Subtractive proteomics and immunoinformatics revealed novel B-cell derived T-cell epitopes against Yersinia enterocolitica: An etiological agent of Yersiniosis

Immunoinformatic approach for designing a multi-epitope vaccine against non-typhoidal salmonellosis using starvation-stress response proteins from Salmonella Oranienburg

Non-typhoidal Salmonella is responsible for gastrointestinal illnesses worldwide. Therefore, it is important to implement effective therapeutic interventions for preventing these diseases. Vaccines have proven highly efficacious in the treatment and prevention of several illnesses. Nevertheless, there is currently no authorized vaccine available for non-typhoidal salmonellosis. This study aimed to employ in silico techniques to develop a multi-epitope vaccine targeting non-typhoidal salmonellosis. Specifically, we focused on proteins associated with the starvation stress response (SSR) in Salmonella Oranienburg. The presence of these proteins is essential for the survival and disease of the host organism. The vaccine sequence was constructed utilizing B-cell and T-cell epitopes. Linkers, adjuvants and PADRE sequences were used to establish connections between epitopes. The vaccine exhibited no allergenicity, toxigenicity and a significantly high antigenicity score. Docking analysis conducted between the designed vaccine and the TLR-1, TLR-2 and TLR-4 receptors demonstrated favorable interactions and the potential to activate these receptors. In addition, it was found through immunological simulation testing that the vaccine elicits a robust immune response. The use of these proteins in the construction of a multi-epitope vaccine shows potential in terms of both safety and immunogenicity.

Identification of promising inhibitors against breast cancer disease by targeting NUDIX hydrolase 5 (NUDT5) biomolecule

It is well documented that NUDT5 enzyme inhibition in breast cancer cell lines arrest cancer cells growth, invasiveness and migration. The NUDT5 enzyme enhances breast cancer aggressiveness and act as key regulator of oncogenic pathways. Similarly, the NUDT5 enzyme plays a primer role in ATP-dependent cellular processes and proliferation in breast cancer. Thus, the NUDT5 enzyme plays a profound contribution in promoting breast cancers carcinogenesis and could be an ideal target for anti-cancer drug discovery. In this work, LAS_51382001, LAS_51177972 and LAS_51380924 with binding energy of -12.64 kcal/mol, -11.59 kcal/mol and -10.01 kcal/mol, respectively were filtered as lead molecules. The control molecule binding energy was -10.87 kcal/mol. The system dynamics were found uniform in molecular dynamics simulation studies and observed with no major structural changes. Among the leads, the LAS_51177972 showed the most stable binding energy values. The MM-GBSA binding energy of the compound was -37.07 kcal/mol and MM-PBSA binding energy of -43.56 kcal/mol. Similarly, the compound revealed very stable WaterSwap absolute binding energy values; Bennett's, TI and FEP energy of -36.2 kcal/mol, -36.13 kcal/mol and -36.58 kcal/mol, respectively. Similarly, the leads reported very favorable physicochemical properties, water solubility, pharmacokinetics, druglikeness and medicinal chemistry properties. In a nutshell, the compounds are potent in term of the current computational study however, need to be subjected to experimental studies.Communicated by Ramaswamy H. Sarma.

Integrated structural proteomics and machine learning-guided mapping of a highly protective precision vaccine against mycoplasma pulmonis

Mycoplasma pulmonis (M. pulmonis) is an emerging respiratory infection commonly linked to prostate cancer, and it is classified under the group of mycoplasmas. Improved management of mycoplasma infections is essential due to the frequent ineffectiveness of current antibiotic treatments in completely eliminating these pathogens from the host. The objective of this study is to design and construct effective and protective vaccines guided by structural proteomics and machine learning algorithms to provide protection against the M. pulmonis infection. Through a thorough examination of the entire proteome of M. pulmonis, four specific targets Membrane protein P80, Lipoprotein, Uncharacterized protein and GGDEF domain-containing protein have been identified as appropriate for designing a vaccine. The proteins underwent mapping of cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL) (IFN)-γ ±, and B-cell epitopes using artificial and recurrent neural networks. The design involved the creation of mRNA and peptide-based vaccine, which consisted of 8 CTL epitopes associated by GGS linkers, 7 HTL (IFN-positive) epitopes, and 8 B-cell epitopes joined by GPGPG linkers. The vaccine designed exhibit antigenic behavior, non-allergenic qualities, and exceptional physicochemical attributes. Structural modeling revealed that correct folding is crucial for optimal functioning. The coupling of the MEVC and Toll-like Receptors (TLR)1, TLR2, and TLR6 was examined through molecular docking experiments. This was followed by molecular simulation investigations, which included binding free energy estimations. The results indicated that the dynamics of the interaction were stable, and the binding was strong. In silico cloning and optimization analysis revealed an optimized sequence with a GC content of 49.776 % and a CAI of 0.982. The immunological simulation results showed strong immune responses, with elevated levels of active and plasma B-cells, regulatory T-cells, HTL, and CTL in both IgM+IgG and secondary immune responses. The antigen was completely cleared by the 50th day. This study lays the foundation for creating a potent and secure vaccine candidate to combat the newly identified M. pulmonis infection in people.

