepatoma Huh7.5 cells and human lung carcinoma A549-hACE2 cells, respectively. Selectivity indexes based on antiviral and cell viability assays were highest for linear PIs. In short-term treatments, combination of macrocyclic but not linear PIs with remdesivir showed synergism in Vero E6 and A549-hACE2 cells. Longer-term treatment of infected Vero E6 and A549-hACE2 cells with 1-fold EC₅₀ PI revealed minor differences in the barrier to SARS-CoV-2 escape. Viral suppression was achieved with 3- to 8-fold EC₅₀ boceprevir or 1-fold EC₅₀ simeprevir or grazoprevir, but not boceprevir, in combination with 0.4- to 0.8-fold EC₅₀ remdesivir; these concentrations did not lead to viral suppression in single treatments. This study could inform the development and application of protease inhibitors for optimized antiviral treatments of COVID-19.

Carbohydrate-Based NK1R Antagonists with Broad-Spectrum Anticancer Activity

NK1R antagonists, investigated for the treatment of several pathologies, have shown encouraging results in the treatment of several cancers. In the present study, we report on the synthesis of carbohydrate-based NK1R antagonists and their evaluation as anticancer agents against a wide range of cancer cells. All of the prepared compounds, derived from either d-galactose or l-arabinose, have shown high affinity and NK1R antagonistic activity with a broad-spectrum anticancer activity and an important selectivity, comparable to Cisplatin. This strategy has allowed us to identify the galactosyl derivative 14α, as an interesting hit exhibiting significant NK1R antagonist effect (kinact 0.209 ± 0.103 μM) and high binding affinity for NK1R (IC50 = 50.4 nM, Ki = 22.4 nM by measuring the displacement of [125I] SP from NK1R). Interestingly, this galactosyl derivative has shown marked selective cytotoxic activity against 12 different types of cancer cell lines.

Recent studies of nitrogen containing heterocyclic compounds as novel antiviral agents: A review

N-heterocycles are important, not only because of their abundance, but above all because of their chemical, biological and technical significance. They play an important role in biological investigation such as anticancer, antiinflammatory, antibacterial, antiviral, anti-tumor, antidiabetic, etc. In this study, we focused on examining synthesized some 5- or 6-ring N-heterocyclic compounds that showed the antiviral activity in last 5 years, and investigation of these compounds structure-activity relationship studies. This review will be useful to scientists in research fields of organic synthesis, medicinal chemistry, and pharmacology.

Computational Simulations Identified Marine-Derived Natural Bioactive Compounds as Replication Inhibitors of SARS-CoV-2

The rapid spread of COVID-19, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a worldwide health emergency. Unfortunately, to date, a very small number of remedies have been to be found effective against SARS-CoV-2 infection. Therefore, further research is required to achieve a lasting solution against this deadly disease. Repurposing available drugs and evaluating natural product inhibitors against target proteins of SARS-CoV-2 could be an effective approach to accelerate drug discovery and development. With this strategy in mind, we derived Marine Natural Products (MNP)-based drug-like small molecules and evaluated them against three major target proteins of the SARS-CoV-2 virus replication cycle. A drug-like database from MNP library was generated using Lipinski's rule of five and ADMET descriptors. A total of 2,033 compounds were obtained and were subsequently subjected to molecular docking with 3CLpro, PLpro, and RdRp. The docking analyses revealed that a total of 14 compounds displayed better docking scores than the reference compounds and have significant molecular interactions with the active site residues of SARS-CoV-2 virus targeted proteins. Furthermore, the stability of docking-derived complexes was analyzed using molecular dynamics simulations and binding free energy calculations. The analyses revealed two hit compounds against each targeted protein displaying stable behavior, binding affinity, and molecular interactions. Our investigation identified two hit compounds against each targeted proteins displaying stable behavior, higher binding affinity and key residual molecular interactions, with good in silico pharmacokinetic properties, therefore can be considered for further in vitro studies.

