A computational study to disclose potential drugs and vaccine ensemble for COVID-19 conundrum

Investigating the polyethylene degradation mechanism using docking and molecular dynamics simulations

Polyethylene (PE), widely utilized in everyday life, is notorious for its protracted degradation period, extending over decades, presenting an environmental hazard. Recently, there has been growing interest in utilizing microorganisms to aid in PE decomposition. Molecular docking and molecular dynamics simulations are valuable tools for understanding specific mechanisms and conducting initial screenings to support experimental research in this context. In this study, various enzymes, including lignin peroxidase, laccase, manganese peroxidase, and cutinase, sourced from Phanerodontia chrysosporium, Melanocarpus albomyces, and Fusarium vanettenii, were investigated. The docking simulations revealed that lignin peroxidase exhibited the most substantial binding interaction with PE, displaying a binding energy of - 4.69162 kcal mol-1 and an RMSD value of 0.93428 Å. Following lignin peroxidase in binding strength were laccase, manganese peroxidase, and cutinase. Furthermore, molecular dynamics simulations provided insights into the binding mechanisms. These simulations demonstrated stability over a 200-ns period, as indicated by RMSD and RMSF values below 0.2 nm. Additionally, the study delved into the interaction mechanisms between microorganisms and plastic molecules, enriching our understanding of this process. While the findings of this study may be considered modest, they contribute to a broader perspective and have the potential to influence more profound and significant research in the field.

Design of an Epitope-Based Vaccine Against MERS-CoV

Background and Objectives: Middle East Respiratory Syndrome (MERS) is a viral respiratory illness caused by a coronavirus called Middle East respiratory syndrome. In the current study, immunoinformatics studies were applied to design an epitope-based vaccine construct against Middle East Respiratory Syndrome. Materials and Methods: In this study, epitopes base vaccine construct was designed against MERS using immunoinformatics approach. Results: In this approach, the targeted proteins were screened, and probable antigenic, non-allergenic, and good water-soluble epitopes were selected for vaccine construction. In vaccine construction, the selected epitopes were joined by GPGPG linkers, and a linear multi-epitope vaccine was constructed. The vaccine construct underwent a physiochemical property analysis. The 3D structure of the vaccine construct was predicted and subjected to refinement. After the refinement, the 3D model was subjected to a molecular docking analysis, TLRs (TLR-3 and TLR-9) were selected as receptors for vaccine construct, and the molecular docking analysis study determined that the vaccine construct has binding ability with the targeted receptor. Conclusions: The docking analysis also unveils that the vaccine construct can properly activate immune system against the target virus however experimental validation is needed to confirm the in silico findings further.

Development of a potent recombinant scFv antibody against the SARS-CoV-2 by in-depth bioinformatics study: Paving the way for vaccine/diagnostics development

BACKGROUND

The SARS-CoV-2 has led to a worldwide disaster. Thus, developing prophylactics/therapeutics is required to overcome this public health issue. Among these, producing the anti-SARS-CoV-2 single-chain variable fragment (scFv) antibodies has attracted a significant attention. Accordingly, this study aims to address this question: Is it possible to bioinformatics-based design of a potent anti-SARS-CoV-2 scFv as an alternative to current production approaches?

METHOD

Using the complexed SARS-CoV-2 spike-antibodies, two sets analyses were performed: (1) B-cell epitopes (BCEs) prediction in the spike receptor-binding domain (RBD) region as a parameter for antibody screening; (2) the computational analysis of antibodies variable domains (VH/VL). Based on these primary screenings, and docking/binding affinity rating, one antibody was selected. The protein-protein interactions (PPIs) among the selected antibody-epitope complex were predicted and its epitope conservancy was also evaluated. Thereafter, some elements were added to the final scFv: (1) the PelB signal peptide; (2) a GSGGGGS linker to connect the VH-VL. Finally, this scFv was analyzed/optimized using various web servers.

RESULTS

Among the antibody library, only one met the various criteria for being an efficient scFv candidate. Moreover, no interaction was predicted between its paratope and RBD hot-spot residues of SARS-CoV-2 variants-of-Concern (VOCs).

CONCLUSIONS

Herein, a step-by-step bioinformatics platform has been introduced to bypass some barriers of traditional antibody production approaches. Based on existing literature, the current study is one of the pioneer works in the field of bioinformatics-based scFv production. This scFv may be a good candidate for diagnostics/therapeutics design against the SARS-CoV-2 as an emerging aggressive pathogen.

