Interactions between carbon nanotubes and external structures of SARS-CoV-2 using molecular docking and molecular dynamics.

Molecular modeling techniques are used to describe the process of interaction between nanotubes and the main structures of the Covid-19 virus: the envelope protein, the main protease, and the Spike glycoprotein. Molecular docking studies show that the ligands have interaction characteristics capable of adsorbing the structures. Molecular dynamics simulations provide information on the mean squared deviation of atomic positions ​​between 0.5 and 3.0 Å. The Gibbs free energy model and solvent accessible surface area approaches are used. Through the results obtained through molecular dynamics simulations, it is noted that the zig-zag nanotube prefers to interact with E-pro, M-pro, and S-gly, respectively. Molecular couplings and free energy showed that the S-gly active site residues strongly interact with zigzag, chiral, and armchair nanotubes, in this order. The interactions demonstrated in this manuscript may predict some promising candidates for virus antagonists, which may be confirmed through experimental approaches.

Tuberculosis and HIV responses threatened by nCOVID-19: A situation prompting an in silico investigation of reported MbtA inhibitors for combined inhibition of SARS-CoV-2 and HIV-TB co-infection

The menace of infectious diseases has constantly been a reason of concern for humankind since time immemorial. As evident by the name, infectious diseases can infect a huge population within a short period, leading to an eruption of pandemics and epidemics. The present human era is fortunate enough to have a wide array of readily available drugs that help cure and prevent various diseases. Moreover, the scientific community has always responded to the needs of society through its drug discovery and development programs. The co-existence of multiple diseases calls forth the scientific community to design and develop drugs that could have a broad spectrum of activity. In this perspective, our goal was to investigate the potential of reported MbtA inhibitors (antitubercular molecules) in inhibiting HIV-1 RT and nCovid-19-RdRp and eventually leading to the identification of a multi-targeted ligand (triple co-infection inhibitor). In this study, the primary success was attained by capitalizing on the structure-based virtual screening drug discovery approach. Results were quite promising. Molecular docking results showed that GV17 interacted strongly with the active site residues of both the target proteins (HIV-1 RT and nCOVID-19-RdRp). Moreover, the docking score of GV17 was more than that of the internal ligands of both the target proteins, which indicates a firm binding. Molecular dynamics further validated these results as identical amino acid residues were observed in the protein's docked pose with the ligand. The detailed atomic interactions of ligand GV17 with the protein residues have been discussed. Overall, the protein–ligand complexes remained stable throughout the simulation, and the system's backbone fluctuations were modest. MM-GBSA analysis revealed free binding energy of − 72.30 ± 7.85 kcal/mol and − 65.40 ± 7.25 kcal/mol for 1RT2 and 7BV2, respectively. The more negative binding energy indicates a stronger affinity of GV17 with both the receptors. GV17 also gave satisfactory predictive in silico ADMET results. Overall, this computational study identified GV17 as a potential HIT molecule and findings can open up a new avenue to explore and develop inhibitors against nCOVID-19-HIV-TB triple-infections.

DFT, ADMET, molecular docking and molecular dynamics studies of pyridoxal

We report in silico studies of pyridoxal, which is of interest both as a precursor for further functionalization due to the presence of the aldehyde functionality, as well as a bioactive compound. So far, the crystal structure of pyridoxal has not been reported and, thus, we have optimized its structure both under water solvation and in gas phase using the DFT calculations. Under water solvation conditions the optimized structure of pyridoxal is 7.62 kcal/mol more favorable in comparison to that in gas phase. The DFT calculations were also applied to verify optical and electronic properties of the optimized structure of pyridoxal in water. The HOMO and LUMO were revealed to subtract a set of descriptors of the so-called global chemical reactivity as well as to probe pyridoxal as a potential corrosion inhibitor for some important metals used in implants. The title compound exhibits the best electron charge transfer from the molecule to the surface of Ni and Co. Some biological properties of pyridoxal were evaluated using the respective on-line tools. Molecular docking was additionally applied to study interaction of pyridoxal with some SARS-CoV-2 proteins as well as one of the monkeypox proteins. It was established that the title compound is active against all the applied proteins with the most efficient interaction with nonstructural protein 15 (endoribonuclease) and Omicron Spike protein of SARS-CoV-2. Pyridoxal was found to be also active against the studied monkeypox protein. Interaction of pyridoxal with nonstructural protein 15 (endoribonuclease) was further studied using molecular dynamics simulation.Copyright © 2023 Indian Chemical Society

