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1.
Methods Mol Biol ; 2673: 371-399, 2023.
Article in English | MEDLINE | ID: covidwho-20241347

ABSTRACT

Structure-based vaccine design (SBVD) is an important technique in computational vaccine design that uses structural information on a targeted protein to design novel vaccine candidates. This increasing ability to rapidly model structural information on proteins and antibodies has provided the scientific community with many new vaccine targets and novel opportunities for future vaccine discovery. This chapter provides a comprehensive overview of the status of in silico SBVD and discusses the current challenges and limitations. Key strategies in the field of SBVD are exemplified by a case study on design of COVID-19 vaccines targeting SARS-CoV-2 spike protein.


Subject(s)
COVID-19 , Humans , COVID-19/prevention & control , SARS-CoV-2 , COVID-19 Vaccines , Spike Glycoprotein, Coronavirus , Molecular Docking Simulation
2.
Front Cell Infect Microbiol ; 13: 1134802, 2023.
Article in English | MEDLINE | ID: covidwho-20239332

ABSTRACT

There has been progressive improvement in immunoinformatics approaches for epitope-based peptide design. Computational-based immune-informatics approaches were applied to identify the epitopes of SARS-CoV-2 to develop vaccines. The accessibility of the SARS-CoV-2 protein surface was analyzed, and hexa-peptide sequences (KTPKYK) were observed having a maximum score of 8.254, located between amino acids 97 and 102, whereas the FSVLAC at amino acids 112 to 117 showed the lowest score of 0.114. The surface flexibility of the target protein ranged from 0.864 to 1.099 having amino acid ranges of 159 to 165 and 118 to 124, respectively, harboring the FCYMHHM and YNGSPSG hepta-peptide sequences. The surface flexibility was predicted, and a 0.864 score was observed from amino acids 159 to 165 with the hepta-peptide (FCYMHHM) sequence. Moreover, the highest score of 1.099 was observed between amino acids 118 and 124 against YNGSPSG. B-cell epitopes and cytotoxic T-lymphocyte (CTL) epitopes were also identified against SARS-CoV-2. In molecular docking analyses, -0.54 to -26.21 kcal/mol global energy was observed against the selected CTL epitopes, exhibiting binding solid energies of -3.33 to -26.36 kcal/mol. Based on optimization, eight epitopes (SEDMLNPNY, GSVGFNIDY, LLEDEFTPF, DYDCVSFCY, GTDLEGNFY, QTFSVLACY, TVNVLAWLY, and TANPKTPKY) showed reliable findings. The study calculated the associated HLA alleles with MHC-I and MHC-II and found that MHC-I epitopes had higher population coverage (0.9019% and 0.5639%) than MHC-II epitopes, which ranged from 58.49% to 34.71% in Italy and China, respectively. The CTL epitopes were docked with antigenic sites and analyzed with MHC-I HLA protein. In addition, virtual screening was conducted using the ZINC database library, which contained 3,447 compounds. The 10 top-ranked scrutinized molecules (ZINC222731806, ZINC077293241, ZINC014880001, ZINC003830427, ZINC030731133, ZINC003932831, ZINC003816514, ZINC004245650, ZINC000057255, and ZINC011592639) exhibited the least binding energy (-8.8 to -7.5 kcal/mol). The molecular dynamics (MD) and immune simulation data suggest that these epitopes could be used to design an effective SARS-CoV-2 vaccine in the form of a peptide-based vaccine. Our identified CTL epitopes have the potential to inhibit SARS-CoV-2 replication.


Subject(s)
COVID-19 , Viral Vaccines , Humans , SARS-CoV-2 , COVID-19 Vaccines , COVID-19/prevention & control , Molecular Docking Simulation , Epitopes, T-Lymphocyte , Epitopes, B-Lymphocyte , Peptides , Vaccines, Subunit , Amino Acids , Endopeptidases , Computational Biology
3.
Sci Rep ; 13(1): 8743, 2023 05 30.
Article in English | MEDLINE | ID: covidwho-20239097

