Investigation of antiviral substances in Covid 19 by Molecular Docking: In Silico Study

Aims: This paper aimed to investigate the antiviral drugs against Sars-Cov-2 main protease (MPro) using in silico methods. Material(s) and Method(s): A search was made for antiviral drugs in the PubChem database and antiviral drugs such as Bictegravir, Emtricitabine, Entecavir, Lamivudine, Tenofovir, Favipiravir, Hydroxychloroquine, Lopinavir, Oseltamavir, Remdevisir, Ribavirin, Ritonavir were included in our study. The protein structure of Sars-Cov-2 Mpro (PDB ID: 6LU7) was taken from the Protein Data Bank (www.rcsb. Org) system and included in our study. Molecular docking was performed using AutoDock/Vina, a computational docking program. Protein-ligand interactions were performed with the AutoDock Vina program. 3D visualizations were made with the Discovery Studio 2020 program. N3 inhibitor method was used for our validation. Result(s): In the present study, bictegravir, remdevisir and lopinavir compounds in the Sars-Cov-2 Mpro structure showed higher binding affinity compared to the antiviral compounds N3 inhibitor, according to our molecular insertion results. However, the favipiravir, emtricitabine and lamuvidune compounds were detected very low binding affinity. Other antiviral compounds were found close binding affinity with the N3 inhibitor. Conclusion(s): Bictegravir, remdevisir and lopinavir drugs showed very good results compared to the N3 inhibitor. Therefore, they could be inhibitory in the Sars Cov-2 Mpro target.Copyright © 2023 Oner E et al.

Identification of phytochemical compounds of Fagopyrum dibotrys and their targets by metabolomics, network pharmacology and molecular docking studies.

Acute lung injury (ALI) is a clinically severe lung illness with high incidence rate and mortality. Especially, coronavirus disease 2019 (COVID-19) poses a serious threat to world wide governmental fitness. It has distributed to almost from corner to corner of the universe, and the situation in the prevention and control of COVID-19 remains grave. Traditional Chinese medicine plays a vital role in the precaution and therapy of sicknesses. At present, there is a lack of drugs for treating these diseases, so it is necessary to develop drugs for treating COVID-19 related ALI. Fagopyrum dibotrys (D. Don) Hara is an annual plant of the Polygonaceae family and one of the long-history used traditional medicine in China. In recent years, its rhizomes (medicinal parts) have attracted the attention of scholars at home and abroad due to their significant anti-inflammatory, antibacterial and anticancer activities. It can work on SARS-COV-2 with numerous components, targets, and pathways, and has a certain effect on coronavirus disease 2019 (COVID-19) related acute lung injury (ALI). However, there are few systematic studies on its aerial parts (including stems and leaves) and its potential therapeutic mechanism has not been studied. The phytochemical constituents of rhizome of F. dibotrys were collected using TCMSP database. And metabolites of F. dibotrys' s aerial parts were detected by metabonomics. The phytochemical targets of F. dibotrys were predicted by the PharmMapper website tool. COVID-19 and ALI-related genes were retrieved from GeneCards. Cross targets and active phytochemicals of COVID-19 and ALI related genes in F. dibotrys were enriched by gene ontology (GO) and KEGG by metscape bioinformatics tools. The interplay network entre active phytochemicals and anti COVID-19 and ALI targets was established and broke down using Cytoscape software. Discovery Studio (version 2019) was used to perform molecular docking of crux active plant chemicals with anti COVID-19 and ALI targets. We identified 1136 chemicals from the aerial parts of F. dibotrys, among which 47 were active flavonoids and phenolic chemicals. A total of 61 chemicals were searched from the rhizome of F. dibotrys, and 15 of them were active chemicals. So there are 6 commonly key active chemicals at the aerial parts and the rhizome of F. dibotrys, 89 these phytochemicals's potential targets, and 211 COVID-19 and ALI related genes. GO enrichment bespoken that F. dibotrys might be involved in influencing gene targets contained numerous biological processes, for instance, negative regulation of megakaryocyte differentiation, regulation of DNA metabolic process, which could be put down to its anti COVID-19 associated ALI effects. KEGG pathway indicated that viral carcinogenesis, spliceosome, salmonella infection, coronavirus disease - COVID-19, legionellosis and human immunodeficiency virus 1 infection pathway are the primary pathways obsessed in the anti COVID-19 associated ALI effects of F. dibotrys. Molecular docking confirmed that the 6 critical active phytochemicals of F. dibotrys, such as luteolin, (+) -epicatechin, quercetin, isorhamnetin, (+) -catechin, and (-) -catechin gallate, can combine with kernel therapeutic targets NEDD8, SRPK1, DCUN1D1, and PARP1. In vitro activity experiments showed that the total antioxidant capacity of the aerial parts and rhizomes of F. dibotrys increased with the increase of concentration in a certain range. In addition, as a whole, the antioxidant capacity of the aerial part of F. dibotrys was stronger than that of the rhizome. Our research afford cues for farther exploration of the anti COVID-19 associated ALI chemical compositions and mechanisms of F. dibotrys and afford scientific foundation for progressing modern anti COVID-19 associated ALI drugs based on phytochemicals in F. dibotrys. We also fully developed the medicinal value of F. dibotrys' s aerial parts, which can effectively avoid the waste of resources. Meanwhile, our work provides a new strategy for integrating metabonomics, network pharmacology, and molecular docking techniques which was an efficient way for recognizing effective constituents and mechanisms valid to the pharmacologic actions of traditional Chinese medicine.