Potential Candidates against COVID-19 Targeting RNA-Dependent RNA Polymerase: A Comprehensive Review

Due to the extremely contagious nature of SARS-COV-2, it presents a significant threat to humans worldwide. A plethora of studies are going on all over the world to discover the drug to fight SARS-COV-2. One of the most promising targets is RNA-dependent RNA polymerase (RdRp), responsible for viral RNA replication in host cells. Since RdRp is a viral enzyme with no host cell homologs, it allows the development of selective SARS-COV-2 RdRp inhibitors. A variety of studies used in silico approaches for virtual screening, molecular docking, and repurposing of already existing drugs and phytochemicals against SARS-COV-2 RdRp. This review focuses on collating compounds possessing the potential to inhibit SARS-COV-2 RdRp based on in silico studies to give medicinal chemists food for thought so that the existing drugs can be repurposed for the control and treatment of ongoing COVID-19 pandemic after performing in vitro and in vivo experiments.

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.

Analysis of the SARS-CoV-2-host protein interaction network reveals new biology and drug candidates: focus on the spike surface glycoprotein and RNA polymerase

Introduction: The COVID-19 pandemic originated from the emergence of anovel coronavirus, SARS-CoV-2, which has been intensively studied since its discovery in order to generate the knowledge necessary to accelerate the development of vaccines and antivirals. Of note, many researchers believe there is great potential in systematically identifying host interactors of viral factors already targeted by existing drugs.Areas Covered: Herein, the authors discuss in detail the only available large-scale systematic study of the SARS-CoV-2-host protein-protein interaction network. More specifically, the authors review the literature on two key SARS-CoV-2 drug targets, the Spike surface glycoprotein, and the RNA polymerase. The authors also provide the reader with their expert opinion and future perspectives.Expert opinion: Interactions made by viral proteins with host factors reveal key functions that are likely usurped by the virus and, as aconsequence, points to known drugs that can be repurposed to fight viral infection and collateral damages that can exacerbate various disease conditions in COVID-19.

Virtual screening of peptides with high affinity for SARS-CoV-2 main protease

The current pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused more than 2,000,000 deaths worldwide. Currently, vaccine development and drug repurposing have been the main strategies to find a COVID-19 treatment. However, the development of new drugs could be the solution if the main strategies fail. Here, a virtual screening of pentapeptides was applied in order to identify peptides with high affinity to SARS-CoV-2 main protease (M^pro). Over 70,000 peptides were screened employing a genetic algorithm that uses a docking score as the fitness function. The algorithm was coupled with a RESTful API to persist data and avoid redundancy. The docking exhaustiveness was adapted to the number of peptides in each virtual screening step, where the higher the number of peptides, the lower the docking exhaustiveness. Two potential peptides were selected (HHYWH and HYWWT), which have higher affinity to M^pro than to human proteases. Albeit preliminary, the data presented here provide some basis for the rational design of peptide-based drugs to treat COVID-19.

Structural insights into SARS-CoV-2 infection and therapeutics development

The current COVID-19 pandemic is caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). By late October 2020, more than 43 million cases of infections, including over 1.15 million deaths, have been confirmed worldwide. This review focuses on our current understanding of SARS-CoV-2 from the perspective of the three-dimensional (3D) structures of SARS-CoV-2 viral proteins and their implications on therapeutics development against COVID-19.

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.

Exploring potential inhibitor of SARS-CoV2 replicase from FDA approved drugs using insilico drug discovery methods

Severe Acute Respiratory Syndrome Corona Virus-2 (SARS-CoV2) is responsible for fetal pneumonia called COVID19. SARS-CoV2 emerged in Wuhan, Hubei Province of China in December 2019. The COVID19 pandemic has now gripped the entire world with more than 70 million cases and over 1.5 million deaths so far. There no treatment option for COVID19 is in term of a drug or vaccine is currently available. Therefore drug repurposing may only provide a quick method for utilizing existing drugs for a therapeutic option. The virus genome contains several non-structural proteins (NSP) which serve as target for designing of antiviral agents. NSP9 of SARS-CoV2 encodes for a replicase enzyme which is essential for the virus replication in the host cell. In search of potent inhibitors, we have screened FDA approved drugs against NSP9 using in silico methods. Five drugs fluspirilene, troglitazone, alvesco, dihydroergotoxine and avodart were found to have highest affinities with the replicase. The molecular dynamics simulation (MDS) studies demonstrated strong drugs binding and stable NSP9-drugs complexes formation. The findings are also strongly supported by root-mean-square deviation, root-mean-square fluctuation, radius of gyration, and hydrogen bond analysis of the complexes. Principal component analysis showed the stable conformation of NSP9 upon drug binding. It could be inferred that these five drugs individually or in combinations may be used as potential inhibitors of NSP9 of SARS-CoV-2 after exploring their in vivo antiviral potential.Communicated by Ramaswamy H. Sarma.