ABSTRACT

Spike glycoprotein of SARS-CoV-2 variants plays a critical role in infection and transmission through its interaction with human angiotensin converting enzyme 2 (hACE2) receptors. Prior findings using molecular docking and biomolecular studies reported varied findings on the difference in the interactions among the spike variants with the hACE2 receptors. Hence, it is a prerequisite to understand these interactions in a more precise manner. To this end, firstly, we performed ELISA with trimeric spike glycoproteins of SARS-CoV-2 variants including Wuhan Hu-1(Wild), Delta, C.1.2 and Omicron. Further, to study the interactions in a more specific manner by mimicking the natural infection, we developed hACE2 receptors expressing HEK-293T cell line, evaluated their binding efficiencies and competitive binding of spike variants with D614G spike pseudotyped virus. In line with the existing findings, we observed that Omicron had higher binding efficiency compared to Delta in both ELISA and Cellular models. Intriguingly, we found that cellular models could differentiate the subtle differences between the closely related C.1.2 and Delta in their binding to hACE2 receptors. Our study using the cellular model provides a precise method to evaluate the binding interactions between spike sub-lineages to hACE2 receptors.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , Angiotensin-Converting Enzyme 2/genetics , Molecular Docking Simulation , Spike Glycoprotein, Coronavirus/genetics , Protein Binding
4.
Int J Mol Sci ; 23(24)2022 Dec 16.
Article in English | MEDLINE | ID: covidwho-20239015

ABSTRACT

The effective antiviral agents that treat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are urgently needed around the world. The 3C-like protease (3CLpro) of SARS-CoV-2 plays a pivotal role in virus replication; it also has become an important therapeutic target for the infection of SARS-CoV-2. In this work, we have identified Darunavir derivatives that inhibit the 3CLpro through a high-throughput screening method based on a fluorescence resonance energy transfer (FRET) assay in vitro. We found that the compounds 29# and 50# containing polyphenol and caffeine derivatives as the P2 ligand, respectively, exhibited favorable anti-3CLpro potency with EC50 values of 6.3 µM and 3.5 µM and were shown to bind to SARS-CoV-2 3CLpro in vitro. Moreover, we analyzed the binding mode of the DRV in the 3CLpro through molecular docking. Importantly, 29# and 50# exhibited a similar activity against the protease in Omicron variants. The inhibitory effect of compounds 29# and 50# on the SARS-CoV-2 3CLpro warrants that they are worth being the template to design functionally improved inhibitors for the treatment of COVID-19.


Subject(s)
Antiviral Agents , Coronavirus 3C Proteases , Darunavir , Protease Inhibitors , SARS-CoV-2 , Humans , Antiviral Agents/pharmacology , COVID-19 , Darunavir/pharmacology , Molecular Docking Simulation , Protease Inhibitors/pharmacology , SARS-CoV-2/drug effects , SARS-CoV-2/enzymology , Coronavirus 3C Proteases/antagonists & inhibitors
5.
Clin Epigenetics ; 15(1): 100, 2023 06 12.
Article in English | MEDLINE | ID: covidwho-20238980

ABSTRACT

BACKGROUND & AIMS: The effects of SARS-CoV-2 infection can be more complex and severe in patients with hepatocellular carcinoma (HCC) as compared to other cancers. This is due to several factors, including pre-existing conditions such as viral hepatitis and cirrhosis, which are commonly associated with HCC. METHODS: We conducted an analysis of epigenomics in SARS-CoV-2 infection and HCC patients, and identified common pathogenic mechanisms using weighted gene co-expression network analysis (WGCNA) and other analyses. Hub genes were identified and analyzed using LASSO regression. Additionally, drug candidates and their binding modes to key macromolecular targets of COVID-19 were identified using molecular docking. RESULTS: The epigenomic analysis of the relationship between SARS-CoV-2 infection and HCC patients revealed that the co-pathogenesis was closely linked to immune response, particularly T cell differentiation, regulation of T cell activation and monocyte differentiation. Further analysis indicated that CD4+ T cells and monocytes play essential roles in the immunoreaction triggered by both conditions. The expression levels of hub genes MYLK2, FAM83D, STC2, CCDC112, EPHX4 and MMP1 were strongly correlated with SARS-CoV-2 infection and the prognosis of HCC patients. In our study, mefloquine and thioridazine were identified as potential therapeutic agents for COVID-19 in combined with HCC. CONCLUSIONS: In this research, we conducted an epigenomics analysis to identify common pathogenetic processes between SARS-CoV-2 infection and HCC patients, providing new insights into the pathogenesis and treatment of HCC patients infected with SARS-CoV-2.


