Inferring B-cell derived T-cell receptor induced multi-epitope-based vaccine candidate against enterovirus 71: a reverse vaccinology approach.

Purpose: Enterovirus 71, a pathogen that causes hand-foot and mouth disease (HFMD) is currently regarded as an increasing neurotropic virus in Asia and can cause severe complications in pediatric patients with blister-like sores or rashes on the hand, feet, and mouth. Notwithstanding the significant burden of the disease, no authorized vaccine is available. Previously identified attenuated and inactivated vaccines are worthless over time owing to changes in the viral genome. Materials and Methods: A novel vaccine construct using B-cell derived T-cell epitopes from the virulent polyprotein found the induction of possible immune response. In order to boost the immune system, a beta-defensin 1 preproprotein adjuvant with EAAAK linker was added at the N-terminal end of the vaccine sequence. Results: The immunogenicity of the designed, refined, and verified prospective three-dimensional-structure of the multi-epitope vaccine was found to be quite high, exhibiting non-allergenic and antigenic properties. The vaccine candidates bound to toll-like receptor 3 in a molecular docking analysis, and the efficacy of the potential vaccine to generate a strong immune response was assessed through in silico immunological simulation. Conclusion: Computational analysis has shown that the proposed multi-epitope vaccine is possibly safe for use in humans and can elicit an immune response.

Protein profiling and immunoinformatic analysis of the secretome of a metal-resistant environmental isolate Pseudomonas aeruginosa S-8.

The bacterial secretome represents a comprehensive catalog of proteins released extracellularly that have multiple important roles in virulence and intercellular communication. This study aimed to characterize the secretome of an environmental isolate Pseudomonas aeruginosa S-8 by analyzing trypsin-digested culture supernatant proteins using nano-LC-MS/MS tool. Using a combined approach of bioinformatics and mass spectrometry, 1088 proteins in the secretome were analyzed by PREDLIPO, SecretomeP 2.0, SignalP 4.1, and PSORTb tool for their subcellular localization and further categorization of secretome proteins according to signal peptides. Using the gene ontology tool, secretome proteins were categorized into different functional categories. KEGG pathway analysis identified the secreted proteins into different metabolic functional pathways. Moreover, our LC-MS/MS data revealed the secretion of various CAZymes into the extracellular milieu, which suggests its strong biotechnological applications to breakdown complex carbohydrate polymers. The identified immunodominant epitopes from the secretome of P. aeruginosa showed the characteristic of being non-allergenic, highly antigenic, nontoxic, and having a low risk of triggering autoimmune responses, which highlights their potential as successful vaccine targets. Overall, the identification of secreted proteins of P. aeruginosa could be important for both diagnostic purposes and the development of an effective candidate vaccine.

Identification of potential flavonoid compounds as antibacterial therapeutics against Klebsiella pneumoniae infection using structure-based virtual screening and molecular dynamics simulation.

Klebsiella pneumoniae, which is among the top three pathogens on WHO's priority list, is one of the gram-negative bacteria that doctors and researchers around the world have fought for decades. Capsular polysaccharide (CPS) protein is extensively recognized as an important K. pneumoniae virulence factor. Thus, CPS has become the most characterized target for the discovery of novel drug candidates. The ineffectiveness of currently existing antibiotics urges the search for potent antimicrobial compounds. Flavonoids are a group of plant metabolites that have antibacterial potential and can enhance the present medications to elicit improved results against diverse diseases without adverse reactions. Henceforth, the present study aims to illustrate the inhibitory potential of flavonoids with varying pharmacological properties, targeting the CPS protein of K. pneumoniae by in silico approaches. The flavonoid compounds (n = 169) were retrieved from the PubChem database and screened using the structure-based virtual screening approach. Compounds with the highest binding score were estimated through their pharmacokinetic effects by ADMET descriptors. Finally, four potential inhibitors with PubChem CID: (4301534, 5213, 5481948, and 637080) were selected after molecular docking and drug-likeness analysis. All four lead compounds were employed for the MDS analysis of a 100 ns time period. Various studies were undertaken to assess the stability of the protein-ligand complexes. The binding free energy was computed using MM-PBSA, and the outcomes indicated that the molecules are having stable interactions with the binding site of the target protein. The results revealed that all four compounds can be employed as potential therapeutics against K. pneumoniae.