Electronic, intermolecular, quantum computational investigations, molecular docking and simulation studies of the potent antiviral drug EIDD-2801

In this work, an analysis has been done to describe the molecular structure, spectroscopic, reduced density gradient, topological properties, atomic charges, Lipinski rule, Natural bond orbital analysis, docking and molecular dynamics simulation of the potent antiviral drug EIDD-2801 in the effective treatment against COVID-19. Intramolecular charge distribution is well understood by three schemes such as AIM, Mulliken and NBO analysis and non-covalent interactions have been understood through reduced density gradient. Topological properties, such as charge density and Laplacian of charge density along with the electron localization function, make it easy to obtain comprehensive information about bond strengths and critical points. The details obtained from the calculation of global reactivity descriptors and Lipinski rule are useful for understanding the nature of molecular reactivity and site selectivity. Electrostatic potentials help to identify potential electrophilic and nucleophilic sites for interaction between EIDD-2801 and target proteins. The molecular docking combined with molecular dynamic simulation studies enables us to get better picture about the ligand-protein interaction.Copyright © 2023 Indian Chemical Society

Computational Docking Study of the Phytochemical Constituent, Silybin (Silybum marianum) against SARS-CoV-2 Omicron Variant Spike Glycoprotein: An In-silico Approach

SARS-CoV-2 is continually evolving with the emergence of new variants with increased viral pathogenicity. The emergence of heavily mutated Omicron (B.1.1.529) with spike protein mutations are known to mediate its higher transmissibility and immune escape that has brought newer challenges for global public health to contain SARS-CoV-2 infection. One has to come up with a therapeutic strategy against the virus so as to effectively contain the infection and spread. Natural phytochemicals are being considered a significant source of bioactive compounds possessing an antiviral therapeutic potential. Being a promising anticancer and chemo-preventive agent, Silybin holds a significant potential to be used as a therapeutic. In the present study, molecular docking of Silybin with Omicron spike protein (7QNW) was carried out. Molecular docking results showed greater stability of Silybin in the active site of the Omicron spike protein with suitable binding mode of interactions. The study reveals that Silybin has the potential to block the host ACE2 receptor-viral spike protein binding;thereby inhibiting the viral entry to human cells. Therefore, Silybin may be further developed as a medication with the ability to effectively combat SARS-CoV-2 Omicron.Copyright © The Author(s) 2023.

Studying the Predictive Effects of Bacterial Carotenoids in the Treatment of Endometriosis Using Virtual Screening Methods