Subject(s)
COVID-19 , Carcinoma, Hepatocellular , Liver Neoplasms , Humans , SARS-CoV-2 , DNA Methylation , Molecular Docking Simulation , Microtubule-Associated Proteins , Cell Cycle Proteins , Epoxide Hydrolases
6.
Molecules ; 28(11)2023 May 24.
Article in English | MEDLINE | ID: covidwho-20238192

ABSTRACT

Essential oils (Eos) have demonstrated antiviral activity, but their toxicity can hinder their use as therapeutic agents. Recently, some essential oil components have been used within safe levels of acceptable daily intake limits without causing toxicity. The "ImmunoDefender," a novel antiviral compound made from a well-known mixture of essential oils, is considered highly effective in treating SARS-CoV-2 infections. The components and doses were chosen based on existing information about their structure and toxicity. Blocking the main protease (Mpro) of SARS-CoV-2 with high affinity and capacity is critical for inhibiting the virus's pathogenesis and transmission. In silico studies were conducted to examine the molecular interactions between the main essential oil components in "ImmunoDefender" and SARS-CoV-2 Mpro. The screening results showed that six key components of ImmunoDefender formed stable complexes with Mpro via its active catalytic site with binding energies ranging from -8.75 to -10.30 kcal/mol, respectively for Cinnamtannin B1, Cinnamtannin B2, Pavetannin C1, Syzyginin B, Procyanidin C1, and Tenuifolin. Furthermore, three essential oil bioactive inhibitors, Cinnamtannin B1, Cinnamtannin B2, and Pavetannin C, had significant ability to bind to the allosteric site of the main protease with binding energies of -11.12, -10.74, and -10.79 kcal/mol; these results suggest that these essential oil bioactive compounds may play a role in preventing the attachment of the translated polyprotein to Mpro, inhibiting the virus's pathogenesis and transmission. These components also had drug-like characteristics similar to approved and effective drugs, suggesting that further pre-clinical and clinical studies are needed to confirm the generated in silico outcomes.


Subject(s)
COVID-19 , Oils, Volatile , Humans , SARS-CoV-2 , Antiviral Agents/chemistry , Oils, Volatile/pharmacology , Molecular Docking Simulation , Protease Inhibitors/chemistry , Viral Nonstructural Proteins/metabolism , Peptide Hydrolases/metabolism , Molecular Dynamics Simulation
7.
Viruses ; 15(5)2023 05 09.
Article in English | MEDLINE | ID: covidwho-20237088

ABSTRACT

During the COVID-19 pandemic, drug repurposing represented an effective strategy to obtain quick answers to medical emergencies. Based on previous data on methotrexate (MTX), we evaluated the anti-viral activity of several DHFR inhibitors in two cell lines. We observed that this class of compounds showed a significant influence on the virus-induced cytopathic effect (CPE) partly attributed to the intrinsic anti-metabolic activity of these drugs, but also to a specific anti-viral function. To elucidate the molecular mechanisms, we took advantage of our EXSCALATE platform for in-silico molecular modelling and further validated the influence of these inhibitors on nsp13 and viral entry. Interestingly, pralatrexate and trimetrexate showed superior effects in counteracting the viral infection compared to other DHFR inhibitors. Our results indicate that their higher activity is due to their polypharmacological and pleiotropic profile. These compounds can thus potentially give a clinical advantage in the management of SARS-CoV-2 infection in patients already treated with this class of drugs.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/metabolism , Pandemics , Molecular Docking Simulation , Antiviral Agents/pharmacology , Antiviral Agents/metabolism , Drug Repositioning/methods
8.
Pak J Biol Sci ; 26(2): 81-90, 2023 Jan.
Article in English | MEDLINE | ID: covidwho-20236999