A cheminformatics-biophysics correlate to identify promising lead molecules against matrix metalloproteinase-2 (MMP-2) enzyme: A promising anti-cancer target

Matrix metalloproteinase-2 (MMP-2) is an endopeptidase enzyme that is devoted to extracellular matrix proteins degradation. The enzyme is warranted as promising drugs target for different light threating diseases such as arthritis, cancer and fibrosis. Herein, in this study, three drug molecules: CMNPD8322, CMNPD8320, and CMNPD8318 were filtered as high affinity binding compounds with binding energy score of -9.75 kcal/mol, -9.11 kcal/mol, -9.05 kcal/mol, respectively. The control binding energy score was -9.01 kcal/mol. The compounds docked deeply inside the pocket interacting with S1 pocket residues. The docked complexes dynamics in real time at cellular environment was then done to decipher the stable binding conformation and intermolecular interactions network. The compounds complexes achieved very stable dynamics with root mean square deviation (RMSD) with mean value of around 2-3 Å compared to control complex that showed higher fluctuations of 5 Å. The simulation trajectories frames based binding free energy demonstrated all the compounds-MMP-2 complexes reported highly stable energy, particularly the van der Waals energy dominate the overall net energy. Similarly, the complexes revalidation of WaterSwap based energies also disclosed the complexes highly stable in term docked conformation. Also, the compounds illustrated the compounds favorable pharmacokinetics and were non-toxic and non-mutagenic. Thus, the compounds might be used thorough experimental assays to confirm compounds selective biological potency against MMP-2 enzyme.

An integrated computational approach towards novel drugs discovery against polyketide synthase 13 thioesterase domain of Mycobacterium tuberculosis

The acquired drug resistance by Mycobacterium tuberculosis (M. tuberculosis) to antibiotics urges the need for developing novel anti-M. tuberculosis drugs that possess novel mechanism of action. Since traditional drug discovery is a labor-intensive and costly process, computer aided drug design is highly appreciated tool as it speeds up and lower the cost of drug development process. Herein, Asinex antibacterial compounds were virtually screened against thioesterase domain of Polyketide synthase 13, a unique enzyme that forms α-alkyl β-ketoesters as a direct precursor of mycolic acids which are essential components of the lipid-rich cell wall of M. tuberculosis. The study identified three drug-like compounds as the most promising leads; BBB_26582140, BBD_30878599 and BBC_29956160 with binding energy value of - 11.25 kcal/mol, - 9.87 kcal/mol and - 9.33 kcal/mol, respectively. The control molecule binding energy score is -9.25 kcal/mol. Also, the docked complexes were dynamically stable with maximum root mean square deviation (RMSD) value of 3 Å. Similarly, the MM-GB\PBSA method revealed highly stable complexes with mean energy values < - 75 kcal/mol for all three systems. The net binding energy scores are validated by WaterSwap and entropy energy analysis. Furthermore, The in silico druglike and pharmacokinetic investigation revealed that the compounds could be suitable candidates for additional experimentations. In summary, the study findings are significant, and the compounds may be used in experimental validation pipeline to develop potential drugs against drug-resistant tuberculosis.

Targeting Toxoplasma gondii ME49 TgAPN2: A Bioinformatics Approach for Antiparasitic Drug Discovery

As fewer therapeutic options are available for treating toxoplasmosis, newer antiparasitic drugs that can block TgAPN2 M1 aminopeptidase are of significant value. Herein, we employed several computer-aided drug-design approaches with the objective of identifying drug molecules from the Asinex library with stable conformation and binding energy scores. By a structure-based virtual screening process, three molecules—LAS_52160953, LAS_51177972, and LAS_52506311—were identified as promising candidates, with binding affinity scores of −8.6 kcal/mol, −8.5 kcal/mol, and −8.3 kcal/mol, respectively. The compounds produced balanced interacting networks of hydrophilic and hydrophobic interactions, vital for holding the compounds at the docked cavity and stable binding conformation. The docked compound complexes with TgAPN2 were further subjected to molecular dynamic simulations that revealed mean RMSD for the LAS_52160953 complex of 1.45 Å), LAS_51177972 complex 1.02 Å, and LAS_52506311 complex 1.087 Å. Another round of binding free energy validation by MM-GBSA/MM-PBSA was done to confirm docking and simulation findings. The analysis predicted average MM-GBSA value of <−36 kcal/mol and <−35 kcal/mol by MM-PBSA. The compounds were further classified as appropriate candidates to be used as drug-like molecules and showed favorable pharmacokinetics. The shortlisted compounds showed promising biological potency against the TgAPN2 enzyme and may be used in experimental validation. They may also serve as parent structures to design novel derivatives with enhanced biological potency.