Background: Endometriosis is a chronic inflammatory disease defined as the presence of endometrial tissue outside the uterus, which causes pelvic pain and infertility. Cytokines appear to play vital roles in the development and progression of endometriosis and associated infertility. Tumor necrosis factoralpha (TNF-alpha) is a multifunctional pro-inflammatory cytokine, responsible for autoimmune and inflammatory disorders. TNF- alpha plays an important role in endometrial physiology as well as during early implantation. In addition, this cytokine has a considerable pathophysiological function in diseases such as menorrhagia, endometriosis, or infertility due to its regulatory impact on proliferation, differentiation, and angiogenesis in the human endometrium. In women with endometriosis, TNF-alpha levels increases in peritoneal fluid and serum significantly. In the present study, we focused on finding novel small molecules that can directly block TNFalpha- hTNFR1 (human TNF receptor 1) interaction. Method(s): In this regard, TNF-alpha inhibiting capacity of natural carotenoids was investigated in terms of blocking TNF-alpha-hTNFR1 interaction with the help of a combination of in silico approaches, based on virtual screening, molecular docking, and molecular dynamics (MD) simulation. Result(s): A total of 125 carotenoids were selected out of 1204 natural molecules, based on their pharmacokinetics properties, and they all met Lipinski's rule of five. Among them, sorgomol, strigol, and orobanchol had the most favorable DELTAG with the best pharmacokinetics properties and were selected for MD simulation studies, which explored the complex stability and the impact of ligands on protein conformation. It was shown that sorgomol formed the most hydrogen bonds, resulting in the highest binding energy with the lowest RMSD and RMSF. Conclusion(s): Our results showed that sorgomol was the most appropriate candidate as a TNF-alpha inhibitor. In conclusion, the present study could serve to expand possibilities to develop new therapeutic small molecules against TNF-alpha which plays an important role in the inflammation of endometriosis.

Landscape Analysis of Quercetin: A Potential Candidate Against SARS-CoV-2

Fruit, vegetables, and green tea contain quercetin (a flavonoid). Some of the diet's most signifi-cant sources of quercetin are apples, onions, tomatoes, broccoli, and green tea. Antioxidant, anticancer, anti-inflammatory, antimicrobial, antibacterial, and anti-viral effects have been studied of quercetin. The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus, ribonucleic acid (RNA) polymer-ase, and other essential viral life-cycle enzymes are all prevented from entering the body by quercetin. Despite extensive in vitro and in vivo investigations on the immune-modulating effects of quercetin and vitamin C treatment. 3-methyl-quercetin has been shown to bind to essential proteins necessary to convert minus-strand RNA into positive-strand RNAs, preventing the replication of viral RNA in the cytoplasm. Quercetin has been identified as a potential SARS-CoV-2 3C-like protease (3CLpro) suppressor in recent molecular docking studies and in silico assessment of herbal medicines. It has been demonstrated that quercetin increases the expression of heme oxygenase-1 through the nuclear factor erythroid-related factor 2 (Nrf2) signal network. Inhibition of heme oxygenase-1 may increase bilirubin synthesis, an endoge-nous antioxidant that defends cells. When human gingival fibroblast (HGF) cells were exposed to lipo-polysaccharide (LPS), inflammatory cytokine production was inhibited. The magnesium (Mg+2) cation complexation improves quercetin free radical scavenging capacity, preventing oxidant loss and cell death. The main objective of this paper is to provide an overview of the pharmacological effects of quercetin, its protective role against SARS-CoV-2 infection, and any potential molecular processes.Copyright © 2022 Bentham Science Publishers.

Application of Virtual Screening and Molecular Modeling Technologies to Identify Potential SARS-CoV-2 Main Protease Inhibitors

A virtual screening of the molecular library of biologically active compounds was carried out to identify potential inhibitors of SARS-CoV-2 main protease (Mpro) which plays an important role in the process of virus replication. Using molecular docking and molecular dynamics, the binding energy of these compounds to the catalytic site of the enzyme was assessed, resulting in six molecules that exhibited high chemical affinity for SARS-CoV-2 Mpro. This is evidenced by the low values of the binding free energy of the ligand/Mpro complexes comparable with those predicted for the potent non-covalent SARSCoV-2 Mpro inhibitor using the identical computational protocol. Based on the data obtained, it was concluded that the identified compounds have a good therapeutic potential for inhibiting the catalytic activity of the enzyme and form promising basic structures for the development of new effective drugs against COVID-19 © 2023, Mathematical Biology and Bioinformatics. All Rights Reserved.

Discovery of potential SARS-CoV 3CL protease inhibitors from approved antiviral drugs using: virtual screening, molecular docking, pharmacophore mapping evaluation and dynamics simulation.