Gold nanoparticle assisted colorimetric biosensors for rapid polyethylene terephthalate (PET) sensing for sustainable environment to monitor microplastics.

The extremely widespread and ubiquitous nature of plastics, estimated to boost its global production by 26 billion tons till 2050. The large chunks of plastic waste that decomposed down to micro- or nano plastics (MNPs) leads to various ill effects on biological entities. The conventional PET detection methods lack rapid detection of microplastics due to variances in microplastic features, long-drawn-out sample pre-processing procedures and complex instrumentation. Therefore, an instantaneous colorimetric evaluation of microplastic will ensures the simplicity of conducting assays on field. Several nanoparticle-based biosensors that detects proteins, nucleic acids, metabolites operate on either cluster or disperse state of nanoparticle. However, gold nanoparticle (AuNPs) emerges an ideal scaffold for sensory element in lateral flow biosensors due to their simple surface functionalization, unique optoelectronic properties and varied colour spectrum depending on morphologies and aggregation state. In this paper an effort has been made in the form of a hypothesis using in silico tools as a basis to detect polyethylene terephthalate (PET) - most abundant type of microplastic using gold nanoparticle based lateral flow biosensor. We retrieved sequences of PET-binding synthetic peptides and modelled their 3-D structure using I-Tasser server. The best protein model for each peptide sequences are docked with PET monomers - BHET, MHET and other PET polymeric ligands, to evaluate their binding affinities. The synthetic peptide SP 1 (WPAWKTHPILRM) docked with BHET and (MHET)4 exhibits 1.5-fold increases in binding affinity as compared to reference PET anchor peptide Dermaseptin SI (DSI). The GROMACS molecular dynamics simulation studies of synthetic peptide SP 1 - BHET & - (MHET)4 complexes for 50 ns further confirmed the stable binding. RMSF, RMSD, hydrogen bonds, Rg and SASA analysis provides useful structural insights of the SP 1 complexes as compared to reference DSI. Furthermore, SP 1 functionalized AuNP-based colorimetric device was described in detail for detection of PET.

Designing of multi-epitope peptide vaccine against Acinetobacter baumannii through combined immunoinformatics and protein interaction-based approaches.

Acinetobacter baumannii is one of the major pathogenic ESKAPE bacterium, which is responsible for about more than 722,000 cases in a year, globally. Despite the alarming increase in multidrug resistance, a safe and effective vaccine for Acinetobacter infections is still not available. Hence in the current study, a multiepitope vaccine construct was developed using linear B cell, cytotoxic T cell, and helper T cell epitopes from the antigenic and well-conserved lipopolysaccharide assembly proteins employing systematic immunoinformatics and structural vaccinology strategies. The multi-peptide vaccine was predicted to be highly antigenic, non-allergenic, non-toxic, and cover maximum population coverage worldwide. Further, the vaccine construct was modeled along with adjuvant and peptide linkers and validated to achieve a high-quality three-dimensional structure which was subsequently utilized for cytokine prediction, disulfide engineering, and docking analyses with Toll-like receptor (TLR4). Ramachandran plot showed 98.3% of the residues were located in the most favorable and permitted regions, thereby corroborating the feasibility of the modeled vaccine construct. Molecular dynamics simulation for a 100 ns timeframe further confirmed the stability of the binding vaccine-receptor complex. Finally, in silico cloning and codon adaptation were also performed with the pET28a (+) plasmid vector to determine the efficiency of expression and translation of the vaccine. Immune simulation studies demonstrated that the vaccine could trigger both B and T cell responses and can elicit strong primary, secondary, and tertiary immune responses. The designed multi-peptide subunit vaccine would certainly expedite the experimental approach for the development of a vaccine against A. baumannii infection.

Designing a Next-Generation Multiepitope-Based Vaccine against Staphylococcus aureus Using Reverse Vaccinology Approaches.

