In silico approach for predicting toxicity of peptides and proteins

Design and evaluation of a multi-epitope DNA vaccine against HPV16

Cervical cancer, among the deadliest cancers affecting women globally, primarily arises from persistent infection with high-risk human papillomavirus (HPV). To effectively combat persistent infection and prevent the progression of precancerous lesions into malignancy, a therapeutic HPV vaccine is under development. This study utilized an immunoinformatics approach to predict epitopes of cytotoxic T lymphocytes (CTLs) and helper T lymphocytes (HTLs) using the E6 and E7 oncoproteins of the HPV16 strain as target antigens. Subsequently, through meticulous selection of T-cell epitopes and other necessary elements, a multi-epitope vaccine was constructed, exhibiting good immunogenic, physicochemical, and structural characteristics. Furthermore, in silico simulations showed that the vaccine not only interacted well with toll-like receptors (TLR2/TLR3/TLR4), but also induced a strong innate and adaptive immune response characterized by elevated Th1-type cytokines, such as interferon-gamma (IFN-γ) and interleukin-2 (IL2). Additionally, our study investigated the effects of different immunization intervals on immune responses, aiming to optimize a time-efficient immunization program. In animal model experiments, the vaccine exhibited robust immunogenic, therapeutic, and prophylactic effects. Administered thrice, it consistently induced the expansion of specific CD4 and CD8 T cells, resulting in substantial cytokines release and increased proliferation of memory T cell subsets in splenic cells. Overall, our findings support the potential of this multi-epitope vaccine in combating HPV16 infection and signify its candidacy for future HPV vaccine development.

Interpretable molecular encodings and representations for machine learning tasks

Molecular encodings and their usage in machine learning models have demonstrated significant breakthroughs in biomedical applications, particularly in the classification of peptides and proteins. To this end, we propose a new encoding method: Interpretable Carbon-based Array of Neighborhoods (iCAN). Designed to address machine learning models' need for more structured and less flexible input, it captures the neighborhoods of carbon atoms in a counting array and improves the utility of the resulting encodings for machine learning models. The iCAN method provides interpretable molecular encodings and representations, enabling the comparison of molecular neighborhoods, identification of repeating patterns, and visualization of relevance heat maps for a given data set. When reproducing a large biomedical peptide classification study, it outperforms its predecessor encoding. When extended to proteins, it outperforms a lead structure-based encoding on 71% of the data sets. Our method offers interpretable encodings that can be applied to all organic molecules, including exotic amino acids, cyclic peptides, and larger proteins, making it highly versatile across various domains and data sets. This work establishes a promising new direction for machine learning in peptide and protein classification in biomedicine and healthcare, potentially accelerating advances in drug discovery and disease diagnosis.

Development of multi-epitope mRNA vaccine against Clostridioides difficile using reverse vaccinology and immunoinformatics approaches

Clostridioides difficile (C. difficile), as the major pathogen of diarrhea in healthcare settings, has become increasingly prevalent within community populations, resulting in significant morbidity and mortality. However, the therapeutic options for Clostridioides difficile infection (CDI) remain limited, and as of now, no authorized vaccine is available to combat this disease. Therefore, the development of a novel vaccine against C. difficile is of paramount importance. In our study, the complete proteome sequences of 118 strains of C. difficile were downloaded and analyzed. We found four antigenic proteins that were highly conserved and can be used for epitope identification. We designed two vaccines, WLcd1 and WLcd2, that contain the ideal T-cell and B-cell epitopes, adjuvants, and the pan HLA DR-binding epitope (PADRE) sequences. The biophysical and chemical assessments of these vaccine candidates indicated that they were suitable for immunogenic applications. Molecular docking analyses revealed that WLcd1 bonded with higher affinity to Toll-like receptors (TLRs) than WLcd2. Furthermore, molecular dynamics (MD) simulations, performed using Gmx_MMPBSA v1.56, confirmed the binding stability of WLcd1 with TLR2 and TLR4. The preliminary findings suggested that this multi-epitope vaccine could be a promising candidate for protection against CDI; however, experimental studies are necessary to confirm these predictions.

Discovering peptides and computational investigations of a multiepitope vaccine target Mycobacterium tuberculosis

Mycobacterium tuberculosis (MTB) is the causative agent of tuberculosis (TB), a prevalent airborne infectious disease. Despite the availability of the Bacille Calmette-Guerin vaccine, its global efficacy remains modest, and tuberculosis persists as a significant global public health threat. Addressing this challenge and advancing towards the End MTB Strategy, we developed a multiepitope vaccine (MEV) based on immunoinformatics and computational approaches. Immunoinformatics screening of MBT protein identified immune-dominant epitopes based on Major Histocompatibility Complex (MHC) allele binding, immunogenicity, antigenicity, allergenicity, toxicity, and cytokine inducibility. Selected epitopes were integrated into an MEV construct with adjuvant and linkers, forming a fully immunogenic vaccine candidate. Comprehensive analyses encompassed the evaluation of immunological and physicochemical properties, determination of tertiary structure, molecular docking with Toll-Like Receptors (TLR), molecular dynamics (MD) simulations for all atoms, and immune simulations. Our MEV comprises 534 amino acids, featuring 6 cytotoxic T lymphocyte, 8 helper T lymphocyte, and 7 linear B lymphocyte epitopes, demonstrating high antigenicity and stability. Notably, molecular docking studies and triplicate MD simulations revealed enhanced interactions and stability of MEV with the TLR4 complex compared to TLR2. In addition, the immune simulation indicated the capacity to effectively induce elevated levels of antibodies and cytokines, emphasizing the vaccine's robust immunogenic response. This study presents a promising MEV against TB, exhibiting favorable immunological and physicochemical attributes. The findings provide theoretical support for TB vaccine development. Our study aligns with the global initiative of the End MTB Strategy, emphasizing its potential impact on addressing persistent challenges in TB control.