Selection of suitable protein structure from Protein Data Bank: An important step in Structure based Drug Design Studies.

Selection of a protein structure is an important step for the success of the drug discovery process using structure-based design. Selection of the right crystal structure is a critical step as multiple crystal structures are available for the same protein in the protein data bank (PDB). In this communication, we have discussed a systematic approach for selecting the right type of protein structure. Some case studies for the selection of crystal structures of TACE, 11ß-HSD1, DprE1 andSARS-CoV-2 Mpro enzymes have been discussed for the purpose of illustration.

D155Y substitution of SARS-CoV-2 ORF3a weakens binding with Caveolin-1.

The clinical manifestation of the recent pandemic COVID-19, caused by the novel SARS-CoV-2 virus, varies from mild to severe respiratory illness. Although environmental, demographic and co-morbidity factors have an impact on the severity of the disease, contribution of the mutations in each of the viral genes towards the degree of severity needs a deeper understanding for designing a better therapeutic approach against COVID-19. Open Reading Frame-3a (ORF3a) protein has been found to be mutated at several positions. In this work, we have studied the effect of one of the most frequently occurring mutants, D155Y of ORF3a protein, found in Indian COVID-19 patients. Using computational simulations we demonstrated that the substitution at 155th changed the amino acids involved in salt bridge formation, hydrogen-bond occupancy, interactome clusters, and the stability of the protein compared with the other substitutions found in Indian patients. Protein-protein docking using HADDOCK analysis revealed that substitution D155Y weakened the binding affinity of ORF3a with caveolin-1 compared with the other substitutions, suggesting its importance in the overall stability of ORF3a-caveolin-1 complex, which may modulate the virulence property of SARS-CoV-2.

Molecular Docking and the Pharmacokinetic Properties of the Anti-Viral Compounds Towards SARS-CoV- An In-silico Approach

The main aim of this study is to determine the bioactive compounds which have drug-like properties and has the potential to combat the spike-glycoprotein of SARS-CoV-2. The 6LXT protein of covid-19 was chosen from the protein data bank as a target protein. The compounds which are potentially capable to bind with the target were picked from the PubChem database and docked using the tool Autodock 4.2. Molecular docking of the molecules was done with the best conformations of the ligands and grid size was selected according to the hit compounds' interaction with the target protein. The ligand binding sites with the target molecules were predicted using MetaPocket 2.0. The docking Score of 50 compounds wascarried out and also toxicity studies were carried out. The compounds selected were calculated to identify the best conformations having drug-likeness properties. The top 10 compounds were chosen for the structure-activity relationship based on their binding interactions with the protein and ligand. The ligands then underwent the pharmacokinetic analysis followed by Lipinski's and all the results were finalized and categorized. ManzamineA, Imatinib, and basotinib were elected as the peak compounds with the binding energy -9.01kcal/mol, -8.71kcal/mol, and -8.01kcal/mol.