Staphylococcus aureus is a human bacterial pathogen that can cause a wide range of symptoms. As virulent and multi-drug-resistant strains of S. aureus have evolved, invasive S. aureus infections in hospitals and the community have become one of the leading causes of mortality and morbidity. The development of novel techniques is therefore necessary to overcome this bacterial infection. Vaccines are an appropriate alternative in this context to control infections. In this study, the collagen-binding protein (CnBP) from S. aureus was chosen as the target antigen, and a series of computational methods were used to find epitopes that may be used in vaccine development in a systematic way. The epitopes were passed through a filtering pipeline that included antigenicity, toxicity, allergenicity, and cytokine inducibility testing, with the objective of identifying epitopes capable of eliciting both T and B cell-mediated immune responses. To improve vaccine immunogenicity, the final epitopes and phenol-soluble modulin α4 adjuvant were fused together using appropriate linkers; as a consequence, a multiepitope vaccine was developed. The chosen T cell epitope ensemble is expected to cover 99.14% of the global human population. Furthermore, docking and dynamics simulations were used to examine the vaccine's interaction with the Toll-like receptor 2 (TLR2), revealing great affinity, consistency, and stability between the two. Overall, the data indicate that the vaccine candidate may be extremely successful, and it will need to be evaluated in experimental systems to confirm its efficiency.

An immunoinformatics and structural vaccinology study to design a multi-epitope vaccine against Staphylococcus aureus infection.

Staphylococcus aureus has been widely reported to be majorly responsible for causing nosocomial infections worldwide. Due to an increase in antibiotic-resistant strains, the development of an effective vaccine against the bacteria is the most viable alternative. Therefore, in the current work, an effort has been undertaken to develop a novel peptide-based vaccine construct against S aureus that can potentially evoke the B and T cell immune responses. The fibronectin-binding proteins are an attractive target as they play a prominent role in bacterial adherence and host cell invasion and are also well conserved among rapidly mutating pathogens. Therefore, highly immunogenic linear B lymphocytes (LBL), cytotoxic T lymphocytes (CTL), and helper T lymphocytes (HTL) epitopes were identified from the antigenic fibronectin-binding proteins A and B (FnBPA and FnBPB) of S aureus using immunoinformatics approaches. The selected peptides were confirmed to be non-allergenic, non-toxic, and with a high binding affinity to the majority of human leukocyte antigens (HLA) alleles. Consequently, the multi-peptide vaccine construct was developed by fusing the screened epitopes (three LBL, five CTL, and two HTL) together with the suitable adjuvant and linkers. In addition, the tertiary conformation of the peptide construct was modeled and later docked to the Toll-like receptor 2. Subsequently, a molecular dynamics simulation of 100 ns was employed to corroborate the stability of the designed vaccine-receptor complex. Besides exhibiting high immunogenicity and conformational stability, the developed vaccine was observed to possess wide population coverage of 99.51% worldwide. Additional in vivo and in vitro validation studies would certainly corroborate the designed vaccine construct to have improved prophylactic efficacy against S aureus.

Nanotechnology and COVID-19 Convergence: Toward New Planetary Health Interventions Against the Pandemic.

COVID-19 is a systemic disease affecting multiple organ systems and caused by infection with the SARS-CoV-2 virus. Two years into the COVID-19 pandemic and after the introduction of several vaccines, the pandemic continues to evolve in part owing to global inequities in access to preventive and therapeutic measures. We are also witnessing the introduction of antivirals against COVID-19. Against this current background, we review the progress made with nanotechnology-based approaches such as nanoformulations to combat the multiorgan effects of SARS-CoV-2 infection from a systems medicine lens. While nanotechnology has previously been widely utilized in the antiviral research domain, it has not yet received the commensurate interest in the case of COVID-19 pandemic response strategies. Notably, SARS-CoV-2 and nanomaterials are similar in size ranging from 50 to 200 nm. Nanomaterials offer the promise to reduce the side effects of antiviral drugs, codeliver multiple drugs while maintaining stability in the biological milieu, and sustain the release of entrapped drug(s) for a predetermined time period, to name but a few conceivable scenarios, wherein nanotechnology can enable and empower preventive medicine and therapeutic innovations against SARS-CoV-2. We conclude the article by underlining that nanotechnology-based interventions warrant further consideration to enable precision planetary health responses against the COVID-19 pandemic.

Immunoinformatics-guided designing of epitope-based subunit vaccine from Pilus assembly protein of Acinetobacter baumannii bacteria.