ABSTRACT

<b>Background and Objective:</b> The COVID-19, which has been circulating since late 2019, is caused by SARS-CoV-2. Because of its high infectivity, this virus has spread widely throughout the world. Spike glycoprotein is one of the proteins found in SARS-CoV-2. Spike glycoproteins directly affect infection by forming ACE-2 receptors on host cells. Inhibiting glycoprotein spikes could be one method of treating COVID-19. In this study, the antivirus marketed as a database will be repurposed into an antiviral SARS-CoV-2 and the selected compounds will be modified to become organoselenium compounds. <b>Materials and Methods:</b> The research was carried out using <i>in silico</i> methods, such as rigid docking and flexible docking. To obtain information about the interaction between spike glycoprotein and ligands, MOE 2014.09 was used to perform the molecular docking simulation. <b>Results:</b> The analysis of binding energy values was used to select the ten best ligands from the first stage of the molecular docking simulation, which was then modified according to the previous QSAR study to produce 96 new molecules. The second stage of molecular docking simulation was performed with modified molecules. The best-modified ligand was chosen by analyzing the ADME-Tox property, RMSD value and binding energy value. <b>Conclusion:</b> The best three unmodified ligands, Ombitasvir, Elbasvir and Ledipasvir, have a binding energy value of -15.8065, -15.3842 and -15.1255 kcal mol<sup>1</sup>, respectively and the best three modified ligands ModL1, ModL2 and ModL3 has a binding value of -15.6716, -13.9489 and -13.2951 kcal mol<sup>1</sup>, respectively with an RMSD value of 1.7109 Å, 2.3179 Å and 1.7836 Å.


Subject(s)
COVID-19 , Organoselenium Compounds , Humans , SARS-CoV-2 , Ligands , Molecular Docking Simulation , Antiviral Agents/pharmacology , Molecular Dynamics Simulation
9.
J Am Chem Soc ; 145(24): 13204-13214, 2023 06 21.
Article in English | MEDLINE | ID: covidwho-20236265

ABSTRACT

We report the results of computational modeling of the reactions of the SARS-CoV-2 main protease (MPro) with four potential covalent inhibitors. Two of them, carmofur and nirmatrelvir, have shown experimentally the ability to inhibit MPro. Two other compounds, X77A and X77C, were designed computationally in this work. They were derived from the structure of X77, a non-covalent inhibitor forming a tight surface complex with MPro. We modified the X77 structure by introducing warheads capable of reacting with the catalytic cysteine residue in the MPro active site. The reaction mechanisms of the four molecules with MPro were investigated by quantum mechanics/molecular mechanics (QM/MM) simulations. The results show that all four compounds form covalent adducts with the catalytic cysteine Cys 145 of MPro. From the chemical perspective, the reactions of these four molecules with MPro follow three distinct mechanisms. The reactions are initiated by a nucleophilic attack of the thiolate group of the deprotonated cysteine residue from the catalytic dyad Cys145-His41 of MPro. In the case of carmofur and X77A, the covalent binding of the thiolate to the ligand is accompanied by the formation of the fluoro-uracil leaving group. The reaction with X77C follows the nucleophilic aromatic substitution SNAr mechanism. The reaction of MPro with nirmatrelvir (which has a reactive nitrile group) leads to the formation of a covalent thioimidate adduct with the thiolate of the Cys145 residue in the enzyme active site. Our results contribute to the ongoing search for efficient inhibitors of the SARS-CoV-2 enzymes.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Cysteine , Molecular Dynamics Simulation , Protease Inhibitors/pharmacology , Protease Inhibitors/chemistry , Antiviral Agents/pharmacology , Molecular Docking Simulation
10.
J Chem Phys ; 158(21)2023 Jun 07.
Article in English | MEDLINE | ID: covidwho-20235913

ABSTRACT

We present a hybrid, multi-method, computational scheme for protein/ligand systems well suited to be used on modern and forthcoming massively parallel computing systems. The scheme relies on a multi-scale polarizable molecular modeling, approach to perform molecular dynamics simulations, and on an efficient Density Functional Theory (DFT) linear scaling method to post-process simulation snapshots. We use this scheme to investigate recent α-ketoamide inhibitors targeting the main protease of the SARS-CoV-2 virus. We assessed the reliability and the coherence of the hybrid scheme, in particular, by checking the ability of MM and DFT to reproduce results from high-end ab initio computations regarding such inhibitors. The DFT approach enables an a posteriori fragmentation of the system and an investigation into the strength of interaction among identified fragment pairs. We show the necessity of accounting for a large set of plausible protease/inhibitor conformations to generate reliable interaction data. Finally, we point out ways to further improve α-ketoamide inhibitors to more strongly interact with particular protease domains neighboring the active site.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Ligands , Reproducibility of Results , Protease Inhibitors/pharmacology , Protease Inhibitors/chemistry , Coronavirus 3C Proteases , Molecular Dynamics Simulation , Catalytic Domain , Molecular Docking Simulation
11.
J Nat Prod ; 86(6): 1428-1436, 2023 Jun 23.
Article in English | MEDLINE | ID: covidwho-20234189

