Discover the Medication Potential of Algerian Medicinal Plants Against Sars-Cov-2 Main Protease (Mpro): Molecular Docking, Molecular Dynamic Simulation, and ADMET Analysis

At the end of 2019, the world faced a big challenge and crisis caused by the SARS-CoV-2 virus. It spreads rapidly and is contagious;no treatment has officially been found. Algeria has used medicinal plants native to the country to defend against this pandemic. The objective of this paper is based on a molecular docking study of the active compounds of five Algerian medicinal plants with their target Sars-2Cov-2 virus protease to assess their potential antiviral activity against COVID-19. Innovative software and computerized databases were introduced into the in-silico domain, mainly the Auto-Dock software version 1.5.6. Similar results were obtained for all ligands, with a better chemical affinity of − 5.600 kcal/mol for the protease target 6LU7 and − 5.700 kcal/mol for the protease target 6WTT, with an average of − 4.227 kcal/mol and − 4.221 kcal/mol, respectively. The protease targets 6LU7 and 6WTT. In the ADME-Tox study, the active compounds of Algerian medicinal plants also demonstrated an excellent pharmacokinetic and toxic profile. Best scores were noted for cedrol, camphor, and eucalyptol. A molecular dynamics simulation showed the stability of camphor-6LU7 and cedrol-6LU7 complexes, favoring the biological potential of white artemisia and cypress plants. Graphical : [Figure not available: see fulltext.] © 2023, This is a U.S. Government work and not under copyright protection in the US;foreign copyright protection may apply.

Inhibition of SARS-CoV2 Replication Regulated by NSP3 through Ayurveda Phytoconstituents of Indian Traditional Medicine

With Covid-19, a significant proportion of the population who are already vaccinated have tested positive. Therefore, there is a need for better medicines that act against the virus rigorously without causing any side effects. We aim to achieve the same through molecular docking and further simulations for bioactive phytochemicals of ayurvedic medicinal plants. The target for this study has been considered the NSP3 protein of the viral RNA that actively takes part in both replication and immune evasion pathways of the virus. Ligand libraries consisting of bioactive phytochemicals of aswasgandha and analogues of curcumin and piperine are curated. The libraries, along with the NSP3 protein moiety are docked onto two active sites. With the best-scored complexes further taken up for molecular dynamics simulation, the study resulted in favourable outcomes for three such ligands (compound ID 5469426, 69501714, ZINC000003874317). © 2023 Bharati Vidyapeeth, New Delhi.

Antimalarial phytochemicals as potential inhibitors of SARS-CoV-2 guanine N7-methyltransferase (nsp 14): an integrated computational approach.

The inhibition of capping enzymes such as guanine-N7-methyltransferase (GMT) is an attractive target for regulating viral replication, transcription, virulence, and pathogenesis. Thus, compounds that target the Severe Acute Respiratory Syndrome Corona Virus 2 GMT (S2GMT) will enhance drug development against COVID-19. In this study, an in-house library of 249 phytochemicals from African medicinal plants was screened using computational approaches including homology modeling, molecular docking, molecular dynamic simulations, binding free energy calculations based on molecular mechanics/Poisson-Boltzmann surface area (MMPBSA) and Absorption-Distribution-Metabolism-Excretion-Toxicity (ADMET) analysis for inhibitors of S2GMT. The top-ten ranked phytochemicals (TTRP) obtained from the docking analysis to S2GMT were further docked to SARS-COV N7-MTase. Among the TTRP, the top-four ranked phytocompounds (TFRP) viz: 3 alkaloids (Isocryptolepine, 10'-Hydroxyusambarensine and Isostrychnopentamine) and a flavonoid (Mulberrofuran F) interacted strongly with critical catalytic residues whose interference either reduce or completely abolish N7-MTase activity, indicating their potential as capping machinery disruptors. The interactions of TFRP with the catalytic residues of S2GMT were preserved in a 100 ns simulated dynamic environment, thereby, demonstrating high degree of structural stability. The MMPBSA binding free energy calculations corroborated the docking scores with biscryptolepine having the highest binding free energy to S2GMT. The TFRP showed favourable drug-likeness and ADMET properties over a wide range of molecular descriptors. Therefore, the TFRP can be further explored as potential S2GMT inhibitors in in vitro and in vivo experiments.Communicated by Ramaswamy H. Sarma.