Potential inhibitors interacting in Neuropilin-1 to develop an adjuvant drug against COVID-19, by molecular docking

The COVID-19 pandemic continues without specific treatment. In this study it is proposed compounds that can be developed as adjuvant / complementary drugs against COVID-19. Through a search for molecular docking, for the development of a new drug using pharmacological compounds targeting the b1 region in neuropilin-1 (NRP1), which is important for the interaction with the S1 region of the S-Protein of SARS-CoV-2, to slow down the infection process of this virus.

A molecular docking was performed using almost 500,000 compounds targeted to interact in the region between amino acids (Thr316, Asp320, Ser346, Thr349, and Tyr353) in NRP1 to determine compounds able to hinder the interaction with the S1 region in the S-Protein.

In this study, ten compounds are proposed as potential inhibitors between S1 region in the S-Protein of SARS-CoV-2 with the b1 region in NRP1, to develop a new adjuvant / complementary drug against COVID-19, and to hinder the interaction between SARS-CoV-2 and human cells, with a high probability to be safe in humans, validated by web servers for prediction of ADME and toxicity (PreADMET).

A comprehensive review on potential therapeutics interventions for COVID-19

COVID-19 is an infectious respiratory disease caused by SARS-CoV-2, a new beta coronavirus that emerged in Wuhan, China. Being primarily a respiratory disease, it is highly transmissible through both direct and indirect contacts. It displays a range of symptoms in different individuals and thus has been grouped into mild, moderate, and severe diseases. The virus utilizes spike proteins present on its surface to recognize ACE-2 receptors present on the host cells to enter the cell cytoplasm and replicate. The viral invasion of cells induces damage response, pyroptosis, infiltration of immune cells, expression of pro-inflammatory cytokines (cytokine storm), and activation of the adaptive immune system. Depending on viral load and host factors like age and underlying medical conditions, the immune responses mounted against SARS-CoV-2 may cause acute respiratory distress syndrome (ARDS), multiple organ failure, and death. In this review, we specify and justify both viral and host therapeutic targets that can be modulated to relieve the symptoms and treat the disease. Furthermore, we discuss vaccine development in the time of pandemic and the most promising vaccine candidates by far, according to WHO database. Finally, we discuss the conventional re-purposed drugs and potential alternative treatments as adjuvants.

Computational analysis of macrolides as SARS-CoV-2 main protease inhibitors: a pattern recognition study based on molecular topology and validated by molecular docking

Macrolides share the same chemo-mathematical pattern as SARS-CoV-2 protease inhibitors.

Computational selection of flavonoid compounds as inhibitors against SARS-CoV-2 main protease, RNA-dependent RNA polymerase and spike proteins: A molecular docking study