Immunoinformatic approach for multi-epitope vaccine design against Staphylococcus aureus based on hemolysin proteins

Staphylococcus aureus is a common bacterium that causes a variety of infections in humans. This microorganism produces several virulence factors, including hemolysins, which contribute to its disease-causing ability. The treatment of S. aureus infections typically involves the use of antibiotics. However, the emergence of antibiotic-resistant strains has become a major concern. Therefore, vaccination against S. aureus has gained attention as an alternative approach. Vaccination has the advantage of stimulating the immune system to produce specific antibodies that can neutralize bacteria and prevent infection. However, developing an effective vaccine against S. aureus has proven to be challenging. This study aimed to use in silico methods to design a multi-epitope vaccine against S. aureus infection based on hemolysin proteins. The designed vaccine contained four B-cell epitopes, four CTL epitopes, and four HTL epitopes, as well as the ribosomal protein L7/L12 and pan-HLA DR-binding epitope, included as adjuvants. Furthermore, the vaccine was non-allergenic and non-toxic with the potential to stimulate the TLR2-, TLR-4, and TLR-6 receptors. The predicted vaccine exhibited a high degree of antigenicity and stability, suggesting potential for further development as a viable vaccine candidate. The population coverage of the vaccine was 94.4 %, indicating potential widespread protection against S. aureus. Overall, these findings provide valuable insights into the design of an effective multi-epitope vaccine against S. aureus infection and pave the way for future experimental validations.

Subtractive proteomics-guided vaccine targets identification and designing of multi-epitopes vaccine for immune response instigation against Burkholderia pseudomallei

In this study, a methodical workflow using subtractive proteomics, vaccine designing, molecular simulation, and agent-based modeling approaches were used to annotate the whole proteome of Burkholderia pseudomallei (strain K96243) for vaccine designing. Among the total 5717 proteins in the whole proteome, 505 were observed to be essential for the pathogen's survival and pathogenesis predicted by the Database of Essential Genes. Among these, 23 vaccine targets were identified, of which fimbrial assembly chaperone (Q63UH5), Outer membrane protein (Q63UH1), and Hemolysin-like protein (Q63UE4) were selected for the subsequent analysis based on the systematic approaches. Using immunoinformatic approaches CTL (cytotoxic T lymphocytes), HTL (helper T lymphocytes), IFN-positive, and B cell epitopes were predicted for these targets. A total of 9 CTL epitopes were added using the GSS linker, 6 HTL epitopes using the GPGPG linker, and 6 B cell epitopes using the KK linker. An adjuvant was added for enhanced antigenicity, an HIV-TAT peptide for improved delivery, and a PADRE sequence was added to form a 466 amino acids long vaccine construct. The construct was classified as non-allergenic, highly antigenic, and experimentally feasible. Molecular docking results validated the robust interaction of MEVC with immune receptors such as TLR2/4. Furthermore, molecular simulation revealed stable dynamics and compact nature of the complexes. The binding free energy results further validated the robust binding. In silico cloning, results revealed GC contents of 50.73 % and a CIA value of 0.978 which shows proper downstream processing. Immune simulation results reported that after the three injections of the vaccine a robust secondary immune response, improved antigen clearance, and effective immune memory generation were observed highlighting its potential for effective and sustained immunity. Future directions should encompass experimental validations, animal model studies, and clinical trials to substantiate the vaccine's efficacy, safety, and immunogenicity.

Recombinant YopE and LcrV vaccine candidates protect mice against plague and yersiniosis

No licensed vaccine exists for the lethal plague and yersiniosis. Therefore, a combination of recombinant YopE and LcrV antigens of Yersinia pestis was evaluated for its vaccine potential in a mouse model. YopE and LcrV in formulation with alum imparted a robust humoral immune response, with isotyping profiles leaning towards the IgG1 and IgG2b subclasses. It was also observed that a significantly enhanced expression of IFN-γ, TNF-α, IL-6, IL-2, and IL-1β from the splenic cells of vaccinated mice, as well as YopE and LcrV-explicit IFN-γ eliciting T-cells. The cocktail of YopE + LcrV formulation conferred complete protection against 100 LD50Y. pestis infection, while individually, LcrV and YopE provided 80 % and 60 % protection, respectively. Similarly, the YopE + LcrV vaccinated animal group had significantly lower colony forming unit (CFU) counts in the spleen and blood compared to the groups administered with YopE or LcrV alone when challenged with Yersinia pseudotuberculosis and Yersinia enterocolitica. Histopathologic evidence reinforces these results, indicating the YopE + LcrV formulation provided superior protection against acute lung injury as early as day 3 post-challenge. In conclusion, the alum-adjuvanted YopE + LcrV is a promising vaccine formulation, eliciting a robust antibody response including a milieu of pro-inflammatory cytokines and T-cell effector functions that contribute to the protective immunity against Yersinia infections. YopE and LcrV, conserved across all three human-pathogenic Yersinia species, provide cross-protection. Therefore, our current vaccine (YopE + LcrV) targets all three pathogens: Y. pestis, Y. pseudotuberculosis, and Y. enterocolitica. However, the efficacy should be tested in other higher mammalian models.