Human indoleamine-2,3-dioxygenase 2 cofactor lability and low substrate affinity explained by homology modeling, molecular dynamics and molecular docking.

The human indoleamine-2,3-dioxygenase 2 (hIDO2) protein is growing of interest as it is increasingly implicated in multiple diseases (cancer, autoimmune diseases, COVID-19). However, it is only poorly reported in the literature. Its mode of action remains unknown because it does not seem to catalyze the reaction for which it is attributed: the degradation of the L-Tryptophan into N-formyl-kynurenine. This contrasts with its paralog, the human indoleamine-2,3-dioxygenase 1 (hIDO1), which has been extensively studied in the literature and for which several inhibitors are already in clinical trials. Yet, the recent failure of one of the most advanced hIDO1 inhibitors, the Epacadostat, could be caused by a still unknown interaction between hIDO1 and hIDO2. In order to better understand the mechanism of hIDO2, and in the absence of experimental structural data, a computational study mixing homology modeling, Molecular Dynamics, and molecular docking was conducted. The present article highlights an exacerbated lability of the cofactor as well as an inadequate positioning of the substrate in the active site of hIDO2, which might bring part of an answer to its lack of activity.Communicated by Ramaswamy H. Sarma.

N'-(3,4-dimethoxybenzylidene)-4-methylbenzenesulfonohydrazide derivatives: Synthesis, Quantum Chemical Method, in silico ADMET, Molecular docking and Molecular dynamic simulations

A new N'-(3,4-dimethoxybenzylidene)-4-methylbenzenesulfonohydrazide derivatives were prepared from a condensation reaction between 4-methylbenzenesulfonohydrazide and 3,4-dimethoxybenzaldehyde. The structure of DMSH was elucidated using various spectral techniques including FT-IR, 1H-NMR and 13C-NMR. The structure of DMSH bond parameters also confirmed by single crystal XRD analysis of related derivatives and optimized bond parameters are calculated by density functional theory (DFT) method at B3LYP/6-311G (d, p) level of theory. The optimized geometrical parameters obtained by DFT calculation are in good agreement with single crystal XRD data. The experimentally observed FT-IR bands were assigned to different normal modes of the molecule. The results show a good agreement with each other when these computed bond parameters are compared to XRD values of related compounds. The stability, chemical reactivity and charge transfer within the molecule was explained by frontier molecular orbital calculations. Atomic charges on the various atoms of DMSH obtained by Mulliken population analysis. Potential reactive sites of the DMSH compound have been identified by MEP which is mapped to the electron density surfaces. The reported molecule is used as a potential NLO material since it has a high μβ0 value. The theoretical UV-vis spectrum of the compound is used to study the visible absorption maxima (λ max). The molecular docking mechanism between DMSH ligand and COVID-19/6WCF and COVID-19/6Y84 receptors were studied to investigate the binding modes of this compound at the active sites. Molecular docking outcomes have shown that the DMSH molecule can be considered as a potential agent against COVID-19/6WCF-6Y84 receptors. In addition, the theoretical parameters of the bioactive molecules were calculated to establish their drug-likeness qualities and ADME/T analysis was carried out to examine the drug properties of the synthesized compound. Molecular dynamics simulation was performed for COVID-19 main protease (Mpro: 6WCF/6Y84) to understand the elements governing the inhibitory effect and the stability of interaction under dynamic conditions. The resultant complex structures were subjected to 100 ns simulation run to estimate their binding stabilities using GROMACS. The molecular dynamics simulation studies provided essential evidence that the systems were stable during the progression of 100 ns simulation run.