The spread of corona-virus disease 2019 (COVID-19) has been faster than any other corona-viruses that have succeeded in crossing the animal-human barrier. This disease, caused by the severe acute respiratory syndrome corona-virus 2 (SARS-CoV-2/2019-nCoV) posing a serious threat to global public health and local economies. There are three responsible for this disease; SARS-CoV-2, SARS-CoV and MERS-CoV. Whereas our goal is to test the affinity for a new class of compounds obtained from a hybridization of Chloroquine, Amodiaquine and Mefloquine with three targets SARS-CoV-2, SARS-CoV and MERS-CoV, in order to find new compounds as new inhibitors against Covid-19. In this work, we first used: the molecular docking/dynamics methods and ADME properties to study interaction and affinity between eight new compounds against three targets involved in the Covid-19. The results of the docking simulations and dynamics revealed that inhibitor of the malaria (Ligand 87) has an affinity to interact with SARS-CoV-2, SARS-CoV and MERS-CoV targets and they can be good inhibitors for treatment of Covid-19. Moreover, they give best affinity compared to the Remdesivir and Chloroquine and other clinical tests. The Pharmacokinetics was justified by means of lipophilicity and high coefficient of skin permeability. The in silico evaluation of ADME and drug-likeness revealed that L87 has higher absorption in the intestines with good bioavailability. However, an additional in vitro and/or in vivo experimental study should make it possible to verify the theoretical results obtained in silico.Communicated by Ramaswamy H. Sarma.

Chemi-Informatic Approach to Investigate Putative Pharmacoactive Agents of Plant Origin to Eradicate COVID-19

Background: The scientific community has supported the medicinal flora of ancient as well as modern times in extracting chemicals, which holds therapeutic potential. In many previous studies, Amentoflavone discovered as an anti-viral agent, and it is present as a bioactive constituent in many plants of different families like Selaginellaceae, Euphorbiaceae, and Calophyllaceae. Withania somnifera (Ashwagandha) is already considered a significant anti-viral agent in traditional medicine, and it is the main source of Somniferine-A and Withanolide-B. Objective(s): In this study, phytochemicals such as withanolide-b, somniferine-a, stigmasterol, amentoflavone, and chavicine were analyzed to screen protein inhibitors, out of them;such proteins are involved in the internalization and interaction of SARS-CoV-2 with human cytological domains. This will help in developing a checkpoint for SARS-CoV-2 internalization. Method(s): Chemi-informatic tools like basic local alignment search tool (BLAST), AutoDock-vina, SwissADME, MDWeb, Molsoft, ProTox-II, and LigPlot were used to examine the action of pharmacoactive agents against SARS-CoV-2. The tools used in the study were based on the finest algorithms like artificial neural networking, machine learning, and artificial intelligence. Result(s): On the basis of binding energies less than equal to-8.5 kcal/mol, amentoflavone, stigmasterol, and somniferine-A were found to be the most effective against COVID-19 disease as these chemical agents exhibit hydrogen bond interactions and competitively inhibit major proteins (SARS-CoV-2 Spike, Human ACE-2 receptor, Human Furin protease, SARS-CoV-2 RNA binding protein) that are involved in its infection and pathogenesis. Simulation analysis provides more validity to the selection of the drug candidate Amentoflavone. ADMET properties were found to be in the feasible range for putative drug candidates. Conclusion(s): Computational analysis was successfully used for searching pharmacoactive phytochemicals like Amentoflavone, Somniferine-A, and Stigmasterol that can bring control over COVID-19 expansion. This new methodology was found to be efficient, as it reduces monetary expenditures and time consumption. Molecular wet-lab validations will provide approval for finalizing our selected drug model for controlling the COVID-19 pandemic.Copyright © 2022 Bentham Science Publishers.