Current Treatments for COVID-19: Application of Supercritical Fluids in the Manufacturing of Oral and Pulmonary Formulations

Even though more than two years have passed since the emergence of COVID-19, the research for novel or repositioned medicines from a natural source or chemically synthesized is still an unmet clinical need. In this review, the application of supercritical fluids to the development of novel or repurposed medicines for COVID-19 and their secondary bacterial complications will be discussed. We envision three main applications of the supercritical fluids in this field: (i) drug micronization, (ii) supercritical fluid extraction of bioactives and (iii) sterilization. The supercritical fluids micronization techniques can help to improve the aqueous solubility and oral bioavailability of drugs, and consequently, the need for lower doses to elicit the same pharmacological effects can result in the reduction in the dose administered and adverse effects. In addition, micronization between 1 and 5 µm can aid in the manufacturing of pulmonary formulations to target the drug directly to the lung. Supercritical fluids also have enormous potential in the extraction of natural bioactive compounds, which have shown remarkable efficacy against COVID-19. Finally, the successful application of supercritical fluids in the inactivation of viruses opens up an opportunity for their application in drug sterilization and in the healthcare field.

Mapping Potential Vaccine Candidates Predicted by VaxiJen for Different Viral Pathogens between 2017-2021-A Scoping Review

Reverse vaccinology (RV) is a promising alternative to traditional vaccinology. RV focuses on in silico methods to identify antigens or potential vaccine candidates (PVCs) from a pathogen's proteome. Researchers use VaxiJen, the most well-known RV tool, to predict PVCs for various pathogens. The purpose of this scoping review is to provide an overview of PVCs predicted by VaxiJen for different viruses between 2017 and 2021 using Arksey and O'Malley's framework and the Preferred Reporting Items for Systematic Reviews extension for Scoping Reviews (PRISMA-ScR) guidelines. We used the term 'vaxijen' to search PubMed, Scopus, Web of Science, EBSCOhost, and ProQuest One Academic. The protocol was registered at the Open Science Framework (OSF). We identified articles on this topic, charted them, and discussed the key findings. The database searches yielded 1033 articles, of which 275 were eligible. Most studies focused on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), published between 2020 and 2021. Only a few articles (8/275; 2.9%) conducted experimental validations to confirm the predictions as vaccine candidates, with 2.2% (6/275) articles mentioning recombinant protein expression. Researchers commonly targeted parts of the SARS-CoV-2 spike (S) protein, with the frequently predicted epitopes as PVCs being major histocompatibility complex (MHC) class I T cell epitopes WTAGAAAYY, RQIAPGQTG, IAIVMVTIM, and B cell epitope IAPGQTGKIADY, among others. The findings of this review are promising for the development of novel vaccines. We recommend that vaccinologists use these findings as a guide to performing experimental validation for various viruses, with SARS-CoV-2 as a priority, because better vaccines are needed, especially to stay ahead of the emergence of new variants. If successful, these vaccines could provide broader protection than traditional vaccines.

Vaccinomics to Design a Multiepitope Vaccine against Legionella pneumophila

Legionella pneumophila is found in the natural aquatic environment and can resist a wide range of environmental conditions. There are around fifty species of Legionella, at least twenty-four of which are directly linked to infections in humans. L. pneumophila is the cause of Legionnaires' disease, a potentially lethal form of pneumonia. By blocking phagosome-lysosome fusion, L. pneumophila lives and proliferates inside macrophages. For this disease, there is presently no authorized multiepitope vaccine available. For the multi-epitope-based vaccine (MEBV), the best antigenic candidates were identified using immunoinformatics and subtractive proteomic techniques. Several immunoinformatics methods were utilized to predict B and T cell epitopes from vaccine candidate proteins. To construct an in silico vaccine, epitopes (07 CTL, 03 HTL, and 07 LBL) were carefully selected and docked with MHC molecules (MHC-I and MHC-II) and human TLR4 molecules. To increase the immunological response, the vaccine was combined with a 50S ribosomal adjuvant. To maximize vaccine protein expression, MEBV was cloned and reverse-translated in Escherichia coli. To prove the MEBV's efficacy, more experimental validation is required. After its development, the resulting vaccine is greatly hoped to aid in the prevention of L. pneumophila infections.