Bioinformatic Screening of Compounds from Iranian Lamiaceae Family Members against SARS-CoV-2 Spike Protein

Background: COVID-19 (coronavirus disease 2019) is still a major challenge worldwide. The disease is caused by binding the coronavirus to ACE2 receptors on lung cells, infecting the cells and triggering the onset of symptoms. The prevention of such a binding in which the virus is eventually unable to enter the cell could be a promising therapeutic approach.Methods: In this in silico study, 306 compounds of Lamiaceae family native in Iran (native Mints) were retrieved from several databases as 3D structures, and after that molecular docking and virtual screening, the compounds with inhibitory potential were selected in terms of free energy binding against the spike protein of the virus. The pharmacokinetic profile of selected compounds was evaluated, and by molecular dynamic simulation and MM/PBSA, four compounds were further assessed for binding affinities against the receptor-binding domain of the spike.Results: The results showed the Catechin gallate and Perovskone B from Stachys and Salvia genus generated a stronger binding affinity, and therefore could act as potential inhibitory compounds of RBD of the SARS-CoV-2 spike protein.Conclusion: This study revealed that some members of the Lamiaceae family could be employed to inhibit SARS-CoV-2 activity through interaction with spike protein and therefore could be used for further investigation in vitro and in vivo.

Association of SARS-CoV-2 Infection and Triple Negative Breast Cancer (TNBC) A Computational Illustrative Study

Background: Anticipating the correlation between SARS-CoV-2 infection and ‘triplenegative breast cancer (TNBC)' remains challenging. It has been reported that people currently diagnosed with cancer have a higher risk of severe complications if they are affected by the viral infection. Cancer treatments, including chemotherapy, targeted therapies, and immunotherapy, may weaken the immune system and possibly cause critical lung damage and breathing problems. Special attention must be paid to the ‘comorbidity condition' while estimating the risk of severe SARSCoV- 2 infection in TNBC patients. Hence the work aims to study the correlation between triplenegative breast cancer (TNBC) and SARS-CoV-2 using biomolecular networking.Methods: The genes associated with SARS CoV-2 have been collected from curated data in Bio- GRID. TNBC-related genes have been collected from expression profiles. Molecular networking has generated a Protein-Protein Interaction (PPI) network and a Protein-Drug Interaction (PDI) network. The network results were further evaluated through molecular docking studies followed by molecular dynamic simulation.Results: The genetic correlation of TNBC and SARS-Cov-2 has been observed from the combined PPI of their proteins. The drugs interacting with the disease's closely associated genes have been identified. The docking and simulation study showed that anti-TNBC and anti-viral drugs interact with these associated targets, suggesting their influence in inhibiting both the disease mutations.Conclusion: The study suggests a slight influence of SARS-CoV-2 viral infection on Triple Negative Breast Cancer. Few anticancer drugs such as Lapatinib, Docetaxel and Paclitaxel are found to inhibit both TNBC and viral mutations. The computational studies suggest these molecules are also useful for TNBC patients to control SARS-CoV-2 infection.

In silico identification of the potential natural inhibitors of SARS-CoV-2 Guanine-N7 methyltransferase