Repurposing of drugs for combined treatment of COVID-19 cytokine storm using machine learning.

Severe acute respiratory syndrome coronavirus 2 (SARS­CoV­2) induced cytokine storm is the major cause of COVID­19 related deaths. Patients have been treated with drugs that work by inhibiting a specific protein partly responsible for the cytokines production. This approach provided very limited success, since there are multiple proteins involved in the complex cell signaling disease mechanisms. We targeted five proteins: Angiotensin II receptor type 1 (AT1R), A disintegrin and metalloprotease 17 (ADAM17), Nuclear Factor­Kappa B (NF­κB), Janus kinase 1 (JAK1) and Signal Transducer and Activator of Transcription 3 (STAT3), which are involved in the SARS­CoV­2 induced cytokine storm pathway. We developed machine learning (ML) models for these five proteins, using known active inhibitors. After developing the model for each of these proteins, FDA-approved drugs were screened to find novel therapeutics for COVID­19. We identified twenty drugs that are active for four proteins with predicted scores greater than 0.8 and eight drugs active for all five proteins with predicted scores over 0.85. Mitomycin C is the most active drug across all five proteins with an average prediction score of 0.886. For further validation of these results, we used the PyRx software to conduct protein-ligand docking experiments and calculated the binding affinity. The docking results support findings by the ML model. This research study predicted that several drugs can target multiple proteins simultaneously in cytokine storm-related pathway. These may be useful drugs to treat patients because these therapies can fight cytokine storm caused by the virus at multiple points of inhibition, leading to synergistically effective treatments.

S-PDB: Analysis and Classification of SARS-CoV-2 Spike Protein Structures

This paper proposes a novel and efficient method, called S-PDB, for the analysis and classification of Spike (S) protein structures of SARS-CoV-2 and other viruses/organisms in the Protein Data Bank (PDB). The method first finds and identifies protein structures in PDB that are similar to a protein structure of interest (SARS-CoV-2 S) via a protein structure comparison tool. The amino acid (AA) sequences of identified protein structures, downloaded from PDB, and their aligned amino acids (AAA) and secondary structure elements (ASSE), that are stored in three separate datasets, are then used for the reliable detection/classification of SARS-CoV-2 S protein structures. Three classifiers are used and their performance is compared by using six evaluation metrics. Obtained results show that two classifiers for text data (Multinomial Naive Bayes and Stochastic Gradient Descent) performed better and achieved high accuracy on the dataset that contains AAA of protein structures compared to the datasets for AA and ASSE, respectively. © 2022 IEEE.

Electron microscopy holdings of the Protein Data Bank: the impact of the resolution revolution, new validation tools, and implications for the future.

As a discipline, structural biology has been transformed by the three-dimensional electron microscopy (3DEM) "Resolution Revolution" made possible by convergence of robust cryo-preservation of vitrified biological materials, sample handling systems, and measurement stages operating a liquid nitrogen temperature, improvements in electron optics that preserve phase information at the atomic level, direct electron detectors (DEDs), high-speed computing with graphics processing units, and rapid advances in data acquisition and processing software. 3DEM structure information (atomic coordinates and related metadata) are archived in the open-access Protein Data Bank (PDB), which currently holds more than 11,000 3DEM structures of proteins and nucleic acids, and their complexes with one another and small-molecule ligands (~ 6% of the archive). Underlying experimental data (3DEM density maps and related metadata) are stored in the Electron Microscopy Data Bank (EMDB), which currently holds more than 21,000 3DEM density maps. After describing the history of the PDB and the Worldwide Protein Data Bank (wwPDB) partnership, which jointly manages both the PDB and EMDB archives, this review examines the origins of the resolution revolution and analyzes its impact on structural biology viewed through the lens of PDB holdings. Six areas of focus exemplifying the impact of 3DEM across the biosciences are discussed in detail (icosahedral viruses, ribosomes, integral membrane proteins, SARS-CoV-2 spike proteins, cryogenic electron tomography, and integrative structure determination combining 3DEM with complementary biophysical measurement techniques), followed by a review of 3DEM structure validation by the wwPDB that underscores the importance of community engagement.