ABSTRACT

Traditional herbal medicine offers opportunities to discover novel therapeutics against SARS-CoV-2 mutation. The dried aerial part of mint (Mentha canadensis L.) was chosen for bioactivity-guided extraction. Seven constituents were isolated and characterized by nuclear magnetic resonance (NMR) and mass spectrometry (MS). Syringic acid and methyl rosmarinate were evaluated in drug combination treatment. Ten amide derivatives of methyl rosmarinate were synthesized, and the dodecyl (13) and 3-ethylphenyl (19) derivatives demonstrated significant improvement in the anti-SARS-CoV-2 plaque reduction assay, achieving IC50 of 0.77 and 2.70 µM, respectively, against Omicron BA.1 as compared to methyl rosmarinate's IC50 of 57.0 µM. Spike protein binding and 3CLpro inhibition assays were performed to explore the viral inhibition mechanism. Molecular docking of compounds 13 and 19 to 3CLpro was performed to reveal potential interaction. In summary, natural products with anti-Omicron BA.1 activity were isolated from Mentha canadensis and derivatives of methyl rosmarinate were synthesized, showing 21- to 74-fold improvement in antiviral activity against Omicron BA.1.


Subject(s)
Biological Products , COVID-19 , Mentha , Antiviral Agents/pharmacology , Molecular Docking Simulation , SARS-CoV-2 , Anti-Inflammatory Agents, Non-Steroidal , Antioxidants , Biological Products/pharmacology , Cinnamates , Depsides
12.
Methods Mol Biol ; 2673: 431-452, 2023.
Article in English | MEDLINE | ID: covidwho-20233939

ABSTRACT

Since the onset of the COVID-19 pandemic, a number of approaches have been adopted by the scientific communities for developing efficient vaccine candidate against SARS-CoV-2. Conventional approaches of developing a vaccine require a long time and a series of trials and errors which indeed limit the feasibility of such approaches for developing a dependable vaccine in an emergency situation like the COVID-19 pandemic. Hitherto, most of the available vaccines have been developed against a particular antigen of SARS-CoV, spike protein in most of the cases, and intriguingly, these vaccines are not effective against all the pathogenic coronaviruses. In this context, immunoinformatics-based reverse vaccinology approaches enable a robust design of efficacious peptide-based vaccines against all the infectious strains of coronaviruses within a short frame of time. In this chapter, we enumerate the methodological trajectory of developing a universal anti-SARS-CoV-2 vaccine, namely, "AbhiSCoVac," through advanced computational biology-based immunoinformatics approach and its in-silico validation using molecular dynamics simulations.


Subject(s)
COVID-19 , Viral Vaccines , Humans , COVID-19/prevention & control , COVID-19 Vaccines , SARS-CoV-2 , Pandemics/prevention & control , Molecular Docking Simulation , Epitopes, B-Lymphocyte , Epitopes, T-Lymphocyte , Vaccines, Subunit , Computational Biology
13.
J Nat Prod ; 86(6): 1536-1549, 2023 Jun 23.
Article in English | MEDLINE | ID: covidwho-20233730

ABSTRACT

Aurones are a small subgroup of flavonoids in which the basic C6-C3-C6 skeleton is arranged as (Z)-2-benzylidenebenzofuran-3(2H)-one. These compounds are structural isomers of flavones and flavonols, natural products reported as potent inhibitors of SARS-CoV-2 replication. Herein, we report the design, synthesis, and anti-SARS-CoV-2 activity of a series of 25 aurones bearing different oxygenated groups (OH, OCH3, OCH2OCH3, OCH2O, OCF2H, and OCH2C6H4R) at the A- and/or B-rings using cell-based screening assays. We observed that 12 of the 25 compounds exhibit EC50 < 3 µM (8e, 8h, 8j, 8k, 8l, 8m, 8p, 8q, 8r, 8w, 8x, and 8y), of which five presented EC50 < 1 µM (8h, 8m, 8p, 8q, and 8w) without evident cytotoxic effect in Calu-3 cells. The substitution of the A- and/or B-ring with OCH3, OCH2OCH3, and OCF2H groups seems beneficial for the antiviral activity, while the corresponding phenolic derivatives showed a significant decrease in the anti-SARS-CoV-2 activity. The most potent compound of the series, aurone 8q (EC50 = 0.4 µM, SI = 2441.3), is 2 to 3 times more effective than the polyphenolic flavonoids myricetin (2) and baicalein (1), respectively. Investigation of the five more active compounds as inhibitors of SARS-CoV-2 3CLpro based on molecular dynamic calculations suggested that these aurones should detach from the active site of 3CLpro, and, probably, they could bind to another SARS-CoV-2 protein target (either receptor or enzyme).