Background: The outbreak of the COVID-19 pandemic caused by the SARS-CoV-2 has triggered intense scientific research into the possible therapeutic strategies that can combat the ravaging disease. One of such strategies is the inhibition of an important enzyme that affects an important physiological process of the virus. The enzyme, Guanine-N7 Methyltransferase is responsible for the capping of the SARS-CoV-2 mRNA to conceal it from the host's cellular defense. The aim of the study: This study aims at computationally identifying the potential natural inhibitors of the SARS-CoV-2 Guanine-N7 methyltransferase binding at the active site (Pocket 41). Material(s) and Method(s): A library of small molecules was obtained from edible African plants and was molecularly docked against the SARS-CoV-2 Guanine-N7 methyltransferase (QHD43415_13. pdb) using the Pyrx software. Sinefungin, an approved antiviral drug had a binding score of -7.6 kcal/ mol with the target was chosen as a standard. Using the molecular descriptors of the compounds, virtual screening for oral availability was performed using the Pubchem and SWISSADME web tools. The online servers pkCSM and Molinspiration were used for further screening for the pharmacokinetic properties and bioactivity respectively. The molecular dynamic simulation and analyses of the Apo and Holo proteins were performed using the GROMACS software on the Galaxy webserver. Result(s): With a total RMSD of 77.78, average RMSD of 3.704, total regional (active site) RMSF of 30.61, average regional RMSF of 1.91, gyration of 6.9986, and B factor of 696.14, Crinamidine showed the greatest distortion of the target. Conclusion(s): All the lead compounds performed better than the standard while Crinamidine is predicted to show the greatest inhibitory activity. Further tests are required to further investigate the inhibitory activities of the lead compounds.Copyright © 2022 Belgorod State National Research University. All right reserved.

An immunoinformatics study: designing multivalent T-cell epitope vaccine against canine circovirus.

BACKGROUND: Canine circovirus is a deadly pathogen of dogs and causes vasculitis and hemorrhagic enteritis. It causes lethal gastroenteritis in pigs, fox, and dogs. Canine circovirus genome contains two main (and opposite) transcription units which encode two open reading frames (ORFs), a replicase-associated protein (Rep) and the capsid (Cap) protein. The replicase protein and capsid protein consist of 303 amino acids and 270 amino acids respectively. Several immuno-informatics methods such as epitope screening, molecular docking, and molecular-dynamics simulations were used to craft peptide-based vaccine construct against canine circovirus. RESULTS: The vaccine construct was designed by joining the selected epitopes with adjuvants by suitable linker. The cloning and expression of the vaccine construct was also performed using in silico methods. Screening of epitopes was conducted by NetMHC server that uses ANN (Artificial neural networking) algorithm. These methods are fast and cost-effective for screening epitopes that can interact with dog leukocyte antigens (DLA) and initiate an immune response. Overall, 5 epitopes, YQHLPPFRF, YIRAKWINW, ALYRRLTLI, HLQGFVNLK, and GTMNFVARR, were selected and used to design a vaccine construct. The molecular docking and molecular dynamics simulation studies show that these epitopes can bind with DLA molecules with stability. The codon adaptation and in silico cloning studies show that the vaccine can be expressed by Escherichia coli K12 strain. CONCLUSION: The results suggest that the vaccine construct can be useful in preventing the dogs from canine circovirus infections. However, the results need further validation by performing other in vitro and in vivo experiments.

Updates on drug designing approach through computational strategies: a review.

The drug discovery and development (DDD) process in pursuit of novel drug candidates is a challenging procedure requiring lots of time and resources. Therefore, computer-aided drug design (CADD) methodologies are used extensively to promote proficiency in drug development in a systematic and time-effective manner. The point in reference is SARS-CoV-2 which has emerged as a global pandemic. In the absence of any confirmed drug moiety to treat the infection, the science fraternity adopted hit and trial methods to come up with a lead drug compound. This article is an overview of the virtual methodologies, which assist in finding novel hits and help in the progression of drug development in a short period with a specific medicinal solution.

An extensive survey of technological applications in drug discovery and development, encompassing offline and online approaches, is presented in this review. The span of research issues that can be tackled using these advances is vast, opening new horizons for future innovations. The article is designed to incite further research investments into drug development procedures and bridge existing research voids by outlining multiple pharmaceutical products that resulted from employing systematic computational methodologies.