An outbreak of Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 has been recognized as a global health concern. Since, no specific antiviral drug is proven effective for treatment against COVID-19, identification of new therapeutics is an urgent need. In this study, flavonoid compounds were analyzed for its inhibitory potential against important protein targets of SARS-CoV-2 using computational approaches. Virtual docking was performed for screening of flavonoid compounds retrieved from PubChem against the main protease of SARS-CoV-2 using COVID-19 docking server. The cut off of dock score was set to >-9 kcal/mol and screened compounds were individually docked against main protease, RNA-dependent RNA polymerase, and spike proteins using AutoDock 4.1 software. Finally, lead flavonoid compounds were subjected to ADMET analysis. A total of 458 flavonoid compounds were virtually screened against main protease target and 36 compounds were selected based on the interaction energy value >-9 kcal/mol. Furthermore, these compounds were individually docked against protein targets and top 10 lead compounds were identified. Among the lead compounds, agathisflavone showed highest binding energy value of -8.4 kcal/mol against main protease, Albireodelphin showed highest dock score of -9.8 kcal/mol and -11.2 kcal/mol against RdRp, and spike proteins, respectively. Based on the high dock score and ADMET properties, top 5 lead molecules such as Albireodelphin, Apigenin 7-(6″-malonylglucoside), Cyanidin-3-(p-coumaroyl)-rutinoside-5-glucoside, Delphinidin 3-O-beta-D-glucoside 5-O-(6-coumaroyl-beta-D-glucoside) and (-)-Maackiain-3-O-glucosyl-6″-O-malonate were identified as potent inhibitors against main protease, RdRp, and spike protein targets of SARS-CoV-2. These all compounds are having non-carcinogenic and non-mutagenic properties. This study finding suggests that the screened compounds include Albireodelphin, Apigenin 7-(6″-malonylglucoside), Cyanidin-3-(p-coumaroyl)-rutinoside-5-glucoside, Delphinidin 3-O-beta-D-glucoside 5-O-(6-coumaroyl-beta-D-glucoside) and (-)-Maackiain-3-O-glucosyl-6″-O-malonate could be the potent inhibitors of SARS-CoV-2 targets.

Structural insights of key enzymes into therapeutic intervention against SARS-CoV-2

COVID-19 pandemic, caused by SARS-CoV-2, has drastically affected human health all over the world. After the emergence of the pandemic the major focus of efforts to attenuate the infection has been on repurposing the already approved drugs to treat COVID-19 adopting a fast-track strategy. However, to date a specific regimen to treat COVID-19 is not available. Over the last few months a substantial amount of data about the structures of various key proteins and their recognition partners involved in the SARS-CoV-2 pathogenesis has emerged. These studies have not only provided the molecular level descriptions ofthe viral pathogenesis but also laid the foundation for rational drug design and discovery. In this review, we have recapitulated the structural details of four key viral enzymes, RNA-dependent RNA polymerase, 3-chymotrypsin like protease, papain-like protease and helicase, and two host factors including angiotensin-converting enzyme 2 and transmembrane serine protease involved in the SARS-CoV-2 pathogenesis, and described the potential hotspots present on these structures which could be explored for therapeutic intervention. We have also discussed the significance of endoplasmic reticulum α-glucosidases as potential targets for anti-SARS-CoV-2 drug discovery.

Molecular mechanisms of the novel coronavirus SARS-CoV-2 and potential anti-COVID19 pharmacological targets since the outbreak of the pandemic

The novel coronavirus SARS-CoV-2 has emerged as a severe threat against public health and global economies. COVID-19, the disease caused by this virus, is highly contagious and has led to an ongoing pandemic. SARS-CoV-2 affects, mainly, the respiratory system, with most severe cases primarily showcasing acute respiratory distress syndrome. Currently, no targeted therapy exists, and since the number of infections and death toll keeps rising, it has become a necessity to study possible therapeutic targets. Antiviral drugs can target various stages of the viral infection, and in the case of SARS-CoV-2, both structural and non-structural proteins have been proposed as potential drug targets. This review focuses on the most researched SARS-CoV-2 proteins, their structure, function, and possible therapeutic approaches.

Evaluation of acridinedione analogs as potential SARS-CoV-2 main protease inhibitors and their comparison with repurposed anti-viral drugs

Background

The main protease (Mpro) of SARS-CoV-2 is involved in the processing of vital polypeptides required for viral genome replication and transcription and is one of the best-characterized targets to inhibit the progression of SARS-CoV-2 in infected individuals.

Methods

We screened a set of novel classes of acridinediones molecules to efficiently bind and inhibit the activity of the SARS-CoV-2 by targeting the Mpro. The repurposed FDA-approved antivirals were taken as standard molecules for this study. Long term (1.1 μs) MD simulations were performed to analyze the conformational space of the binding pocket of Mpro bound to the selected molecules.