S-PDB: Analysis and Classification of SARS-CoV-2 Spike Protein Structures

This paper proposes a novel and efficient method, called S-PDB, for the analysis and classification of Spike (S) protein structures of SARS-CoV-2 and other viruses/organisms in the Protein Data Bank (PDB). The method first finds and identifies protein structures in PDB that are similar to a protein structure of interest (SARS-CoV-2 S) via a protein structure comparison tool. The amino acid (AA) sequences of identified protein structures, downloaded from PDB, and their aligned amino acids (AAA) and secondary structure elements (ASSE), that are stored in three separate datasets, are then used for the reliable detection/classification of SARS-CoV-2 S protein structures. Three classifiers are used and their performance is compared by using six evaluation metrics. Obtained results show that two classifiers for text data (Multinomial Naive Bayes and Stochastic Gradient Descent) performed better and achieved high accuracy on the dataset that contains AAA of protein structures compared to the datasets for AA and ASSE, respectively. © 2022 IEEE.

Functional dynamics of SARS-CoV-2 3C-like protease as a member of clan PA.

SARS-CoV-2 3C-like protease (3CLpro), a potential therapeutic target for COVID-19, consists of a chymotrypsin fold and a C-terminal α-helical domain (domain III), the latter of which mediates dimerization required for catalytic activation. To gain further understanding of the functional dynamics of SARS-CoV-2 3CLpro, this review extends the scope to the comparative study of many crystal structures of proteases having the chymotrypsin fold (clan PA of the MEROPS database). First, the close correspondence between the zymogen-enzyme transformation in chymotrypsin and the allosteric dimerization activation in SARS-CoV-2 3CLpro is illustrated. Then, it is shown that the 3C-like proteases of family Coronaviridae (the protease family C30), which are closely related to SARS-CoV-2 3CLpro, have the same homodimeric structure and common activation mechanism via domain III mediated dimerization. The survey extended to order Nidovirales reveals that all 3C-like proteases belonging to Nidovirales have domain III, but with various chain lengths, and 3CLpro of family Mesoniviridae (family C107) has the same homodimeric structure as that of C30, even though they have no sequence similarity. As a reference, monomeric 3C proteases belonging to the more distant family Picornaviridae (family C3) lacking domain III are compared with C30, and it is shown that the 3C proteases are rigid enough to maintain their structures in the active state. Supplementary Information: The online version contains supplementary material available at 10.1007/s12551-022-01020-x.

Molecular docking studies of phytochemicals from Terminalia chebula for identification of potential multi-target inhibitors of SARS-CoV-2 proteins.