Discovering Potential Bacteriocins Against Pseudomonas fragi: a Subtractive Proteomics and Molecular Dynamic Simulation Study for Food Preservation

Food preservation is a schematic and scientific procedure employed for the maintenance and improvement of food's quality, shelf life, and nutritional value. Although, on one hand, ancient conventional methods such as freezing, pasteurization, canning, and chemical methods have the potential to lengthen the shelf life of edible substances, but on the other hand, they can deteriorate its nutritional value as well. Present research focuses on the identification of promising bacteriocins against Pseudomonas fragi via subtractive proteomics pipeline as an alternative approach for food preservation. Bacteriocins are small peptides produced by certain microbes to naturally defend themselves by destroying other closely related bacteria residing in their neighborhood. P. fragi lies among the most notable microbes responsible for the elicitation of food spoilage. Due to increasing emergence and prevalence of multidrug resistance bacteria, there is a need to unravel novel drug targets, crucially involved in food decay process. Based on subtractive scrutinization, UDP-N-acetylglucosamine O-acyltransferase (LpxA) was chosen as promising therapeutic protein target that could play a significant role in progression of food spoilage. Subtilosin A, thuricin-CD, and mutacin B-NY266 were found as the most robust inhibitors of LpxA according to the molecular docking assay results. Molecular dynamic simulations and binding energy calculations via MM/PBSA method of LpxA and three top hit docked complexes, i.e., LpxA-subtilosin A, LpxA-thuricin-CD, and LpxA-mutacin B-NY266, revealed stability throughout simulations and ensured that shortlisted bacteriocins had strong affinity for LpxA.

Targeted vaccine development against Bilophila wadsworthia to curb colon diseases: A multiepitope approach based on reverse vaccinology and computational analysis

The presence of excessive hydrogen sulfide (H2S)-producing bacteria, particularly Bilophila wadsworthia in appendices, is linked to a weaker colonic mucus barrier, inflammatory bowel disease, and colorectal cancer. Thus, targeting this bacterium could reduce sulfide levels and address associated health concerns. Here, we utilized reverse vaccinology and immunoinformatics to design a chimeric vaccine against B. wadsworthia, focusing on membrane-bound and extracellular proteins. Subtractive proteome analysis identified 18 potential vaccine candidates (PVCs), from which six B-cell, eight CD8+ T cell, and six CD4+ T cell epitopes were predicted. Chosen epitopes were assessed for immunological properties and cross-reactivity with human and mouse proteomes. Subsequently, these epitopes were fused with appropriate linkers, PADRE epitope, TAT peptide, and Cholera Toxin B subunit adjuvant to form a robust multi-epitope vaccine (MEV). The MEV's tertiary structure was modelled and validated for reliable analysis. Molecular docking and dynamics simulations demonstrated stable binding of MEV with Toll-like receptor 4. The MEV showed favorable physicochemical characteristics, high expression potential in Escherichia coli, broad population coverage (∼98 %), and cross-protection against different B. wadsworthia strains. Immune simulation suggested induction of strong B and T cell responses, including primary, secondary, and tertiary immune responses. Further experimental studies are necessary to validate these findings.

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.

Identification of a Potential Vaccine against Treponema pallidum Using Subtractive Proteomics and Reverse-Vaccinology Approaches

Syphilis, a sexually transmitted infection, is a deadly disease caused by Treponema pallidum. It is a Gram-negative spirochete that can infect nearly every organ of the human body. It can be transmitted both sexually and perinatally. Since syphilis is the second most fatal sexually transmitted disease after AIDS, an efficient vaccine candidate is needed to establish long-term protection against infections by T. pallidum. This study used reverse-vaccinology-based immunoinformatic pathway subtractive proteomics to find the best antigenic proteins for multi-epitope vaccine production. Six essential virulent and antigenic proteins were identified, including the membrane lipoprotein TpN32 (UniProt ID: O07950), DNA translocase FtsK (UniProt ID: O83964), Protein Soj homolog (UniProt ID: O83296), site-determining protein (UniProt ID: F7IVD2), ABC transporter, ATP-binding protein (UniProt ID: O83930), and Sugar ABC superfamily ATP-binding cassette transporter, ABC protein (UniProt ID: O83782). We found that the multiepitope subunit vaccine consisting of 4 CTL, 4 HTL, and 11 B-cell epitopes mixed with the adjuvant TLR-2 agonist ESAT6 has potent antigenic characteristics and does not induce an allergic response. Before being docked at Toll-like receptors 2 and 4, the developed vaccine was modeled, improved, and validated. Docking studies revealed significant binding interactions, whereas molecular dynamics simulations demonstrated its stability. Furthermore, the immune system simulation indicated significant and long-lasting immunological responses. The vaccine was then reverse-transcribed into a DNA sequence and cloned into the pET28a (+) vector to validate translational activity as well as the microbial production process. The vaccine developed in this study requires further scientific consensus before it can be used against T. pallidum to confirm its safety and efficacy.