Modified coptisine derivatives as an inhibitor against pathogenic Rhizomucor miehei, Mycolicibacterium smegmatis (Black Fungus), Monkeypox, and Marburg virus by molecular docking and molecular dynamics simulation-based drug design approach.

During the second phase of SARS-CoV-2, an unknown fungal infection, identified as black fungus, was transmitted to numerous people among the hospitalized COVID-19 patients and increased the death rate. The black fungus is associated with the Mycolicibacterium smegmatis, Mucor lusitanicus, and Rhizomucor miehei microorganisms. At the same time, other pathogenic diseases, such as the Monkeypox virus and Marburg virus, impacted global health. Policymakers are concerned about these pathogens due to their severe pathogenic capabilities and rapid spread. However, no standard therapies are available to manage and treat those conditions. Since the coptisine has significant antimicrobial, antiviral, and antifungal properties; therefore, the current investigation has been designed by modifying coptisine to identify an effective drug molecule against Black fungus, Monkeypox, and Marburg virus. After designing the derivatives of coptisine, they have been optimized to get a stable molecular structure. These ligands were then subjected to molecular docking study against two vital proteins obtained from black fungal pathogens: Rhizomucor miehei (PDB ID: 4WTP) and Mycolicibacterium smegmatis (PDB ID 7D6X), and proteins found in Monkeypox virus (PDB ID: 4QWO) and Marburg virus (PDB ID 4OR8). Following molecular docking, other computational investigations, such as ADMET, QSAR, drug-likeness, quantum calculation and molecular dynamics, were also performed to determine their potentiality as antifungal and antiviral inhibitors. The docking score reported that they have strong affinities against Black fungus, Monkeypox virus, and Marburg virus. Then, the molecular dynamic simulation was conducted to determine their stability and durability in the physiological system with water at 100 ns, which documented that the mentioned drugs were stable over the simulated time. Thus, our in silico investigation provides a preliminary report that coptisine derivatives are safe and potentially effective against Black fungus, Monkeypox virus, and Marburg virus. Hence, coptisine derivatives may be a prospective candidate for developing drugs against Black fungus, Monkeypox and Marburg viruses.

Coating of favipiravir (FVP) on silver nanoparticles: First principle study

Silver nanoparticles, thanks to their antiviral and antibacterial properties, have great potential in a variety of applications, such as drug-delivery carriers. The coating properties of silver nanoparticles (size range of 1.6 nm) with a well-known drug, Favipirair, were investigated in this study using quantum mechanical and classical atomistic molecular dynamics simulation in order to use as the drug delivery to treat COVID-19 disease. The drug molecule's optimized structure, frequencies, charge distribution, and electrostatic potential maps were simulated using density functional theory (DFT) at the B3LYP/6–311++g(d,p) level of theory. The coating of AgNP with each of these drugs was then studied using molecular dynamics simulation. The interaction affinity obtained from MD results agrees with the DFT results on drug adsorption on the Ag(1 1 1) slab. © 2023

Anti-viral drug discovery against monkeypox and smallpox infection by natural curcumin derivatives: A Computational drug design approach.