Background: The COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has emerged as a global pandemic claiming more than 6 million lives worldwide as of 16 March 2022. Till date, no medicine has been developed which is proved to have 100% efficiency in combating against this deadly disease. We focussed on ayurvedic medicines to identify drug-like candidates for treatment and management of COVID-19. Among all ayurvedic medicines, we were interested in Terminalia chebula (T. chebula), as it is known to have antibacterial, antifungal, antiviral, antioxidant and anti-inflammatory properties. Objectives: In this study, we evaluated potential inhibitory effects of phytochemicals from T. chebula against eight structural and functional proteins of SARS-CoV-2. Material and methods: We performed blind molecular docking studies using fifteen phytochemicals from T. chebula against the proteins of SARS-CoV-2. The three-dimensional proteins structures were analysed and potential drug-binding sites were identified. The drug-likeness properties of the ligands were assessed as well. Results: Analysing the docking results by comparing Atomic Contact Energy (ACE) and intermolecular interactions along with assessment of ADME/T properties identified 1,3,6-Trigalloyl glucose (-332.14 ± 55.74 kcal/mol), Beta-Sitosterol (-324.75 ± 36.98 kcal/mol) and Daucosterol (-335.67 ± 104.79 kcal/mol) as most promising candidates which exhibit significantly high inhibition efficiency against all eight protein targets. Conclusions: We believe that our study has the potential to help the scientific communities to develop multi-target drugs from T. chebula to combat against the deadly pathogen of COVID-19, with the support of extensive wet lab analysis.

Plant-Based Natural Bioactive Compounds 2,4-Ditert-Butylphenolas: A Potential Candidates Against SARS-Cov-2019.

The novel coronavirus 2019 is spreading around the world and causing serious concern. However, there is limited information about novel coronavirus that hinders the design of effective drug. Bioactive compounds are rich source of chemo preventive ingredients. In our present research focuses on identifying and recognizing bioactive chemicals in Lantana camara, by evaluating their potential toward new coronaviruses and confirming the findings using molecular docking, ADMET, network analysis and dynamics investigations.. The spike protein receptor binding domain were docked with 25 identified compounds and 2,4-Ditertbutyl-phenol (-6.3kcal/mol) shows highest docking score, its interactions enhances the increase in binding and helps to identify the biological activity. The ADME/toxicity result shows that all the tested compounds can serve as inhibitors of the enzymes CYP1A2 and CYP2D6. In addition, Molecular dynamics simulations studies with reference inhibitors were carried out to test the stability. This study identifies the possible active molecules against the receptor binding domain of spike protein, which can be further exploited for the treatment of novel coronavirus 2019. The results of the toxicity risk for phytocompounds and their active derivatives showed a moderate to good drug score.

Unsymmetrical aromatic disulfides as SARS-CoV-2 Mpro inhibitors: Molecular docking, molecular dynamics, and ADME scoring investigations.

COVID-19 pandemic caused by very severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) agent is an ongoing major global health concern. The disease has caused more than 452 million affected cases and more than 6 million death worldwide. Hence, there is an urgency to search for possible medications and drug treatments. There are no approved drugs available to treat COVID-19 yet, although several vaccine candidates are already available and some of them are listed for emergency use by the world health organization (WHO). Identifying a potential drug candidate may make a significant contribution to control the expansion of COVID-19. The in vitro biological activity of asymmetric disulfides against coronavirus through the inhibition of SARS-CoV-2 main protease (Mpro) protein was reported. Due to the lack of convincing evidence those asymmetric disulfides have favorable pharmacological properties for the clinical treatment of Coronavirus, in silico evaluation should be performed to assess the potential of these compounds to inhibit the SARS-CoV-2 Mpro. In this context, we report herein the molecular docking for a series of 40 unsymmetrical aromatic disulfides as SARS-CoV-2 Mpro inhibitor. The optimal binding features of disulfides within the binding pocket of SARS-CoV-2 endoribonuclease protein (Protein Data Bank [PDB]: 6LU7) was described. Studied compounds were ranked for potential effectiveness, and those have shown high molecular docking scores were proposed as novel drug candidates against SARS-CoV-2. Moreover, the outcomes of drug similarity and ADME (Absorption, Distribution, Metabolism, and Excretion) analyses have may have the effectiveness of acting as medicines, and would be of interest as promising starting point for designing compounds against SARS-CoV-2. Finally, the stability of these three compounds in the complex with Mpro was validated through molecular dynamics (MD) simulation, in which they displayed stable trajectory and molecular properties with a consistent interaction profile.