Acinetobacter baumannii, a prominent pathogen responsible for chronic infections in the blood, urinary tract, and lungs, has a high mortality due to its virulence and limited preventive methods. The present study aims to characterize the pilus assembly protein of A. baumannii to offer leads for epitope-based vaccine development. FilF is the putative pilus assembly protein that reportedly plays a supreme character in the virulence of this WHO-listed ESKAPE bacterium. Implementing various bioinformatics tools, led to the recognition of many antigenic B and T cell epitopes. Most promising B and T-cell epitopes were selected based on their binding efficiency with commonly occurring MHC alleles. Finally, we stepped down to fourteen protective antigenic peptides. These epitopes were also revealed to be non-allergenic and non-toxic. As a result, a vaccine chimera was created by linking these epitopes with appropriate linkers and adjuvant such as ß-defensins. Furthermore, homology modeling and validation were carried out, with the modeled structure being employed for molecular docking with the immunological receptor (TLR-4) found on lymphocyte cells. As a result of the molecular dynamics simulation, the interaction between human TLR-4 and the multi-epitope vaccine sequence was stable. Finally, in silico cloning and immune simulation were carried out to see the efficacy of the construct vaccine. This is the first study targeting the pilus assembly protein from A. baumannii to identify novel epitopes that hold potential for further experimental design of multi-peptide vaccine construct against the pathogen.

Designing a novel multi-epitope vaccine to evoke a robust immune response against pathogenic multidrug-resistant Enterococcus faecium bacterium.

Enterococcus faecium is an emerging ESKAPE bacterium that is capable of causing severe public health complications in humans. There are currently no licensed treatments or vaccinations to combat the deadly pathogen. We aimed to design a potent and novel prophylactic chimeric vaccine against E. faecium through an immunoinformatics approach The antigenic Penicillin-binding protein 5 (PBP 5) protein was selected to identify B and T cell epitopes, followed by conservancy analysis, population coverage, physiochemical assessment, secondary and tertiary structural analysis. Using various immunoinformatics methods and tools, two linear B-cell epitopes, five CTL epitopes, and two HTL epitopes were finally selected for vaccine development. The constructed vaccine was determined to be highly immunogenic, cytokine-producing, antigenic, non-toxic, non-allergenic, and stable, as well as potentially effective against E. faecium. In addition, disulfide engineering, codon adaptation, and in silico cloning, were used to improve stability and expression efficiency in the host E. coli. Molecular docking and molecular dynamics simulations indicated that the structure of the vaccine is stable and has a high affinity for the TLR4 receptor. The immune simulation results revealed that both B and T cells had an increased response to the vaccination component. Conclusively, the in-depth in silico analysis suggests, the proposed vaccine to elicit a robust immune response against E. faecium infection and hence a promising target for further experimental trials.

Molecular Characterization and Designing of a Novel Multiepitope Vaccine Construct Against Pseudomonas aeruginosa.

ABSTRACT: Pseudomonas aeruginosa, an ESKAPE pathogen causes many fatal clinical diseases in humans across the globe. Despite an increase in clinical instances of Pseudomonas infection, there is currently no effective vaccine or treatment available. The major membrane protein candidate of the P. aeruginosa bacterial cell is known to be a critical component for cellular bacterial susceptibility to antimicrobial peptides and survival inside the host organisms. Therefore, the current computational study aims to examine P. aeruginosa's major membrane protein, OprF, and OprI, in order to design linear B-cell, cytotoxic T-cell, and helper T-cell peptide-based vaccine constructs. Utilizing various immune-informatics tools and databases, a total of two B-cells and twelve T-cells peptides were predicted. The final vaccine design was simulated to generate a high-quality three-dimensional structure, which included epitopes, adjuvant, and linkers. The vaccine was shown to be nonallergenic, antigenic, soluble, and had the best biophysical properties. The vaccine and Toll-like receptor 4 have a strong and stable interaction, according to protein-protein docking and molecular dynamics simulations. Additionally, in silico cloning was employed to see how the developed vaccine expressed in the pET28a (+) vector. Ultimately, an immune simulation was performed to see the vaccine efficacy. In conclusion, the newly developed vaccine appears to be a promising option for a vaccine against P. aeruginosa infection. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10989-021-10356-z.

Immunoinformatic approach employing modeling and simulation to design a novel vaccine construct targeting MDR efflux pumps to confer wide protection against typhoidal Salmonella serovars.