Immunoinformatics-Based Proteome Mining to Develop a Next-Generation Vaccine Design against Borrelia burgdorferi: The Cause of Lyme Borreliosis

The tick-borne bacterium, Borrelia burgdorferi has been implicated in Lyme disease-a deadly infection, formerly confined to North America, but currently widespread across Europe and Asia. Despite the severity of this disease, there is still no human Lyme disease vaccine available. A reliable immunoinformatic approach is urgently needed for designing a therapeutic vaccine against this Gram-negative pathogen. Through this research, we explored the immunodominant proteins of B. burgdorferi and developed a novel and reliable vaccine design with great immunological predictability as well as low contamination and autoimmunity risks. Our initial analysis involved proteome-wide analysis to filter out proteins on the basis of their redundancy, homology to humans, virulence, immunogenicity, and size. Following the selection of proteins, immunoinformatic tools were employed to identify MHC class I & II epitopes and B-cell epitopes, which were subsequently subjected to a rigorous screening procedure. In the final formulation, ten common MHC-I and II epitopes were used together with a suitable adjuvant. We predicted that the final chimeric multi-epitope vaccine could invoke B-cell responses and IFN-gamma-mediated immunity as well as being stable and non-allergenic. The dynamics simulations predicted the stable folding of the designed molecule, after which the molecular docking predicted the stability of the interaction between the potential antigenic epitopes and human immune receptors. Our studies have shown that the designed next-generation vaccine stimulates desirable immune responses, thus potentially providing a viable way to prevent Lyme disease. Nevertheless, further experimental studies in a wet lab are needed in order to validate the results.

Computational Design of a Multi-Epitope Vaccine Against Porphyromonas gingivalis

Porphyromonas gingivalis is a Gram-negative pathogenic bacterium associated with chronic periodontitis. The development of a chimeric peptide-based vaccine targeting this pathogen could be highly beneficial in preventing oral bone loss as well as other severe gum diseases. We applied a computational framework to design a multi-epitope-based vaccine candidate against P. gingivalis. The vaccine comprises epitopes from subunit proteins prioritized from the P. gingivalis reference strain (P. gingivalis ATCC 33277) using several reported vaccine properties. Protein-based subunit vaccines were prioritized through genomics techniques. Epitope prediction was performed using immunoinformatic servers and tools. Molecular modeling approaches were used to build a putative three-dimensional structure of the vaccine to understand its interactions with host immune cells through biophysical techniques such as molecular docking simulation studies and binding free energy methods. Genome subtraction identified 18 vaccine targets: six outer-membrane, nine cytoplasmic membrane-, one periplasmic, and two extracellular proteins. These proteins passed different vaccine checks required for the successful development of a vaccine candidate. The shortlisted proteins were subjected to immunoinformatic analysis to map B-cell derived T-cell epitopes, and antigenic, water-soluble, non-toxic, and good binders of DRB1*0101 were selected. The epitopes were then modeled into a multi-epitope peptide vaccine construct (linked epitopes plus adjuvant) to enhance immunogenicity and effectively engage both innate and adaptive immunity. Further, the molecular docking approach was used to determine the binding conformation of the vaccine to TLR2 innate immune receptor. Molecular dynamics simulations and binding free energy calculations of the vaccine-TLR2 complex were performed to highlight key intermolecular binding energies. Findings of this study will be useful for vaccine developers to design an effective vaccine for chronic periodontitis pathogens, specifically P. gingivalis.