MOLECULAR DOCKING OF CYMBOPOGON NARDUS (L.) RENDLE COMPOUNDS AS A PROTEASE INHIBITOR OF SARS-COV-2

Objective: The study aimed to obtain active compounds from Cymbopogon nardus as candidates for protease inhibitor of SARS-CoV-2 virus by assessing the ligand-binding affinity in the binding pocket of SARS-CoV-2 main protease protein. Methods: Molecular docking as a protease inhibitor of SARS-CoV-2 was carried using computational software Molegro Virtual Docker (MVD);computational docking was carried using receptors with Protein Data Bank (PDB) were also used to compare the affinity strength of the test compounds against the protease receptor (code of 5R81). The compounds of Cymbopogon nardus were optimized before docking using ChemDraw and minimized energy using Chem3D. Visualization of the docking result by using Discovery Studio and pkCSM was utilized to perform a pharmacokinetic and toxicological analysis (ADMET). Results: The result showed geranyl acetate, elemol, citronellal, and citronellyl acetate compounds from Cymbopogon nardus has a rerank score more negative than native ligand from 5R81 receptor as a protease inhibitor of SARS-CoV-2. Conclusion: Cymbopogon nardus can be developed as an antivirus with the mechanism of a protease inhibitor of SARS-CoV-2 candidates after further experimental tests.

Macroalgae Bioactive Compounds for the Potential Antiviral of SARS-CoV-2: An In Silico Study

Coronavirus disease (COVID-19), which was due to novel coronavirus was detected in December 2019 in Wuhan, China for the first time and spread rapidly became a global pandemic. This study aimed to predict the potential of macroalgae compounds as SARS-CoV-2 antiviral by inhibiting of ACE2 receptor through in silico approach. Twenty-seven macroalgae compounds were obtained from PubChem (NCBI, USA), while target protein ACE2 receptor was collected from Protein Data Bank (PDB). Then the initial screening study drug-likeness conducted by Lipinski rule of five web server and prediction of bioactive probability carried out by PASS (Prediction of activity spectra for biologically active substances) Online web server. After those compounds were approved by Lipinski's rule of five and PASS online prediction web server, the blind docking simulation was performed using PyRx 0.8 software to show binding energy value. Molecular interaction analysis was done using BIOVIA Discovery Studio 2016 v16.1.0 and PyMOL v2.4.1 software. There are six macroalgae compounds approved by Lipinski's rule of five and PASS Online Analysis. The result is that macroalgae compound siphonaxanthin among 27 macroalgae compound showed strong binding energy to bind ACE2 receptor with -8.8 kcal/mol. This study also used the SARS-CoV-2 drugs as positive control: remdesivir, molnupiravir, baricitinib, lopinavir, oseltamivir, and favipiravir. The result shows that siphonaxanthin has lowest binding energy than the common SARS-CoV-2 drug. Macroalgae compounds are predicted to have potential as SARS-CoV-2 antiviral. Thus, extension studies need to investigate by in vitro and in vivo analysis for confirmation the siphonaxanthin's inhibitory activity in combat SARS-CoV-2.

Development of Metal Complexes for Treatment of Coronaviruses.

Coronavirus disease (SARS-CoV-2) is a global epidemic. This pandemic, which has been linked to high rates of death, has forced some countries throughout the world to implement complete lockdowns in order to contain the spread of infection. Because of the advent of new coronavirus variants, it is critical to find effective treatments and vaccines to prevent the virus's rapid spread over the world. In this regard, metal complexes have attained immense interest as antibody modifiers and antiviral therapies, and they have a lot of promise towards SARS-CoV-2 and their suggested mechanisms of action are discussed, i.e., a new series of metal complexes' medicinal vital role in treatment of specific proteins or SARS-CoV-2 are described. The structures of the obtained metal complexes were fully elucidated by different analytical and spectroscopic techniques also. Molecular docking and pharmacophore studies presented that most of complexes studied influenced good binding affinity to the main protease SARS-CoV-2, which also was attained as from the RCSB pdb (Protein Data Bank) data PDB ID: 6 W41, to expect the action of metal complexes in contradiction of COVID-19. Experimental research is required to determine the pharmacokinetics of most of the complexes analyzed for the treatment of SARS-CoV-2-related disease. Finally, the toxicity of a metal-containing inorganic complex will thus be discussed by its capability to transfer metals which may bind with targeted site.