STUDIES OF QUANTUM MECHANICS/MOLECULAR DOCKING ON ZANUBRUTINIB AS POTENTIAL REPURPOSED AGAINST COVID-19

Recently, Zanubrutinib, as a novel, selective covalent and potent inhibitor Bruton???s tyrosine kinase (BTK), has been used to treat COVID-19 patients. In this regard, the interaction of Zanubrutinib with Bruton???s tyrosine kinase (BTK) inhibitor studied. The docking molecular and ONIOM2 (B3LYP/6-311G: UFF) methods were conducted to investigate the binding properties of Zanubrutinib with Bruton???s tyrosine kinase (BTK) inhibitor. The active sites of the Bruton???s tyrosine kinase (BTK) inhibitor is evaluated by docking molecular and is used for ONIOM2 calculations. The binding between Zanubrutinib and the BTK receptor is strong because values of the free binding energy are negative. The hydrogen bonds are formed between Zanubrutinib and three residues of the active amino acids Asn484, Arg 525, and Asn 526 at 2.69, 3.15, and 2.75 ??, respectively, which create through the O atom, and the N-atom of Zanubrutinib. ONIOM2 calculation was displayed that the stability system in the solvent phase is higher than the gas-phase, which can occur due to the solvation of the species. Our results display the first mechanistic study of BTK inactivation by Zanubrutinib. This study can be helpful in the design of covalent drugs that target BTK and other similar targets.

Cuspareine as alkaloid against COVID-19 designed with ionic liquids: DFT and docking molecular approaches.

Cuspareine as an antiviral alkaloid can be used in the treatment of COVID-19. In this study, we introduced the ionic liquids (ILs) concluded cuspareinium as a cation with CH3COO-, CF3COO-, and PF6 as anions. The optimized geometry, thermodynamic parameters, and reactivity descriptors were calculated with density functional theory (DFT) approach and time-dependent density functional theory (TD-DFT) using B3LYP/6-311G. In addition, the UV and IR spectra of the introduced ILs were investigated. Based on DFT calculation, the designed IL CH3COO- can be to the most suitable anions due to most solubility in the water. DFT studies displayed that all the introduced ILs have more polarity than pristine cuspareine and CH3COO--cuspareine is the most polarity due to high dipole moment. Also, the thermo- chemical data of the designed ionic liquids revealed that PF6-cuspareine is distinguished to be stable. A molecular docking study of the designed ILs with 6 LU7 protease was performed to display interactions and binding energy. Results of molecular docking displayed that CH3COO- ion liquid has the highest binding energy (- 7.20 kcal/mol) and Ala7, and Lys 5 residues are involved in an interaction. DFT and molecular docking studies of cuspareine as alkaloid based on ionic liquids can be helpful to for more pharmaceutical and biological researches of cuspareine as an antiviral agent against COVID-19.

Flavonoids of Zinnia elegans: Chemical profile and, in vitro antioxidant and in silico anti-COVID-19 activities

Chemical profiles of total alcohol extract and various derived fractions of aerial parts of Zinnia elegans were studied. Accordingly, eight flavonoids were isolated from the ethyl acetate derived fraction based on the antioxidant assay-guided purification, using DPPH and phosphomolybdate complex assays. Eventually, the binding affinities and features of the eight isolated flavonoids were investigated using the molecular docking technique towards SARS-CoV-2 and human targets –namely main protease (Mpro), papain-like protease (PLpro), RNA-dependent RNA polymerase (RdRp), receptor-binding domain (RBD), helicase (NSP13), human angiotensin‐converting enzyme 2 (ACE2), and human neuropilin-1 (NRP1). Docking calculations unveiled the surpass binding affinity of glabrisoflavone with Mpro, PLpro, RdRp, RBD, NSP13, ACE2, and NRP1, with docking scores of −9.2, −7.4, −6.9, −6.9, −8.5, −9.0, and −7.6 kcal/mol, respectively. Binding mode analysis manifested the capability of glabrisoflavone to form several hydrogen bonds with the key amino acid residues inside the active sites of the targets. Besides, 25 ns molecular dynamics (MD) simulations combined with molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations were executed to inspect the binding affinity of glabrisoflavone and compared to an anti-HIV-1 protease inhibitor (darunavir). MM-GBSA calculations demonstrated greater glabrisoflavone affinity for the PLpro, RdRp, RBD and NRP1 over darunavir. Nevertheless, MM-GBSA calculations displayed equal or lower glabrisoflavone affinity against Mpro, NSP13 and ACE2 compared to darunavir. The current study obviously emphasizes the fitness of the glabrisoflavone as an auspicious clinical drug candidate for further development and future in vivo and in vitro evaluations towards viral targets and human targets.