Designing a Multi-Epitope Vaccine against Chlamydia trachomatis by Employing Integrated Core Proteomics, Immuno-Informatics and In Silico Approaches

Chlamydia trachomatis, a Gram-negative bacterium that infects the rectum, urethra, congenital sites, and columnar epithelium of the cervix. It is a major cause of preventable blindness, ectopic pregnancy, and bacterial sexually transmitted infections worldwide. There is currently no licensed multi-epitope vaccination available for this pathogen. This study used core proteomics, immuno-informatics, and subtractive proteomics approaches to identify the best antigenic candidates for the development of a multi-epitope-based vaccine (MEBV). These approaches resulted in six vaccine candidates: Type III secretion system translocon subunit CopD2, SctW family type III secretion system gatekeeper subunit CopN, SycD/LcrH family type III secretion system chaperone Scc2, CT847 family type III secretion system effector, hypothetical protein CTDEC_0668, and CHLPN 76kDa-like protein. A variety of immuno-informatics tools were used to predict B and T cell epitopes from vaccine candidate proteins. An in silico vaccine was developed using carefully selected epitopes (11 CTL, 2 HTL & 10 LBL) and then docked with the MHC molecules (MHC I & MHC II) and human TLR4. The vaccine was coupled with Cholera toxin subunit B (CTB) adjuvant to boost the immune response. Molecular dynamics (MD) simulations, molecular docking, and MMGBSA analysis were carried out to analyze the molecular interactions and binding affinity of MEBV with TLR4 and MHC molecules. To achieve the highest level of vaccine protein expression, the MEBV was cloned and reverse-translated in Escherichia coli. The highest level of expression was achieved, and a CAI score of 0.97 was reported. Further experimental validation of the MEBV is required to prove its efficacy. The vaccine developed will be useful in preventing infections caused by C. trachomatis.

Subtractive Proteomics and Immuno-informatics Approaches for Multi-peptide Vaccine Prediction Against Klebsiella oxytoca and Validation Through In Silico Expression

Klebsiella oxytoca is a gram-negative bacterium. It is opportunistic in nature and causes hospital acquired infections. Subtractive proteomics and reverse vaccinology approaches were employed to screen out the best proteins for vaccine designing. Whole proteome of K. oxytoca strain ATCC 8724, consisting of 5483 proteins, was used for designing the vaccine. Total 1670 cytotoxic T lymphocyte (CTL) epitope were predicted through NetCTL while 1270 helper T lymphocyte (HTL) epitopes were predicted through IEDB server. The epitopes were screened for non-toxicity, allergenicity, antigenicity and water solubility. After epitope screening 300 CTL and 250 HTL epitopes were submitted to IFN-γ epitope server to predict their Interferon-γ induction response. The selected IFN-γ positive epitopes were tested for their binding affinity with MHCI-DRB1 by MHCPred. The 15 CTL and 13 HTL epitopes were joined by linkers AAY and GPGPG respectively in vaccine construct. Chain C of Pam3CSK4 (PDB ID; 2Z7X) was linked to the vaccine construct as an adjuvant. A 450aa long vaccine construct was submitted to I-TASSER server for 3D structure prediction. Thirteen Linear B cells were predicted by ABCPred server and 10 sets of discontinues epitopes for 3D vaccine structure were predicted by DiscoTope server. The modeled 3D vaccine construct was docked with human Toll-like receptor 2 (PDB ID: 6NIG) by PatchDock. The docked complexes were refined by FireDock. The selected docked complex showed five hydrogen bonds and one salt bridge. The vaccine sequence was reverse transcribed to get nucleotide sequence for In silico cloning. The reverse transcribed sequence strand was cloned in pET28a(+) expression vector. A clone containing 6586 bp was constructed including the 450 bp of query gene sequence.

Integrated Multi-omics, Virtual Screening and Molecular Docking Analysis of Methicillin-Resistant Staphylococcus aureus USA300 for the Identification of Potential Therapeutic Targets: An In-Silico Approach

Staphylococcus aureus infection is a leading cause of mortality and morbidity in community, hospital and live-stock sectors, especially with the widespread emergence of methicillin-resistant S. aureus (MRSA) strains. To identify new drug molecules to treat MRSA patients, we have undertaken to search essential proteins that are indispensable for their survival but non-homologous to human host proteins. The current study utilizes a subtractive genome and proteome approach to screen the possible therapeutic targets against S. aureus USA300. Bacterial essential genes are obtained from the DEG database and are compared to avoid cross-reactivity with human host genes. In silico analysis shows 198 proteins that may be considered as therapeutic candidates. Depending on their sub-cellular localization, proteins are grouped as either vaccine or drug targets or both. Extracellular proteins such as cell division proteins (Q2FZ91, Q2FZ95), penicillin-binding proteins (Q2FZ94, Q2FYI0) of the bacterial cell wall, phosphoglucomutase (Q2FE11) and lipoteichoic acid synthase (Q2FIS2) are considered as vaccine targets, and their epitopes have been mapped. Altogether, 53 drug targets are identified, which have shown similarity with the drug targets available in the DrugBank database. Predicted drug targets belong to the common metabolic pathways of MRSA, such as fatty acid biosynthesis, folate biosynthesis, peptidoglycan biosynthesis, ribosome, etc. Protein-protein interaction analysis emphasizing peptidoglycan biosynthesis reveals the connection between penicillin-binding proteins, mur-family proteins and FemXAB proteins. In this study, staphylococcal FemA protein (P0A0A5) is subjected to structure-based virtual screening for the drug repurposing approach. There are 20 residues missing in the crystal structure of FemA, and 12 of these residues are located at the catalytic site. The missing residues are modelled, and stereochemistry is checked. FDA approved drugs available in the DrugBank database have been used in virtual screening with FemA in search of potential repurposed molecules. This approach provides us with 10 drugs that may be used in the treatment of methicillin-resistant staphylococcal mediated diseases. AutoDock 4.2 is used for in silico screening and shows a comparable inhibition constant (Ki) for all 10 FDA-approved drugs towards FemA. Most of these drugs are used in the treatment of various cancers, migraines and leukaemia. Protein-drug interaction analysis shows that the drugs mostly interact with hydrophobic residues of FemA. Moreover, Tyr328 and Lys383 contribute largely to hydrogen bondings during interactions. All interacting amino acids that bind to the drugs are part of the active site cavity of FemA.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10989-021-10287-9.