Background: In the last couple of years, viral infections have been leading the globe, considered one of the most widespread and extremely damaging health problems and one of the leading causes of mortality in the modern period. Although several viral infections are discovered, such as SARS CoV-2, Langya Henipavirus, there have only been a limited number of discoveries of possible antiviral drug, and vaccine that have even received authorization for the protection of human health. Recently, another virial infection is infecting worldwide (Monkeypox, and Smallpox), which concerns pharmacists, biochemists, doctors, and healthcare providers about another epidemic. Also, currently no specific treatment is available against Monkeypox. This research gap encouraged us to develop a new molecule to fight against monkeypox and smallpox disease. So, firstly, fifty different curcumin derivatives were collected from natural sources, which are available in the PubChem database, to determine antiviral capabilities against Monkeypox and Smallpox. Material and method: Preliminarily, the molecular docking experiment of fifty different curcumin derivatives were conducted, and the majority of the substances produced the expected binding affinities. Then, twelve curcumin derivatives were picked up for further analysis based on the maximum docking score. After that, the density functional theory (DFT) was used to determine chemical characterizations such as the highest occupied molecular orbital (HOMO), lowest unoccupied molecular orbital (LUMO), softness, and hardness, etc. Results: The mentioned derivatives demonstrated docking scores greater than 6.80 kcal/mol, and the most significant binding affinity was at -8.90 kcal/mol, even though 12 molecules had higher binding scores (-8.00 kcal/mol to -8.9 kcal/mol), and better than the standard medications. The molecular dynamic simulation is described by root mean square deviation (RMSD) and root-mean-square fluctuation (RMSF), demonstrating that all the compounds might be stable in the physiological system. Conclusion: In conclusion, each derivative of curcumin has outstanding absorption, distribution, metabolism, excretion, and toxicity (ADMET) characteristics. Hence, we recommended the aforementioned curcumin derivatives as potential antiviral agents for the treatment of Monkeypox and Smallpox virus, and more in vivo investigations are warranted to substantiate our findings.

Molecular Modeling of Viral Type I Fusion Proteins: Inhibitors of Influenza Virus Hemagglutinin and the Spike Protein of Coronavirus.

The fusion of viral and cell membranes is one of the basic processes in the life cycles of viruses. A number of enveloped viruses confer fusion of the viral envelope and the cell membrane using surface viral fusion proteins. Their conformational rearrangements lead to the unification of lipid bilayers of cell membranes and viral envelopes and the formation of fusion pores through which the viral genome enters the cytoplasm of the cell. A deep understanding of all the stages of conformational transitions preceding the fusion of viral and cell membranes is necessary for the development of specific inhibitors of viral reproduction. This review systematizes knowledge about the results of molecular modeling aimed at finding and explaining the mechanisms of antiviral activity of entry inhibitors. The first section of this review describes types of viral fusion proteins and is followed by a comparison of the structural features of class I fusion proteins, namely influenza virus hemagglutinin and the S-protein of the human coronavirus.

Inhibitory mechanism of clioquinol and its derivatives at the exopeptidase site of human angiotensin-converting enzyme-2 and receptor binding domain of SARS-CoV-2 viral spike.

The outbreak of SARS-CoV-2 infections around the world has prompted scientists to explore different approaches to develop therapeutics against COVID-19. This study focused on investigating the mechanism of inhibition of clioquinol (CLQ) and its derivatives (7-bromo-5-chloro-8-hydroxyquinoline (CLBQ), 5, 7-Dichloro-8-hydroxyquinoline (CLCQ)) against the viral glycoprotein, and human angiotensin-converting enzyme-2 (hACE-2) involved in SARS-CoV-2 entry. The drugs were docked at the exopeptidase site of hACE-2 and receptor binding domain (RBD) sites of SARS-CoV-2 Sgp to calculate the binding affinity of the drugs. To understand and establish the inhibitory characteristics of the drugs, molecular dynamic (MD) simulation of the best fit docking complex performed. Evaluation of the binding energies of the drugs to hACE-2 after 100 ns MD simulations revealed CLQ to have the highest binding energy value of -40.4 kcal/mol close to MLN-7640 (-45.4 kcal/mol), and higher than the exhibited values for its derivatives: CLBQ (-34.5 kcal/mol) and CLCQ (-24.8 kcal/mol). This suggests that CLQ and CLBQ bind more strongly at the exopeptidase site than CLCQ. Nevertheless, the evaluation of binding affinity of the drugs to SARS-CoV-2 Sgp showed the drugs are weakly bound at the RBD site, with CLBQ, CLCQ, CLQ exhibiting relatively low energy values of -16.8 kcal/mol, -16.34 kcal/mol, -12.5 kcal/mol, respectively compared to the reference drug, Bisoxatin (BSX), with a value of -25.8 kcal/mol. The structural analysis further suggests decrease in systems stability and explain the mechanism of inhibition of clioquinol against SARS-CoV-2 as reported in previous in vitro study.Communicated by Ramaswamy H. Sarma.