An investigation on the molecular structure, interaction with metal clusters, anti-Covid-19 ability of 2-deoxy-D-glucose: DFT calculations, MD and docking simulations

Studies of the geometrical, vibration, absorption and physicochemical properties of 2-deoxy-D-glucose with and without metal clusters are reported using the DFT method. 2-Deoxy-D-glucose forms stable clusters with transition metal clusters of copper, silver and gold. Frontier molecular orbitals and molecular electrostatic potential of 2-deoxy-D-glucose and associated metal clusters (Cu6, Au6, Ag6, 2-DGCu6, 2-DGCu5Au, 2-DGCu5Ag, 2-DGAu6, 2-DGAu5Ag, 2-DGAu5Cu, 2 -DGAg6, 2-DGAg5Au, 2-DGAg5Cu) are examined with the B3LYP / LANL2DZ basis set. It is observed that the stability and chemical properties of 2-deoxy-D-glucose strongly depends on the cluster size. The molecular electrostatic potential maps were developed to provide information about the chemical reactivity of the molecules to explain intermolecular interactions. Then, to explore the ligand-protein recognition properties molecular docking and molecular dynamic (MD) simulation analyses have shown that the compound under consideration possesses potential activity as anti-cancer, anti-SARS-CoV-2, anti-SARS-CoV. Each of these analyzes contributes significantly to our understanding of the biological effects of the molecules outlined.

Identification of novel inhibitors of SARS-CoV-2 main protease (Mpro ) from Withania sp. by molecular docking and molecular dynamics simulation.

Since December 2019, coronavirus disease (COVID-19) has claimed the lives of millions of people across the globe. To date, no medicine is available for the responsible virus SARS-CoV-2. 3CLpro, that is, 3-chymotrypsin-like protease, the main protease (Mpro ), has an important role in cleaving pp1a and pp1ab polyproteins. This Mpro serves as an important target in drug designing against COVID-19. Herein, the study includes the investigation, screening, and identification of potent leads from (Withania sps.), against SARS-CoV-2, using virtual screening, molecular docking, and molecular dynamics (MD) simulations. Seventy-three natural compounds from this important medicinal plant were screened. The Binding affinity was used to identify the most probable target to inhibit the Mpro , compounds 27-hydroxywithanolide F (W32, -11.5 kcal/mol), withanolide A (W56, -11.4 kcal/mol), and withacoagulin H (W30, -11.1 kcal/mol) showed highest binding energy. Lipinski's rule, followed by drug-likability and likeness screening, resulted in 36 molecules. Further, MD simulation of 50 ns predicted withacoagulin H possessing strong binding affinity and hydrogen-bonding interactions with the active site. The binding free energy calculation showed the most negative energy of withacoagulin H (-63.463 KJ/mol) compared to other selected compounds. The study also compared the bonding energy of already reported repurposed and newly synthesized drugs. Further, absorption, distribution, metabolism, and excretion predictions were made to found a good balance of potency. Hence the following screened compounds from Withania sps. could serve as the potential leads for drug development against COVID-19.

An in silico analysis of Ibuprofen enantiomers in high concentrations of sodium chloride with SARS-CoV-2 main protease.