Prioritization of potential vaccine candidates and designing a multiepitope-based subunit vaccine against multidrug-resistant Salmonella Typhi str. CT18: A subtractive proteomics and immunoinformatics approach

Salmonella enterica serovar Typhi (S. Typhi), a causative agent of typhoid fever, is a Gram-negative, human-restricted pathogen that causes significant morbidity and mortality, particularly in developing countries. The currently available typhoid vaccines are not recommended to children below six years of age and have poor long-term efficacy. Due to these limitations and the emerging threat of multidrug-resistance (MDR) strains, the development of a new vaccine is urgently needed. The present study aims to design a multiepitope-based subunit vaccine (MESV) against MDR S. Typhi str. CT18 using a computational-based approach comprising subtractive proteomics and immunoinformatics. Firstly, we investigated the proteome of S. Typhi str. CT18 using subtractive proteomics and identified twelve essential, virulent, host non-homologous, and antigenic outer membrane proteins (OMPs) as potential vaccine candidates with low transmembrane helices (≤1) and molecular weight (≤110 kDa). The OMPs were mapped for cytotoxic T lymphocyte(CTL) epitopes, helper T lymphocyte (HTL) epitopes, and linear B lymphocyte (LBL) epitopes using various immunoinformatics tools and servers. A total of 6, 12, and 11 CTL, HTL, and LBL epitopes were shortlisted, respectively, based on their immunogenicity, antigenicity, allergenicity, toxicity, and hydropathicity potential. Four MESV constructs (MESVCs), MESVC-1, MESVC-2, MESVC-3, and MESVC-4, were designed by linking the CTL, HTL, and LBL epitopes with immune-modulating adjuvants, linkers, and PADRE (Pan HLA DR-binding epitope) sequences. The MESVCs were evaluated for their physicochemical properties, allergenicity, antigenicity, toxicity, and solubility potential to ensure their safety and immunogenic behavior. Secondary and tertiary structures of shortlisted MESVCs (MESVC-1, MESVC-3, and MESVC-4) were predicted, modeled, refined, validated, and then docked with various MHC I, MHC II, and TLR4/MD2 complex. Molecular dynamics (MD) simulation of the final selected MESVC-4 with TLR4/MD2 complex confirms its binding affinity and stability. Codon optimization and in silico cloning verified the translation efficiency and successful expression of MESVC-4 in E. coli str. K12. Finally, the efficiency of MESVC-4 to trigger an effective immune response was assessed by an in silico immune simulation. In conclusion, our findings show that the designed MESVC-4 can elicit humoral and cellular immune responses, implying that it may be used for prophylactic or therapeutic purposes. Therefore, it should be subjected to further experimental validations.

Integrated Core Proteomics, Subtractive Proteomics, and Immunoinformatics Investigation to Unveil a Potential Multi-Epitope Vaccine against Schistosomiasis

Schistosomiasis is a parasitic infection that causes considerable morbidity and mortality in the world. Infections of parasitic blood flukes, known as schistosomes, cause the disease. No vaccine is available yet and thus there is a need to design an effective vaccine against schistosomiasis. Schistosoma japonicum, Schistosoma mansoni, and Schistosoma haematobium are the main pathogenic species that infect humans. In this research, core proteomics was combined with a subtractive proteomics pipeline to identify suitable antigenic proteins for the construction of a multi-epitope vaccine (MEV) against human-infecting Schistosoma species. The pipeline revealed two antigenic proteins-calcium binding and mycosubtilin synthase subunit C-as promising vaccine targets. T and B cell epitopes from the targeted proteins were predicted using multiple bioinformatics and immunoinformatics databases. Seven cytotoxic T cell lymphocytes (CTL), three helper T cell lymphocytes (HTL), and four linear B cell lymphocytes (LBL) epitopes were fused with a suitable adjuvant and linkers to design a 217 amino-acid-long MEV. The vaccine was coupled with a TLR-4 agonist (RS-09; Sequence: APPHALS) adjuvant to enhance the immune responses. The designed MEV was stable, highly antigenic, and non-allergenic to human use. Molecular docking, molecular dynamics (MD) simulations, and molecular mechanics/generalized Born surface area (MMGBSA) analysis were performed to study the binding affinity and molecular interactions of the MEV with human immune receptors (TLR2 and TLR4) and MHC molecules (MHC I and MHC II). The MEV expression capability was tested in an Escherichia coli (strain-K12) plasmid vector pET-28a(+). Findings of these computer assays proved the MEV as highly promising in establishing protective immunity against the pathogens; nevertheless, additional validation by in vivo and in vitro experiments is required to discuss its real immune-protective efficacy.