Impact of Drug Repurposing on SARS-Cov-2 Main Protease

Abstract: The recent emergence of the severe acute respiratory disease caused by a novel coronavirus remains a concern posing many challenges to public health and the global economy. The resolved crystal structure of the main protease of SARS-CoV-2 or SCV2 (Mpro) has led to its identification as an attractive target for designing potent antiviral drugs. Herein, we provide a comparative molecular impact of hydroxychloroquine (HCQ), remdesivir, and β-D-N4-Hydroxycytidine (NHC) binding on SCV2 Mpro using various computational approaches like molecular docking and molecular dynamics (MD) simulation. Data analyses showed that HCQ, remdesivir, and NHC binding to SARS-CoV-2 Mpro decrease the protease loop capacity to fluctuate. These binding influences the drugs' optimum orientation in the conformational space of SCV2 Mpro and produce noticeable steric effects on the interactive residues. An increased hydrogen bond formation was observed in SCV2 Mpro–NHC complex with a decreased receptor residence time during NHC binding. The binding mode of remdesivir to SCV2 Mpro differs from other drugs having van der Waals interaction as the force stabilizing protein–remdesivir complex. Electrostatic interaction dominates in the SCV2 Mpro−HCQ and SCV2 Mpro–NHC. Residue Glu166 was highly involved in the stability of remdesivir and NHC binding at the SCV2 Mpro active site, while Asp187 provides stability for HCQ binding. © 2022, Pleiades Publishing, Ltd.

Design and Synthesis of Vitamin Drug Conjugate for its Probable Potential against SARS-COV-2 Infections

The novel corona virus infection had become a global epidemic due to its rapid spread. So, there is an urgent need to treat COVID-19 patients. The aim of this research was to hypothesize and examine vitamin drug conjugate as targeted moiety. The present scaffold may have potential role to fight against COVID-19 infection due to its antimicrobial, antioxidants and immunomodulatory activities. Here, we've highlighted the term Vitamin Drug Conjugate as possible therapy approach for SARS-COV-2 infection. As a result, we synthesize, characterized, and evaluated a Hydroxychloroquine — Folic Acid conjugate (HCQ-FA) by esterification mechanism to provide effective treatment against SARS-CoV-2 infection by enhancing therapeutic effect through synergistic mechanism, masking undesired side effects, and improving cellular internalization. By using prodrug, the efficacy and bioavailability of existing antiviral drugs could be improved. The structure of the conjugate was determined by spectroscopic data like IR, NMR, and mass spectra, which indicates that HCQ-FA conjugate formed by esteric conjugation. Molecular docking studies revealed that HCQ-FA conjugate shows good level of docking as well as binding interaction with main protease moiety. Molecular dynamic stimulation revealed that this conjugate shows good stability at the binding site of SARS main protease moiety and exhibits inhibitory activity against COVID-19 infection. © 2022 The Authors.

Study of potentiality of dexamethasone and its derivatives against Covid-19.

In December 2019, COVID-19 epidemic was reported in Wuhan, China, and subsequently the infection has spread all over the world and became pandemic. The death toll associated with the pandemic is increasing day by day in a high rate. Herein, an effort has been made to identify the potentiality of commercially available drugs and also their probable derivatives for creation of better opportunity to make more powerful drugs against coronavirus. This study involves the in-silico interactions of dexamethasone and its derivatives against the multiple proteins of SARS-CoV-2 with the help of various computational methods. Descriptor parameters revealed their non-toxic effect in the human body. Ultimately docking studies and molecular dynamic simulation on those target protein by dexamethasone and its derivatives showed a high binding energy. Dexamethasone showed -9.8 kcal/mol and its derivative D5 showed -12.1 kcal/mol binding energy. Those scores indicate that dexamethasone has more therapeutic effect on SARS CoV-2 than other currently used drugs. Derivatives give the clue for the synthesis of a novel drug to remove SARS CoV-2. Until then, dexamethasone will be used as a potential inhibitor of SARS CoV-2.Communicated by Ramaswamy H. Sarma.