Results

The molecules DSPD-2 and DSPD-6 showed more favorable MM-PBSA interaction energies and were seated more deeply inside the binding pocket of Mpro than the topmost antiviral drug (Saquinavir). Moreover, DSPD-5 also exhibited comparable binding energy to Saquinavir. The analysis of per residue contribution energy and SASA studies indicated that the molecules showed efficient binding by targeting the S1 subsite of the Mpro binding pocket.

Conclusion

The DSPD-2, DSPD-6, and DSPD-5 could be developed as potential inhibitors of SARS-CoV-2. Moreover, we suggest that targeting molecules to bind effectively to the S1 subsite could potentially increase the binding of molecules to the SARS-CoV-2 Mpro.

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A robust computational strategy applied to identify the potential lead for COVID-19.

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Repurposed FDA approved antiviral drugs were compared with a set of acridinedione analogs against Mpro of SARS-CoV-2.

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The acridinedione analogs have acceptable ADMET values and low toxicity profile.

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In-house synthesized acridinedione analogs showed good amount of interaction with Mpro of SARS-CoV-2.

Emerging Molecular Prospective of SARS-CoV-2: Feasible Nanotechnology Based Detection and Inhibition

The rapid dissemination of SARS-CoV-2 demonstrates how vulnerable it can make communities and is why it has attained the status of global pandemic. According to the estimation from Worldometer, the SARS-CoV-2 affected cases and deaths are exponentially increasing worldwide, marking the mortality rate as ∼3.8% with no probability of its cessation till now. Despite massive attempts and races among scientific communities in search of proper therapeutic options, the termination of this breakneck outbreak of COVID-19 has still not been made possible. Therefore, this review highlights the diverse molecular events induced by a viral infection, such as autophagy, unfolded protein response (UPR), and inflammasome, illustrating the intracellular cascades regulating viral replication inside the host cell. The SARS-CoV-2-mediated endoplasmic reticulum stress and apoptosis are also emphasized in the review. Additionally, host's immune response associated with SARS-CoV-2 infection, as well as the genetic and epigenetic changes, have been demonstrated, which altogether impart a better understanding of its epidemiology. Considering the drawbacks of available diagnostics and medications, herein we have presented the most sensitive nano-based biosensors for the rapid detection of viral components. Moreover, conceptualizing the viral-induced molecular changes inside its target cells, nano-based antiviral systems have also been proposed in this review.

COVID-19: molecular targets, drug repurposing and new avenues for drug discovery

Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly contagious infection that may break the healthcare system of several countries. Here, we aimed at presenting a critical view of ongoing drug repurposing efforts for COVID-19 as well as discussing opportunities for development of new treatments based on current knowledge of the mechanism of infection and potential targets within. Finally, we also discuss patent protection issues, cost effectiveness and scalability of synthetic routes for some of the most studied repurposing candidates since these are key aspects to meet global demand for COVID-19 treatment.

Structure-based drug designing towards the identification of potential anti-viral for COVID-19 by targeting endoribonuclease NSP15

The world is facing health and economic havoc due to the Corona Virus Disease-2019 (COVID-19) pandemic. Given the number of affected people and the mortality rate, the virus is undoubtedly a serious threat to humanity. By analogy with earlier reports about Severe Acute Respiratory Syndrome (SARS-CoV) and Middle East Respiratory Syndrome (MERS-CoV) - viruses, the novel Coronavirus' replication mechanism is likely well understood. The structure of an endoribonuclease (NSP15) of SARS-CoV-2 was reported recently. This enzyme is expected to play a crucial role in replication. In this work, attempts were made to identify inhibitors of this enzyme. To achieve the goal, high throughput in silico screening and molecular docking procedures were performed. From an Enamine database of a billion compounds, 3978 compounds with potential antiviral activity were selected for screening and induced fit docking that funneled down to eight compounds with good docking score and docking energy. Detailed analysis of non-covalent interactions at the active site and the apparent match of the molecule with the shape of the binding pocket were assessed. All the compounds show significant interactions for tight binding. Since all the compounds are synthetic with favorable drug-like properties, these may be considered for immediate optimization and downstream applications.