Subject(s)
Benzofurans , COVID-19 , Humans , SARS-CoV-2 , Benzofurans/pharmacology , Flavonoids/pharmacology , Flavonoids/chemistry , Antiviral Agents/pharmacology , Protease Inhibitors/pharmacology , Molecular Docking Simulation
14.
J Chem Theory Comput ; 19(11): 3359-3378, 2023 Jun 13.
Article in English | MEDLINE | ID: covidwho-20233230

ABSTRACT

We subject a series of five protein-ligand systems which contain important SARS-CoV-2 targets, 3-chymotrypsin-like protease (3CLPro), papain-like protease, and adenosine ribose phosphatase, to long time scale and adaptive sampling molecular dynamics simulations. By performing ensembles of ten or twelve 10 µs simulations for each system, we accurately and reproducibly determine ligand binding sites, both crystallographically resolved and otherwise, thereby discovering binding sites that can be exploited for drug discovery. We also report robust, ensemble-based observation of conformational changes that occur at the main binding site of 3CLPro due to the presence of another ligand at an allosteric binding site explaining the underlying cascade of events responsible for its inhibitory effect. Using our simulations, we have discovered a novel allosteric mechanism of inhibition for a ligand known to bind only at the substrate binding site. Due to the chaotic nature of molecular dynamics trajectories, regardless of their temporal duration individual trajectories do not allow for accurate or reproducible elucidation of macroscopic expectation values. Unprecedentedly at this time scale, we compare the statistical distribution of protein-ligand contact frequencies for these ten/twelve 10 µs trajectories and find that over 90% of trajectories have significantly different contact frequency distributions. Furthermore, using a direct binding free energy calculation protocol, we determine the ligand binding free energies for each of the identified sites using long time scale simulations. The free energies differ by 0.77 to 7.26 kcal/mol across individual trajectories depending on the binding site and the system. We show that, although this is the standard way such quantities are currently reported at long time scale, individual simulations do not yield reliable free energies. Ensembles of independent trajectories are necessary to overcome the aleatoric uncertainty in order to obtain statistically meaningful and reproducible results. Finally, we compare the application of different free energy methods to these systems and discuss their advantages and disadvantages. Our findings here are generally applicable to all molecular dynamics based applications and not confined to the free energy methods used in this study.


Subject(s)
COVID-19 , Molecular Dynamics Simulation , Humans , SARS-CoV-2 , Ligands , Binding Sites , Proteins/chemistry , Molecular Docking Simulation
15.
Int J Mol Sci ; 24(10)2023 May 16.
Article in English | MEDLINE | ID: covidwho-20232996

ABSTRACT

When an epidemic started in the Chinese city of Wuhan in December 2019, coronavirus was identified as the cause. Infection by the virus occurs through the interaction of viral S protein with the hosts' angiotensin-converting enzyme 2. By leveraging resources such as the DrugBank database and bioinformatics techniques, ligands with potential activity against the SARS-CoV-2 spike protein were designed and identified in this investigation. The FTMap server and the Molegro software were used to determine the active site of the Spike-ACE2 protein's crystal structure. Virtual screening was performed using a pharmacophore model obtained from antiparasitic drugs, obtaining 2000 molecules from molport®. The ADME/Tox profiles were used to identify the most promising compounds with desirable drug characteristics. The binding affinity investigation was then conducted with selected candidates. A molecular docking study showed five structures with better binding affinity than hydroxychloroquine. Ligand_003 showed a binding affinity of -8.645 kcal·mol-1, which was considered an optimal value for the study. The values presented by ligand_033, ligand_013, ligand_044, and ligand_080 meet the profile of novel drugs. To choose compounds with favorable potential for synthesis, synthetic accessibility studies and similarity analyses were carried out. Molecular dynamics and theoretical IC50 values (ranging from 0.459 to 2.371 µM) demonstrate that these candidates are promising for further tests. Chemical descriptors showed that the candidates had strong molecule stability. Theoretical analyses here show that these molecules have potential as SARS-CoV-2 antivirals and therefore warrant further investigation.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Molecular Docking Simulation , Angiotensin-Converting Enzyme 2 , Ligands , Molecular Dynamics Simulation , Antiviral Agents/pharmacology , Antiviral Agents/chemistry , Protein Binding
16.
J Chem Inf Model ; 63(11): 3601-3613, 2023 06 12.
Article in English | MEDLINE | ID: covidwho-20232259