Arjunetin as a promising drug candidate against SARS-CoV-2: molecular dynamics simulation studies.

Stem and bark of the tree Terminalia arjuna Wight & Arn. (Combretaceae) has been documented to exhibit therapeutic properties like cardiotonic, anticancer, antiviral, antibacterial, antifungal, hypercholesterolemia, hypolipidemic, and anti-coagulant. Our previous studies have shown that, ethanolic extract of T. arjuna bark exhibits radical scavenging anti-oxidant activity and also effectively inhibited catalase activity. In this study, oleanane triterpenoids type compounds viz., oleanolic acid, arjunolic acid, arjunolitin, arjunetin were isolated from ethanolic bark extract as bio-active compound and their structures were elucidated using 1H, 13C NMR, HR-ESIMS, IR. Of the various compounds, Arjunetin showed significant inhibition of catalase activity as compared to the other compounds. Based on the structural similarity between arjunetin and current antiviral drugs, we propose that arjunetin might exhibit antiviral activity. Molecular docking and molecular dynamics studies showed that arjunetin binds to the binds to key targets of SARS-CoV-2 namely, 3CLpro, PLpro, and RdRp) with a higher binding energy values (3CLpro, -8.4 kcal/mol; PLpro, -7.6 kcal/mol and RdRp, -8.1 kcal/mol) as compared with FDA approved protease inhibitor drugs to Lopinavir (3CLpro, -7.2 kcal/mole and PLpro -7.7 kcal/mole) and Remdesivir (RdRp -7.6 kcal/mole). To further investigate this, we performed 200-500 ns molecular dynamics simulation studies. The results transpired that the binding affinity of Arjunetin is higher than Remdesivir in the RNA binding cavity of RdRp. Based on structural similarity between arjunetin and Saikosaponin (a known antiviral agents) and based on our molecular docking and molecular dynamic simulation studies, we propose that arjunetin can be a promising drug candidate against Covid-19.Communicated by Ramaswamy H. Sarma.

Remdesivir analogs against SARS-CoV-2 RNA-dependent RNA polymerase.

The COVID-19 pandemic has already taken many lives but is still continuing its spread and exerting jeopardizing effects. This study is aimed to find the most potent ligands from 703 analogs of remdesivir against RNA-dependent RNA polymerase (RdRp) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus . RdRp is a major part of a multi-subunit transcription complex of the virus, which is essential for viral replication. In clinical trials, it has been found that remdesivir is effective to inhibit viral replication in Ebola and in primary human lung cell cultures; it effectively impedes replication of a broad-spectrum pre-pandemic bat coronaviruses and epidemic human coronaviruses. After virtual screening, 30 most potent ligands and remdesivir were modified with triphosphate. Quantum mechanics-based quantitative structure-activity relationship envisages the binding energy for ligands applying partial least square (PLS) regression. PLS regression remarkably predicts the binding energy of the effective ligands with an accuracy of 80% compared to the value attained from molecular docking. Two ligands (L4:58059550 and L28:126719083), which have more interactions with the target protein than the other ligands including standard remdesivir triphosphate, were selected for further analysis. Molecular dynamics simulation is done to assess the stability and dynamic nature of the drug-protein complex. Binding-free energy results via PRODIGY server and molecular mechanics/Poisson-Boltzmann surface area method depict that the potential and solvation energies play a crucial role. Considering all computational analysis, we recommend the best remdesivir analogs can be utilized for efficacy test through in vitro and in vivo trials against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.