Inactivation of SARS-CoV-2 by charged particles for Future Vaccine Production Applications: A Monte Carlo study.

The world is still suffering from the SARS-CoV-2 pandemic, and the number of infected people is still growing in many countries in 2022. Although great strides have been made to produce effective vaccines, efforts in this field should be accelerated, particularly due to the emergence of new variants. Using inactivated viruses is a conventional method of vaccine production. High levels of ionizing radiation can effectively inactivate viruses. Recently, studies on SARS-CoV-2 irradiation using low-LET radiations (e.g., gamma rays) have been performed. However, there are insufficient studies on the impact of charged particles on the inactivation of this virus. In this study, a realistic structure of SARS-CoV-2 is simulated by using Geant4 Monte Carlo toolkit, and the effect of electrons, protons, alphas, C-12, and Fe-56 ions on the inactivation of SARS-CoV-2 is investigated. The simulation results indicated that densely ionizing (high-LET) particles have the advantage of minimum number of damaged spike proteins per single RNA break. The RNA breaks induced by hydroxyl radicals produced in the surrounding water medium were significant only for electron beam radiation. Hence, indirect RNA breaks induced by densely ionizing particles is negligible. From a simulation standpoint, alpha particles (with energies up to 30 MeV) as well as C-12 ions (with energies up to 80 MeV/n), and Fe-56 ions (with any energy) can be introduced as particles of choice for effective SARS-CoV-2 inactivation.

Hydroxychloroquine (HCQ) Exhibits Better Binding to the Main Protease (Mpro) Compared to Spike Protein (S protein) of SARS-CoV-2: An In-silico Analysis

Background: Despite various efforts in preventing and treating SARS-CoV-2 infec-tions;transmission and mortality have been increasing at alarming rates globally. Since its first oc-currence in Wuhan, China, in December 2019, the number of cases and deaths due to SARS-CoV--2 infection continues to increase across 220 countries. Currently, there are about 228 million cases and 4.6 million deaths recorded globally. Although several vaccines/drugs have been reported to prevent or treat SARS-CoV-2, their efficacy to protect against emerging variants and duration of protection are not fully known. Hence, more emphasis is given to repurpose the existing pharmacological agents to manage the infected individuals. One such agent is hydroxychloroquine (HCQ), which is a more soluble derivative of antimalarial drug chloroquine. HCQ has been tested in clinical trials to mitigate SARS-CoV-2 infection-induced complications while reducing the time to clinical recovery (TTCR). However, several concerns and questions about the utility and efficacy of HCQ for treating SARS-CoV-2 infected individuals still persist. Identifying key proteins regulated by HCQ is likely to provide vital clues required to address these concerns. Objective: The objective of this study is to identify the ability of HCQ for binding to the most wide-ly studied molecular targets of SARS-CoV-2 viz., spike glycoprotein (S protein), and main pro-tease (Mpro, also referred as chymotrypsin like protease) using molecular docking approaches and correlate the results with reported mechanisms of actions of HCQ. Methods: X-ray crystallographic structures of spike glycoprotein and main protease of SARS-CoV-2 were retrieved from Research Collaboratory for Structural Bioinformatics (RCSB) Protein Data Bank (PDB). The structure of Hydroxychloroquine was retrieved from the PubChem compound database. The binding interactions of the HCQ with target proteins were predicted using C-Docker algorithm, and visualized using Discovery studio visualizer. Results: Data from molecular docking studies showed very strong binding of HCQ to the main pro-tease compared to spike glycoprotein. Conclusion: The antiviral activity of HCQ is attributed to its ability to bind to the main protease compared to surface glycoprotein. Therefore, future studies should focus more on developing a combination agent/strategy for targeting surface glycoprotein and main protease together.