ABSTRACT

The SARS-CoV-2 main protease (Mpro) is a crucial enzyme for viral replication and has been considered an attractive drug target for the treatment of COVID-19. In this study, virtual screening techniques and in vitro assays were combined to identify novel Mpro inhibitors starting from around 8000 FDA-approved drugs. The docking analysis highlighted 17 promising best hits, biologically characterized in terms of their Mpro inhibitory activity. Among them, 7 cephalosporins and the oral anticoagulant betrixaban were able to block the enzyme activity in the micromolar range with no cytotoxic effect at the highest concentration tested. After the evaluation of the degree of conservation of Mpro residues involved in the binding with the studied ligands, the ligands' activity on SARS-CoV-2 replication was assessed. The ability of betrixaban to affect SARS-CoV-2 replication associated to its antithrombotic effect could pave the way for its possible use in the treatment of hospitalized COVID-19 patients.


Subject(s)
COVID-19 , Humans , SARS-CoV-2 , Antiviral Agents/pharmacology , Antiviral Agents/chemistry , Drug Repositioning , Ligands , Protease Inhibitors/pharmacology , Protease Inhibitors/chemistry , Molecular Docking Simulation , Molecular Dynamics Simulation
17.
Sci Rep ; 13(1): 9161, 2023 06 06.
Article in English | MEDLINE | ID: covidwho-20245441

ABSTRACT

Proteases encoded by SARS-CoV-2 constitute a promising target for new therapies against COVID-19. SARS-CoV-2 main protease (Mpro, 3CLpro) and papain-like protease (PLpro) are responsible for viral polyprotein cleavage-a process crucial for viral survival and replication. Recently it was shown that 2-phenylbenzisoselenazol-3(2H)-one (ebselen), an organoselenium anti-inflammatory small-molecule drug, is a potent, covalent inhibitor of both the proteases and its potency was evaluated in enzymatic and antiviral assays. In this study, we screened a collection of 34 ebselen and ebselen diselenide derivatives for SARS-CoV-2 PLpro and Mpro inhibitors. Our studies revealed that ebselen derivatives are potent inhibitors of both the proteases. We identified three PLpro and four Mpro inhibitors superior to ebselen. Independently, ebselen was shown to inhibit the N7-methyltransferase activity of SARS-CoV-2 nsp14 protein involved in viral RNA cap modification. Hence, selected compounds were also evaluated as nsp14 inhibitors. In the second part of our work, we employed 11 ebselen analogues-bis(2-carbamoylaryl)phenyl diselenides-in biological assays to evaluate their anti-SARS-CoV-2 activity in Vero E6 cells. We present their antiviral and cytoprotective activity and also low cytotoxicity. Our work shows that ebselen, its derivatives, and diselenide analogues constitute a promising platform for development of new antivirals targeting the SARS-CoV-2 virus.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/metabolism , Methyltransferases , Peptide Hydrolases , Antiviral Agents/pharmacology , Antiviral Agents/metabolism , Cysteine Endopeptidases/metabolism , Protease Inhibitors/pharmacology , Molecular Docking Simulation
18.
Int J Mol Sci ; 23(24)2022 Dec 15.
Article in English | MEDLINE | ID: covidwho-20245403

ABSTRACT

Structure-based virtual screening (SBVS), also known as molecular docking, has been increasingly applied to discover small-molecule ligands based on the protein structures in the early stage of drug discovery. In this review, we comprehensively surveyed the prospective applications of molecular docking judged by solid experimental validations in the literature over the past fifteen years. Herein, we systematically analyzed the novelty of the targets and the docking hits, practical protocols of docking screening, and the following experimental validations. Among the 419 case studies we reviewed, most virtual screenings were carried out on widely studied targets, and only 22% were on less-explored new targets. Regarding docking software, GLIDE is the most popular one used in molecular docking, while the DOCK 3 series showed a strong capacity for large-scale virtual screening. Besides, the majority of identified hits are promising in structural novelty and one-quarter of the hits showed better potency than 1 µM, indicating that the primary advantage of SBVS is to discover new chemotypes rather than highly potent compounds. Furthermore, in most studies, only in vitro bioassays were carried out to validate the docking hits, which might limit the further characterization and development of the identified active compounds. Finally, several successful stories of SBVS with extensive experimental validations have been highlighted, which provide unique insights into future SBVS drug discovery campaigns.