Genome-wide screening of vaccine targets prioritization and reverse vaccinology aided design of peptides vaccine to enforce humoral immune response against Campylobacter jejuni

Campylobacter jejuni, gram-negative bacteria, is an infectious agent of foodborne disease-causing bloody diarrhea, abdominal pain, fever, Guillain-Barré syndrome (GBS) and Miller Fisher syndrome in humans. Campylobacter spp. with multidrug resistance to fluoroquinolones, tetracycline, and erythromycin are reported. Hence, an effective vaccine candidate would provide long-term immunity against C. jejuni infections. Thus, we used a subtractive proteomics pipeline to prioritize essential proteins, which impart a critical role in virulence, replication and survival. Five proteins, i.e. Single-stranded DNA-binding protein, UPF0324 membrane protein Cj0999c, DNA translocase FtsK, 50S ribosomal protein L22, and 50S ribosomal protein L1 were identified as virulent proteins and selected for vaccine designing. We reported that the multi-epitopes subunit vaccine based on CTL, HTL and B-cell epitopes combination possess strong antigenic properties and associates no allergenic reaction. Further investigation revealed that the vaccine interacts with the immune receptor (TLR-4) and triggered the release of primary and secondary immune factors. Moreover, the CAI and GC contents obtained through codon optimization were reported to be 0.93 and 53% that confirmed a high expression in the selected vector. The vaccine designed in this study needs further scientific consensus and will aid in managing C. jejuni infections.

Designing multi-epitope vaccine against Staphylococcus aureus by employing subtractive proteomics, reverse vaccinology and immuno-informatics approaches

Staphylococcus aureus is a deadly human bacterial pathogen that causes a wide variety of clinical manifestations. Invasive S. aureus infections in hospitals and the community are one of the main causes of mortality and morbidity, as virulent and multi-drug-resistant strains have evolved. There is an unmet and urgent clinical need for immune-based non-antibiotic approaches to treat these infections as the growing antibiotic resistance poses a significant public health danger. Subtractive proteomics assisted reverse vaccinology-based immunoinformatics pipeline was used in this study to target the suitable antigenic proteins for the development of multi-epitope vaccine (MEV). Three essential virulent and antigenic proteins were identified including Glycosyltransferase, Elastin Binding Protein, and Staphylococcal secretory antigen. A variety of immunoinformatics tools have been used to forecast T-cell and B-cell epitopes from target proteins. Seven CTL, five HTL, and eight LBL epitopes, connected through suitable linkers and adjuvant, were employed to design 444 amino acids long MEV construct. The vaccine was paired with the TLR4 agonist 50S ribosomal protein L7/L12 adjuvant to enhance the immune response towards the vaccine. The predicted MEV structure was assessed to be highly antigenic, non-toxic, non-allergenic, flexible, stable, and soluble. Molecular docking simulation of the MEV with the human TLR4 (toll-like receptor 4) and major histocompatibility complex molecules (MHCI and MHCII) was performed to validate the interactions with the receptors. Molecular dynamics (MD) simulation and MMGBSA binding free energy analyses were carried out for the stability evaluation and binding of the MEV docked complexes with TLR4, MHCI and MHCII. To achieve maximal vaccine protein expression with optimal post-translational modifications, MEV was reverse translated, its mRNA structure was analyzed, and finally in silico cloning was performed into E. coli expression host. These rigorous computational analyses supported the effectivity of proposed MEV in protection against infections associated with S. aureus. However, further experimental validations are required to fully evaluate the potential of proposed vaccine candidate.

Proteome wide vaccine targets prioritization and designing of antigenic vaccine candidate to trigger the host immune response against the Mycoplasma genitalium infection