The Potential Effect of Nigericin from Streptomyces hygroscopicus subsp. Hygroscopicus Against the Syndemic of Malaria and COVID-19 through Molecular Docking Perspective

Background: Malaria is a constantly challenging problem, notably in the Coronavirus Disease-19 (COVID-19) pandemic. The syndemic condition, malaria-COVID-19 co-infections, had been reported. Our previous study successfully revealed several compounds from Streptomyces hygroscopicus subsp. Hygroscopicus, including nigericin that has both antimalarial and antiviral effects. In malaria infection, Plasmodium falciparum Chloroquine Resistance Transporter (PfCRT) is the potential target for eliminating Plasmodium. Meanwhile, for SARS-CoV-2 infection, MPro is an essential protein for SARS-CoV-2 survival. This research aims to examine the potential effect of nigericin towards Plasmodium and SARS-CoV-2 by assessing its molecular interaction with PfCRT and MPro through molecular docking study. Methods: The protein target PfCRT and MPro were obtained from Protein Data Bank. Nigericin and the control ligand (chloroquine and N3) were obtained from PubChem. The pharmacokinetic analysis was done using SwissADME. Specific molecular docking was conducted using PyRx 0.9 and was visualized using LigPlot and PyMOL. Results: Nigericin has a large molecular weight, leading to the non-fulfillment of the Lipinski rule for oral administration. Through molecular docking study, the binding affinity of the Nigericin-PfCRT complex was -8.1 kcal/mol, and Nigericin-MPro was -8.6 kcal/mol. These binding affinities were stronger than the control ligand. The interaction between Nigericin-PfCRT and Nigericin-MPro share a similar pocket-site and amino acid residues as the control ligands. Conclusion: Nigericin has potential antimalarial and anti-coronavirus effects through molecular docking perspective by assessing the binding affinity and similarity of amino acid residues compared to control. Administration of systemic route can be an option in giving nigericin.

Antiviral activity of Matricaria chamomilla in the treatment of COVID-19: Molecular Docking study

Introduction: SARS-CoV-2 infection is a lethal disease caused by a Novel strain of coronaviruses. Although vaccinations of healthy people and meticulous treatment of infected people are the main global health concerns, some plant species have therapeutic effects against viral infections. Matricaria chamomilla is one of the most famous medicinal plants used to manage flu or flu-like symptoms due to its antiviral bioactivity. M. chamomilla belongs to a large group of medicinal herbs used by Persian scholars such as Avicenna and Rhazes to treat respiratory diseases. It has more than 120 chemical constituents, including terpenoids, flavonoids, and some components with potential medicinal activity. In this study, the inhibitory effect of 2 major flavonoid components of M. chamomilla, apigenin and luteolin, was studies for the main protease protein of SARS-CoV-2. Methods: Molecular docking studies were performed using an in-house batch script (DOCKFACE) of Auto Dock 4.2. The 3D structures of the selected flavonoids were retrieved from PubChem, and each ligand was optimized with MM+ then AM1 minimization method using HyperChem 8. The 3D crystal structure of the main protease protein of SARS-CoV-2 (PDB ID: 6LU7) was obtained from the Protein Data Bank (http://www.rcsb.org./pdb). Results: Apigenin and luteolin exhibited good docking scores against 6LU7 receptor, -7.86 and -7.24, respectively, with a combination of hydrogen bonding, van der Waals, and other hydrophobic interactions in the docked complexes. Besides, the estimated inhibition constants, Ki, showed that luteolin exhibited a better inhibitory effect than apigenin. Conclusions: Based on these results, the authors proposed that M. chamomilla can be considered as a valuable resource recommended for preventing SARS-CoV-2 invasion into the human body. Keywords: COVID-19, M. chamomilla, Persian medicine, Molecular Docking, Herbal medicine