Overcoming multi drug resistance is one of the crucial challenges to control enteric typhoid fever caused by Salmonella typhi and Salmonella paratyphi. Overexpression of efflux pumps predominantly causes drug resistance in microorganisms. Therefore, immunotherapy targeting the various efflux pumps antigens could be a promising strategy to increase the success of vaccines. An immunoinformatic approach was employed to design a Salmonellosis multi-epitope subunit vaccine peptide consisting of linear B-cell and T-cell epitopes of multidrug resistance protein families including ATP Binding Cassette (ABC), major facilitator superfamily (MFS), resistance nodulation cell division (RND), small multidrug resistance (SMR), and multidrug and toxin extrusion (MATE). The selected epitopes exhibited conservation in both S. typhi and S. paratyphi and thus could be helpful for cross-protection. Further, the final vaccine construct encompassing the peptides, adjuvants and specific linker sequences showed high immunogenicity, solubility, non-allergenic, nontoxic, and wide population coverage due to strong binding affinity to maximum HLA alleles. The three-dimensional structure was predicted, and validated using various structure validation tools. Additionally, protein-protein docking of the chimeric vaccine construct with the TLR-2 protein and molecular dynamics demonstrated stable and efficient binding. Conclusively, the immunoinformatic study showed that the novel multi epitopic vaccine construct can simulate the both T-cell and B-cell immune responses in typhoidal Salmonella serovars and could potentially be used for prophylactic or therapeutic applications.Communicated by Ramaswamy H. Sarma.

Exploring Klebsiella pneumoniae capsule polysaccharide proteins to design multiepitope subunit vaccine to fight against pneumonia.

BACKGROUND: Klebsiella pneumoniae is an emerging human pathogen causing neonatal lung disease, catheter-associated infections, and nosocomial outbreaks with high fatality rates. Capsular polysaccharide (CPS) protein plays a major determinant in virulence and is considered as a promising target for vaccine development. RESEARCH DESIGN AND METHODS: In this study, we used immunoinformatic approaches to design a multi-peptide vaccine against K. pneumonia. The epitopes were selected through several immune filters, such as antigenicity, conservancy, nontoxicity, non-allergenicity, binding affinity to HLA alleles, overlapping epitopes, and peptides having common epitopes. RESULTS: Finally, a construct comprising 2 B-Cell, 8 CTL, 2 HTL epitopes, along with adjuvant, linkers was designed. Peptide-HLA interaction analysis showed strong binding of these epitopes with several common HLA molecules. The in silico immune simulation and population coverage analysis of the vaccine showed its potential to evoke strong immune responses.. Further, the interaction between vaccine and immune was evaluated by docking and simulation, revealing high affinity and complex stability. Codon adaptation and in silico cloning revealed higher expression of vaccine in E. coli K12 expression system. CONCLUSIONS: Conclusively, the findings of the present study suggest that the designed novel multi-epitopic vaccine holds potential for further experimental validation against the pathogen.

Genome-based identification and comparative analysis of enzymes for carotenoid biosynthesis in microalgae.

Microalgae are potential feedstocks for the commercial production of carotenoids, however, the metabolic pathways for carotenoid biosynthesis across algal lineage are largely unexplored. This work is the first to provide a comprehensive survey of genes and enzymes associated with the less studied methylerythritol 4-phosphate/1-deoxy-D-xylulose 5-phosphate pathway as well as the carotenoid biosynthetic pathway in microalgae through bioinformatics and comparative genomics approach. Candidate genes/enzymes were subsequently analyzed across 22 microalgae species of lineages Chlorophyta, Rhodophyta, Heterokonta, Haptophyta, Cryptophyta, and known Arabidopsis homologs in order to study the evolutional divergence in terms of sequence-structure properties. A total of 403 enzymes playing a vital role in carotene, lutein, zeaxanthin, violaxanthin, canthaxanthin, and astaxanthin were unraveled. Of these, 85 were hypothetical proteins whose biological roles are not yet experimentally characterized. Putative functions to these hypothetical proteins were successfully assigned through a comprehensive investigation of the protein family, motifs, intrinsic physicochemical features, subcellular localization, pathway analysis, etc. Furthermore, these enzymes were categorized into major classes as per the conserved domain and gene ontology. Functional signature sequences were also identified which were observed conserved across microalgal genomes. Additionally, the structural modeling and active site architecture of three vital enzymes, DXR, PSY, and ZDS catalyzing the vital rate-limiting steps in Dunaliella salina were achieved. The enzymes were confirmed to be stereochemically reliable and stable as revealed during molecular dynamics simulation of 100 ns. The detailed functional information about individual vital enzymes will certainly help to design genetically modified algal strains with enhanced carotenoid contents.