Subject(s)
Drug Discovery , Software , Molecular Docking Simulation , Proteins , Ligands , Protein Binding
19.
Front Immunol ; 14: 1167639, 2023.
Article in English | MEDLINE | ID: covidwho-20245313

ABSTRACT

Background: Corona Virus Disease 2019 (COVID-19) and Osteoarthritis (OA) are diseases that seriously affect the physical and mental health and life quality of patients, particularly elderly patients. However, the association between COVID-19 and osteoarthritis at the genetic level has not been investigated. This study is intended to analyze the pathogenesis shared by OA and COVID-19 and to identify drugs that could be used to treat SARS-CoV-2-infected OA patients. Methods: The four datasets of OA and COVID-19 (GSE114007, GSE55235, GSE147507, and GSE17111) used for the analysis in this paper were obtained from the GEO database. Common genes of OA and COVID-19 were identified through Weighted Gene Co-Expression Network Analysis (WGCNA) and differential gene expression analysis. The least absolute shrinkage and selection operator (LASSO) algorithm was used to screen key genes, which were analyzed for expression patterns by single-cell analysis. Finally, drug prediction and molecular docking were carried out using the Drug Signatures Database (DSigDB) and AutoDockTools. Results: Firstly, WGCNA identified a total of 26 genes common between OA and COVID-19, and functional analysis of the common genes revealed the common pathological processes and molecular changes between OA and COVID-19 are mainly related to immune dysfunction. In addition, we screened 3 key genes, DDIT3, MAFF, and PNRC1, and uncovered that key genes are possibly involved in the pathogenesis of OA and COVID-19 through high expression in neutrophils. Finally, we established a regulatory network of common genes between OA and COVID-19, and the free energy of binding estimation was used to identify suitable medicines for the treatment of OA patients infected with SARS-CoV-2. Conclusion: In the present study, we succeeded in identifying 3 key genes, DDIT3, MAFF, and PNRC1, which are possibly involved in the development of both OA and COVID-19 and have high diagnostic value for OA and COVID-19. In addition, niclosamide, ciclopirox, and ticlopidine were found to be potentially useful for the treatment of OA patients infected with SARS-CoV-2.


Subject(s)
COVID-19 , Osteoarthritis , Aged , Humans , COVID-19/diagnosis , COVID-19/genetics , SARS-CoV-2/genetics , Molecular Docking Simulation , Algorithms , Osteoarthritis/diagnosis , Osteoarthritis/drug therapy , Osteoarthritis/genetics , COVID-19 Testing
20.
J Comput Aided Mol Des ; 37(8): 339-355, 2023 08.
Article in English | MEDLINE | ID: covidwho-20244179

ABSTRACT

Identification of potential therapeutic candidates can be expedited by integrating computational modeling with domain aware machine learning (ML) models followed by experimental validation in an iterative manner. Generative deep learning models can generate thousands of new candidates, however, their physiochemical and biochemical properties are typically not fully optimized. Using our recently developed deep learning models and a scaffold as a starting point, we generated tens of thousands of compounds for SARS-CoV-2 Mpro that preserve the core scaffold. We utilized and implemented several computational tools such as structural alert and toxicity analysis, high throughput virtual screening, ML-based 3D quantitative structure-activity relationships, multi-parameter optimization, and graph neural networks on generated candidates to predict biological activity and binding affinity in advance. As a result of these combined computational endeavors, eight promising candidates were singled out and put through experimental testing using Native Mass Spectrometry and FRET-based functional assays. Two of the tested compounds with quinazoline-2-thiol and acetylpiperidine core moieties showed IC[Formula: see text] values in the low micromolar range: [Formula: see text] [Formula: see text]M and 3.41±0.0015 [Formula: see text]M, respectively. Molecular dynamics simulations further highlight that binding of these compounds results in allosteric modulations within the chain B and the interface domains of the Mpro. Our integrated approach provides a platform for data driven lead optimization with rapid characterization and experimental validation in a closed loop that could be applied to other potential protein targets.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Molecular Docking Simulation , Molecular Dynamics Simulation , Protease Inhibitors/pharmacology , Antiviral Agents/pharmacology , Antiviral Agents/chemistry
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