Mycoplasma genitalium is a small size, sexually transmitted bacterial pathogen that causes urethritis in males and cervicitis in females. Being resistant to antibiotics, difficulty in diagnosis, treatment, and control of this cosmopolitan infection, vaccination is the alternating method for its effective management. Herein, this study was conducted to computationally design a multi-epitope vaccine to boost host immune responses against M. genitalium. To achieve the study aim, immunoinformatics approaches were applied to the said pathogen's proteomics sequence data. B and T cell epitopes were projected from the three shortlisted vaccine proteins; MG014, MG015, Hmw3MG317. The final vaccine ensemble comprises cytotoxic and helper T cell epitopes fused through appropriate linkers. The epitopes peptide is then liked to an adjuvant for efficient recognition and processing by the host immune system. The various physicochemical parameters such as allergenicity, antigenicity, theoretical pI, GRAVY, and molecular weight of the vaccine were checked and found safe and effective to be used in post-experimental studies. The stability and binding affinity of the vaccine with the TLR1/2 heterodimer were ensured by performing molecular docking. The best-docked complex was considered, ranked top having the lowest binding energy and strong intermolecular binding and stability. Finally, the vaccine constructs better expression was obtained by in silico cloning into the pET28a (+) vector in Escherichia coli K-12 strain, and immune simulation validated the immune response. In a nutshell, all these approaches lead to developing a multi-epitope vaccine that possessed the ability to induce cellular and antibody-mediated immune responses against the pathogen used.

Proteome-wide mapping and reverse vaccinology-based B and T cell multi-epitope subunit vaccine designing for immune response reinforcement against Porphyromonas gingivalis

Porphyromonas gingivalis, a prominent pathogen responsible for acute periodontal diseases, is widely studied by the scientific community for its successful evasion of the host immune system. P. gingivalis is associated with rheumatoid arthritis, dementia, and Alzheimer's. The pathogen successfully survives itself against the heavy load of conventional antibiotics because of its ability to evade the host immune system. Subtractive proteomics and reverse vaccinology approaches were employed in order to prioritize the best proteins for vaccine designing. Three vaccine candidates with Uniprot ID: Q7MWZ2 (histidine Kinase), Q7MVL1 (Fe (2+) transporter), and Q7MWZ2 (Capsular polysaccharide transport protein) were identified for vaccine designing. These proteins are antigenic and essential for pathogen survival. A wide range of immunoinformatics tools was applied for the prediction of epitopes, B, and T cells, for the vaccine candidate proteins. Molecular docking of the predicted epitopes against the MHC molecules were carried out. In-silico vaccine was constructed using carefully evaluated epitopes and consequently modeled for docking with human Toll-like receptor 2. Chain C of Pam3CSK4 (PDB ID; 2Z7X) was linked to the vaccine as an adjuvant to boost immune response towards the vaccine. For stability evaluation of the vaccine-TLR-2 docked complex, Molecular Dynamics simulations were performed. The reverse-translated nucleotide sequence cloned in Eschericia coli to attain the maximal expression of the vaccine protein. The maximal expression was ensured by CAI score of 0.96. The current vaccine requires future experimental validation to confirm its effectiveness. The vaccine developed will be helpful to protect against P. gingivalis associated infections.Communicated by Ramaswamy H. Sarma.

Mining the Proteome of Streptococcus mutans for Putative Drug Targets

BACKGROUND

Dental caries is the most common and one of the prevalent diseases in the world. Streptococcus mutans is one of the major oral pathogens that cause dental caries by forming a biofilm on dental tissues, degrading dental enamel and consequent cavitation in the tissue. In vitro selection of drug targets is a laborious and expensive process and therefore, computational methods are preferable for target identification at the initial stage.

OBJECTIVE

The present research aims to find new drug targets in S. mutans by using subtractive proteomics analysis, which implements various bioinformatics tools and databases.

METHODS

The proteome of S. mutans UA159 was mined for novel drug targets using computational tools and databases such as: CD-HIT, BLASTP, DEG, KAAS and CELL2GO.

RESULTS

Out of 1953 proteins of S. mutans UA159, proteins that are redundant, homologous to human and non-essential to the pathogen were eliminated. Around 178 proteins already available in drug target repositories were also eliminated. Possible functions and subcellular localization of 32 uncharacterized proteins were predicted. Substantially, 13 proteins were identified as novel drug targets in S. mutans UA159 that can be targeted by various drugs against dental caries.

CONCLUSION

This study will effectuate the development of novel therapeutic agents against dental caries and other Streptococcal infections.

A systematic strategy for the investigation of vaccines and drugs targeting bacteria

Infectious and epidemic diseases induced by bacteria have historically caused great distress to people, and have even resulted in a large number of deaths worldwide. At present, many researchers are working on the discovery of viable drug and vaccine targets for bacteria through multiple methods, including the analyses of comparative subtractive genome, core genome, replication-related proteins, transcriptomics and riboswitches, which plays a significant part in the treatment of infectious and pandemic diseases. The 3D structures of the desired target proteins, drugs and epitopes can be predicted and modeled through target analysis. Meanwhile, molecular dynamics (MD) analysis of the constructed drug/epitope-protein complexes is an important standard for testing the suitability of these screened drugs and vaccines. Currently, target discovery, target analysis and MD analysis are integrated into a systematic set of drug and vaccine analysis strategy for bacteria. We hope that this comprehensive strategy will help in the design of high-performance vaccines and drugs.