Development of a Conserved Chimeric Vaccine for Induction of Strong Immune Response against Staphylococcus aureus Using Immunoinformatics Approaches.

Staphylococcus aureus is one of the most notorious Gram-positive bacteria with a very high mortality rate. The WHO has listed S. aureus as one of the ESKAPE pathogens requiring urgent research and development efforts to fight against it. Yet there is a major layback in the advancement of effective vaccines against this multidrug-resistant pathogen. SdrD and SdrE proteins are attractive immunogen candidates as they are conserved among all the strains and contribute specifically to bacterial adherence to the host cells. Furthermore, these proteins are predicted to be highly antigenic and essential for pathogen survival. Therefore, in this study, using the immunoinformatics approach, a novel vaccine candidate was constructed using highly immunogenic conserved T-cell and B-cell epitopes along with specific linkers, adjuvants, and consequently modeled for docking with human Toll-like receptor 2. Additionally, physicochemical properties, secondary structure, disulphide engineering, and population coverage analysis were also analyzed for the vaccine. The constructed vaccine showed good results of worldwide population coverage and a promising immune response. For evaluation of the stability of the vaccine-TLR-2 docked complex, a molecular dynamics simulation was performed. The constructed vaccine was subjected to in silico immune simulations by C-ImmSim and Immune simulation significantly provided high levels of immunoglobulins, T-helper cells, T-cytotoxic cells, and INF-γ. Lastly, upon cloning, the vaccine protein was reverse transcribed into a DNA sequence and cloned into a pET28a (+) vector to ensure translational potency and microbial expression. The overall results of the study showed that the designed novel chimeric vaccine can simultaneously elicit humoral and cell-mediated immune responses and is a reliable construct for subsequent in vivo and in vitro studies against the pathogen.

Immunoinformatics and molecular docking studies reveal a novel Multi-Epitope peptide vaccine against pneumonia infection.

Pneumonia is a major endemic disease around the world, and an effective vaccine is the need of the hour to fight against the disease. When there are no appropriate antiviral and associated therapies available, vaccine development becomes even more essential. Therefore, in the present study, a variety of immunoinformatics techniques was utilized to develop a novel multi-epitope vaccine that targets the highly immunodominant type 3 fimbrial protein of Klebsiella pneumoniae, the causal organism for pneumonia. The putative B and T cell epitopes were predicted from the protein and screened for antigenicity, toxicity, allergenicity, and cross-reactivity with human proteomes. Subsequently, the selected epitopes were joined with the help of linkers to form a robust vaccine construct. In addition, an adjuvant was applied to the N-terminal of the construct to improve the immunogenicity of the vaccine. The physicochemical properties, solubility, the secondary and tertiary structure of the final vaccine were also established. MD simulations for 100 ns were employed to assess the stability of the vaccine-TLR-2 docked complex. The final vaccine was optimized and cloned in pET28a (+) vector with His-tag to achieve maximum vaccine protein expression for ease of purification. Immune simulation results indicated the potency of this vaccine candidate as a probable therapeutic agent. In conclusion, the overall results of various immunoinformatics tools and methods employed revealed that the constructed multi-epitope vaccine exhibits a high potential for stimulating both B and T-cells immune responses against pneumonia infection. However, experimental immunological studies are required to corroborate the viability of the novel multi-epitope construct as a commercial vaccine.

B and T cell epitope-based peptides predicted from clumping factor protein of Staphylococcus aureus as vaccine targets.

Staphylococcus aureus infection is emerging as a global threat because of the highly debilitating nature of the associated disease's unprecedented magnitude of its spread and growing global resistance to antimicrobial medicines. Recently WHO has categorized these bacteria under the high global priority pathogen list and is one of the six nosocomial pathogens termed as ESKAPE pathogens which have emerged as a serious threat to public health worldwide. The development of a specific vaccine can stimulate an optimal antibody response, thus providing immunity against it. Therefore, in the present study efforts have been made to identify potential vaccine candidates from the Clumping factor surface proteins (ClfA and ClfB) of S. aureus. Employing the immunoinformatics approach, fourteen antigenic peptides including T-cell, B-cell epitopes were identified which were non-toxic, non-allergenic, high antigenicity, strong binding efficiency with commonly occurring MHC alleles. Consequently, a multi-epitope vaccine chimera was designed by connecting these epitopes with suitable linkers an adjuvant to enhance immunogenicity. Further, homology modeling and molecular docking were performed to construct the three-dimensional structure of the vaccine and study the interaction between the modeled structure and immune receptor (TLR-2) present on lymphocyte cells. Consequently, molecular dynamics simulation for 100 ns period confirmed the stability of the interaction and reliability of the structure for further analysis. Finally, codon optimization and in silico cloning were employed to ensure the successful expression of the vaccine candidate. As the targeted protein is highly antigenic and conserved, hence the designed novel vaccine construct holds potential against emerging multi-drug-resistant organisms.