Antiviral activities of 4H-chromen-4-one scaffold-containing flavonoids against SARS-CoV-2 using computational and in vitro approaches

The widespread outbreak of the novel coronavirus called severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused the main health challenge worldwide. This pandemic has attracted the attention of the research communities in various fields, prompting efforts to discover rapid drug molecules for the treatment of the life-threatening COVID-19 disease. This study is aimed at investigating 4H-chromen-4-one scaffold-containing flavonoids that combat the SARS-CoV-2 virus using computational and in vitro approaches. Virtual screening studies of the molecule's library for 4H-chromen-4-one scaffold were performed with the recently reported coronavirus main protease (M^pro, also called 3CL^pro) because it plays an essential role in the maturation and processing of the viral polyprotein. Based on the virtual screening, the top hit molecules such as isoginkgetin and afzelin molecules were selected for further estimating in vitro antiviral efficacies against SARS-CoV-2 in Vero cells. Additionally, these molecules were also docked with RNA-dependent RNA Polymerase (RdRp) to reveal the ligands-protein molecular interaction. In the in vitro study, isoginkgetin showed remarkable inhibition potency against the SARS-CoV-2 virus, with an IC₅₀ value of 22.81 μM, compared to remdesivir, chloroquine, and lopinavir with IC₅₀ values of 7.18, 11.63, and 11.49 μM, respectively. Furthermore, the complex stability of isoginkgetin with an active binding pocket of the SARS-CoV-2 M^pro and RdRp supports its inhibitory potency against the SARS-CoV-2. Thus, isoginkgetin is a potent leading drug candidate and needs to be used in in vivo trials for the treatment of SARS-CoV-2 infected patients.

Comparing the Nucleocapsid Proteins of Human Coronaviruses: Structure, Immunoregulation, Vaccine, and Targeted Drug

The seven pathogenic human coronaviruses (HCoVs) include HCoV-229E, HCoV-OC43, HCoV-NL63, and HCoV-HKU1, which usually cause mild upper respiratory tract diseases, and SARS-CoV, MERS-CoV, and SARS-CoV-2, which cause a severe acute respiratory syndrome. The nucleocapsid (N) protein, as the dominant structural protein from coronaviruses that bind to the genomic RNA, participates in various vital activities after virus invasion and will probably become a promising target of antiviral drug design. Therefore, a comprehensive literature review of human coronavirus’ pathogenic mechanism and therapeutic strategies is necessary for the control of the pandemic. Here, we give a systematic summary of the structures, immunoregulation, and potential vaccines and targeted drugs of the HCoVs N protein. First, we provide a general introduction to the fundamental structures and molecular function of N protein. Next, we outline the N protein mediated immune regulation and pathogenesis mechanism. Finally, we comprehensively summarize the development of potential N protein-targeted drugs and candidate vaccines to treat coronavirus disease 2019 (COVID-19). We believe this review provides insight into the virulence and transmission of SARS-CoV-2 as well as support for further study on epidemic control of COVID-19.

Deciphering the immunogenic T-cell epitopes from spike protein of SARS-CoV-2 concerning the diverse population of India

Scientists are rigorously looking for an efficient vaccine against the current pandemic due to the SARS-CoV-2 virus. The reverse vaccinology approach may provide us with significant therapeutic leads in this direction and further determination of T-cell/B-cell response to antigen. In the present study, we conducted a population coverage analysis referring to the diverse Indian population. From the Immune epitope database (IEDB), HLA- distribution analysis was performed to find the most promiscuous T-cell epitope out of In silico determined epitope of Spike protein from SARS-CoV-2. Epitopes were selected based on their binding affinity with the maximum number of HLA alleles belonging to the highest population coverage rate values for the chosen geographical area in India. 404 cleavage sites within the 1288 amino acids sequence of spike glycoprotein were determined by NetChop proteasomal cleavage prediction suggesting the presence of adequate sites in the protein sequence for cleaving into appropriate epitopes. For population coverage analysis, 179 selected epitopes present the projected population coverage up to 97.45% with 56.16 average hit and 15.07 pc90. 54 epitopes are found with the highest coverage among the Indian population and highly conserved within the given spike RBD domain sequence. Among all the predicted epitopes, 9-mer TRFASVYAW and RFDNPVLPF along with 12-mer LLAGTITSGWTF and VSQPFLMDLEGK epitopes are observed as the best due to their decent docking score and best binding affinity to corresponding HLA alleles during MD simulations. Outcomes from this study could be critical to design a vaccine against SARS-CoV-2 for a different set of populations within the country.Communicated by Ramaswamy H. Sarma.