2020 will be remembered worldwide for the outbreak of Coronavirus disease (COVID-19), which quickly spread until it was declared as a global pandemic. The main protease (Mpro) of SARS-CoV-2, a key enzyme in coronavirus, represents an attractive pharmacological target for inhibition of SARS-CoV-2 replication. Here, we evaluated whether the anti-inflammatory drug Ibuprofen, may act as a potential SARS-CoV-2 Mpro inhibitor, using an in silico study. From molecular dynamics (MD) simulations, we also evaluated the influence of ionic strength on the affinity and stability of the Ibuprofen-Mpro complexes. The docking analysis shows that R(-)Ibuprofen and S(+)Ibuprofen isomers can interact with multiple key residues of the main protease, through hydrophobic interactions and hydrogen bonds, with favourable binding energies (-6.2 and -5.7 kcal/mol, respectively). MM-GBSA and MM-PBSA calculations confirm the affinity of these complexes, in terms of binding energies. It also demonstrates that the ionic strength modifies significantly their binding affinities. Different structural parameters calculated from the MD simulations (120 ns) reveal that these complexes are conformational stable in the different conditions analysed. In this context, the results suggest that the condition 2 (0.25 NaCl) bind more tightly the Ibuprofen to Mpro than the others conditions. From the frustration analysis, we could characterize two important regions (Cys44-Pro52 and Linker loop) of this protein involved in the interaction with Ibuprofen. In conclusion, our findings allow us to propose that racemic mixtures of the Ibuprofen enantiomers might be a potential treatment option against SARS-CoV-2 Mpro. However, further research is necessary to determinate their possible medicinal use.Communicated by Ramaswamy H. Sarma.

Structural Basis for Designing Multiepitope Vaccines Against COVID-19 Infection: In Silico Vaccine Design and Validation.

BACKGROUND: The novel coronavirus disease (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to the ongoing 2019-2020 pandemic. SARS-CoV-2 is a positive-sense single-stranded RNA coronavirus. Effective countermeasures against SARS-CoV-2 infection require the design and development of specific and effective vaccine candidates. OBJECTIVE: To address the urgent need for a SARS-CoV-2 vaccine, in the present study, we designed and validated one cytotoxic T lymphocyte (CTL) and one helper T lymphocyte (HTL) multi-epitope vaccine (MEV) against SARS-CoV-2 using various in silico methods. METHODS: Both designed MEVs are composed of CTL and HTL epitopes screened from 11 Open Reading Frame (ORF), structural and nonstructural proteins of the SARS-CoV-2 proteome. Both MEVs also carry potential B-cell linear and discontinuous epitopes as well as interferon gamma-inducing epitopes. To enhance the immune response of our vaccine design, truncated (residues 10-153) Onchocerca volvulus activation-associated secreted protein-1 was used as an adjuvant at the N termini of both MEVs. The tertiary models for both the designed MEVs were generated, refined, and further analyzed for stable molecular interaction with toll-like receptor 3. Codon-biased complementary DNA (cDNA) was generated for both MEVs and analyzed in silico for high level expression in a mammalian (human) host cell line. RESULTS: In the present study, we screened and shortlisted 38 CTL, 33 HTL, and 12 B cell epitopes from the 11 ORF protein sequences of the SARS-CoV-2 proteome. Moreover, the molecular interactions of the screened epitopes with their respective human leukocyte antigen allele binders and the transporter associated with antigen processing (TAP) complex were positively validated. The shortlisted screened epitopes were utilized to design two novel MEVs against SARS-CoV-2. Further molecular models of both MEVs were prepared, and their stable molecular interactions with toll-like receptor 3 were positively validated. The codon-optimized cDNAs of both MEVs were also positively analyzed for high levels of overexpression in a human cell line. CONCLUSIONS: The present study is highly significant in terms of the molecular design of prospective CTL and HTL vaccines against SARS-CoV-2 infection with potential to elicit cellular and humoral immune responses. The epitopes of the designed MEVs are predicted to cover the large human population worldwide (96.10%). Hence, both designed MEVs could be tried in vivo as potential vaccine candidates against SARS-CoV-2.