DBCOVP: A database of coronavirus virulent glycoproteins.

Since the emergence of SARS-CoV-1 (2002), novel coronaviruses have emerged periodically like the MERS- CoV (2012) and now, the SARS-CoV-2 outbreak which has posed a global threat to public health. Although, this is the third zoonotic coronavirus breakout within the last two decades, there are only a few platforms that provide information about coronavirus genomes. None of them is specific for the virulence glycoproteins and complete sequence-structural features of these virulence factors across the betacoronavirus family including SARS-CoV-2 strains are lacking. Against this backdrop, we present DBCOVP (http://covp.immt.res.in/), the first manually-curated, web-based resource to provide extensive information on the complete repertoire of structural virulent glycoproteins from coronavirus genomes belonging to betacoronavirus genera. The database provides various sequence-structural properties in which users can browse and analyze information in different ways. Furthermore, many conserved T-cell and B-cell epitopes predicted for each protein are present that may perform a significant role in eliciting the humoral and cellular immune response. The tertiary structure of the epitopes together with the docked epitope-HLA binding-complex is made available to facilitate further analysis. DBCOVP presents an easy-to-use interface with in-built tools for similarity search, cross-genome comparison, phylogenetic, and multiple sequence alignment. DBCOVP will certainly be an important resource for experimental biologists engaged in coronavirus research studies and will aid in vaccine development.

Designing an efficient multi-epitope vaccine displaying interactions with diverse HLA molecules for an efficient humoral and cellular immune response to prevent COVID-19 infection.

BACKGROUND: The novel SARS-CoV-2 coronavirus, the causative agent of the ongoing pandemic COVID-19 disease continues to infect people globally and has infected millions of humans worldwide. However, no effective vaccine against this virus exists. METHOD: Using Immunoinformatics, epitopic sequences from multiple glycoproteins that play crucial role in pathogenesis were identified. Particularly, epitopes were mapped from conserved receptor-binding domain of spike protein which have been experimentally validated in SARS-CoV-1 as a promising target for vaccine development. RESULTS: A multi-epitopic vaccine construct comprising of B-cell, CTL, HTL epitopes was developed along with fusion of adjuvant and linkers. The epitopes identified herein are reported for the first time and were predicted to be highly antigenic, stable, nonallergen, nontoxic and displayed conservation across several SARS-CoV-2 isolates from different countries. Additionally, the epitopes associated with maximum HLA alleles and population coverage analysis shows the proposed epitopes would be a relevant representative of large proportion of the world population. A reliable three-dimensional structure of the vaccine construct was developed. Consequently, docking and molecular-dynamics simulation ensured the stable interaction between vaccine and innate-immune receptor.

dEMBF v2.0: An Updated Database of Enzymes for Microalgal Biofuel Feedstock.

In light of increasing algal genomics data and knowledge of biosynthetic pathways responsible for biofuel production, an integrated resource for easy access to all information is essential to improve our understanding of algal lipid metabolism. Against this backdrop, dEMBF v2.0, a significantly updated and improved version of our database of microalgae lipid biosynthetic enzymes for biofuel production, has been developed. dEMBF v2.0 now contains a comprehensive annotation of 2018 sequences encoding 35 enzymes, an increase of over 7-fold as compared with the first version. Other improved features include an increase in species coverage to 32 algal genomes, analysis of additional metabolic pathways, expanded annotation thoroughly detailing sequence and structural features, including enzyme-ligand interactions, and integration of supporting experimental evidence to demonstrate the role of enzymes in increasing lipid content. Along with a complete redesign of the interface, the updated database provides several inbuilt tools and user-friendly functionalities for more interactive and dynamic visualization of data.