Designing a Recombinant Vaccine against Providencia rettgeri Using Immunoinformatics Approach

Antibiotic resistance (AR) is the resistance mechanism pattern in bacteria that evolves over some time, thus protecting the bacteria against antibiotics. AR is due to bacterial evolution to make itself fit to changing environmental conditions in a quest for survival of the fittest. AR has emerged due to the misuse and overuse of antimicrobial drugs, and few antibiotics are now left to deal with these superbug infections. To combat AR, vaccination is an effective method, used either therapeutically or prophylactically. In the current study, an in silico approach was applied for the design of multi-epitope-based vaccines against Providencia rettgeri, a major cause of traveler’s diarrhea. A total of six proteins: fimbrial protein, flagellar hook protein (FlgE), flagellar basal body L-ring protein (FlgH), flagellar hook-basal body complex protein (FliE), flagellar basal body P-ring formation protein (FlgA), and Gram-negative pili assembly chaperone domain proteins, were considered as vaccine targets and were utilized for B- and T-cell epitope prediction. The predicted epitopes were assessed for allergenicity, antigenicity, virulence, toxicity, and solubility. Moreover, filtered epitopes were utilized in multi-epitope vaccine construction. The predicted epitopes were joined with each other through specific GPGPG linkers and were joined with cholera toxin B subunit adjuvant via another EAAAK linker in order to enhance the efficacy of the designed vaccine. Docking studies of the designed vaccine construct were performed with MHC-I (PDB ID: 1I1Y), MHC-II (1KG0), and TLR-4 (4G8A). Findings of the docking study were validated through molecular dynamic simulations, which confirmed that the designed vaccine showed strong interactions with the immune receptors, and that the epitopes were exposed to the host immune system for proper recognition and processing. Additionally, binding free energies were estimated, which highlighted both electrostatic energy and van der Waals forces to make the complexes stable. Briefly, findings of the current study are promising and may help experimental vaccinologists to formulate a novel multi-epitope vaccine against P. rettgeri.

Fine-tuning of the pharmacological potential of novel thiazolium ionic liquids by anion alteration

A novel series of thiazolium ionic liquids (TILs) bound to chloride (2a-c), tetrafluoroborate (BF4) (3a-c), and bis-(trifluoromethanesulfonimide) (Tf2N) anions (4a-c) was synthesized and their physicochemical characteristics were investigated using various microanalytical techniques. The pharmacological potential of the new TILs was assessed as chemotherapeutic agents for bacterial infections and ovarian cancer (SKOV-3). Notably, ILs with the same cations become more bactericidal upon their binding with the strongest chaotropic anion (TN2f). The in vitro toxicity of the TILs toward ovarian carcinoma cell lines (SKOV-3) and normal human skin fibroblast cells (HSF) revealed that all tested TILs have the capacity to induce a dose- and time-dependent decline in SKOV-3 cell viability, with Tf2N-linked TILs (4a-c) having a preferable efficacy. In addition, the new compounds showed excellent selectivity for cancer cells (SKOV-3) over healthy cells (HSF). [iPBzTh][Tf2N] (4b) is the most cytotoxic and specific one and may act as a promising anti-ovarian cancer agent.

Designing of a next generation multiepitope based vaccine (MEV) against SARS-COV-2: Immunoinformatics and in silico approaches

Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory coronavirus 2 (SARS-COV-2) is a significant threat to global health security. Till date, no completely effective drug or vaccine is available to cure COVID-19. Therefore, an effective vaccine against SARS-COV-2 is crucially needed. This study was conducted to design an effective multiepitope based vaccine (MEV) against SARS-COV-2. Seven highly antigenic proteins of SARS-COV-2 were selected as targets and different epitopes (B-cell and T-cell) were predicted. Highly antigenic and overlapping epitopes were shortlisted. Selected epitopes indicated significant interactions with the HLA-binding alleles and 99.93% coverage of the world's population. Hence, 505 amino acids long MEV was designed by connecting 16 MHC class I and eleven MHC class II epitopes with suitable linkers and adjuvant. MEV construct was non-allergenic, antigenic, stable and flexible. Furthermore, molecular docking followed by molecular dynamics (MD) simulation analyses, demonstrated a stable and strong binding affinity of MEV with human pathogenic toll-like receptors (TLR), TLR3 and TLR8. Finally, MEV codons were optimized for its in silico cloning into Escherichia coli K-12 system, to ensure its increased expression. Designed MEV in present study could be a potential candidate for further vaccine production process against COVID-19. However, to ensure its safety and immunogenic profile, the proposed MEV needs to be experimentally validated.