Integrating immunoinformatics and computational epitope prediction for a vaccine candidate against respiratory syncytial virus

Respiratory syncytial virus (RSV) poses a significant global health threat, especially affecting infants and the elderly. Addressing this, the present study proposes an innovative approach to vaccine design, utilizing immunoinformatics and computational strategies. We analyzed RSV's structural proteins across both subtypes A and B, identifying potential helper T lymphocyte, cytotoxic T lymphocyte, and linear B lymphocyte epitopes. Criteria such as antigenicity, allergenicity, toxicity, and cytokine-inducing potential were rigorously examined. Additionally, we evaluated the conservancy of these epitopes and their population coverage across various RSV strains. The comprehensive analysis identified six major histocompatibility complex class I (MHC-I) binding, five MHC-II binding, and three B-cell epitopes. These were integrated with suitable linkers and adjuvants to form the vaccine. Further, molecular docking and molecular dynamics simulations demonstrated stable interactions between the vaccine candidate and human Toll-like receptors (TLR4 and TLR5), with a notable preference for TLR4. Immune simulation analysis underscored the vaccine's potential to elicit a strong immune response. This study presents a promising RSV vaccine candidate and offers theoretical support, marking a significant advancement in vaccine development efforts. However, the promising in silico findings need to be further validated through additional in vivo studies.

Development of an ancestral DC and TLR4-inducing multi-epitope peptide vaccine against the spike protein of SARS-CoV and SARS-CoV-2 using the advanced immunoinformatics approaches

The oldest human coronavirus that started pandemics is severe acute respiratory syndrome virus (SARS-CoV). While SARS-CoV was eradicated, its new version, SARS-CoV2, caused the global pandemic of COVID-19. Evidence highlights the harmful events orchestrated by these viruses are mediated by Spike (S)P protein. Experimental epitopes of the S protein which were overlapping and ancestral between SARS-CoV and SARS-CoV-2 were obtained from the immune epitopes database (IEDB). The epitopes were then assembled in combination with a 50 S ribosomal protein L7/L12 adjuvant, a Mycobacterium tuberculosis-derived element and mediator of dendritic cells (DCs) and toll-like receptor 4 (TLR4). The immunogenic sequence was modeled by the GalaxyWeb server. After the improvement and validation of the protein structure, the physico-chemical properties and immune simulation were performed. To investigate the interaction with TLR3/4, Molecular Dynamics Simulation (MDS) was used. By merging the 17 B- and T-lymphocyte (HTL/CTL) epitopes, the vaccine sequence was created. Also, the Ramachandran plot presented that most of the residues were located in the most favorable and allowed areas. Moreover, SnapGene was successful in cloning the DNA sequence linked to our vaccine in the intended plasmid. A sequence was inserted between the XhoI and SacI position of the pET-28a (+) vector, and simulating the agarose gel revealed the existence of the inserted gene in the cloned plasmid with SARS vaccine (SARSV) construct, which has a 6565 bp in length overall. In terms of cytokines/IgG response, immunological simulation revealed a strong immune response. The stabilized vaccine showed strong interactions with TLR3/4, according to Molecular Dynamics Simulation (MDS) analysis. The present ancestral vaccine targets common sequences which seem to be valuable targets even for the new variant SARS-CoV-2.

Production, characterisation, and biological properties of Tenebrio molitor-derived oligopeptides

Three protein hydrolysates from Tenebrio molitor were obtained by enzymatic hydrolysis employing two food-grade proteases (i.e. Alcalase and Flavourzyme), and a complete characterisation of their composition was done. The digestion-derived products were obtained using the INFOGEST protocol. In vitro antioxidant activity and anti-inflammatory activities were evaluated. Tenebrio molitor flour and the protein hydrolysates showed a high ability to scavenge the DPPH radical (EC50 values from 0.30 to 0.87 mg/mL). The hydrolysate obtained with a combination of the two food-grade proteases could decrease the gene expression of pro-inflammatory genes after being digested. Furthermore, the peptidome was fully determined for the first time for T. molitor hydrolysates and digests, and 40 peptides were selected based on their bioactivity to be evaluated by in silico tools, including prediction tools and molecular docking. These results provide new perspectives on the use of edible insects as sustainable and not nutritionally disadvantageous food for human consumption.

Immunoinformatic-guided novel mRNA vaccine designing to elicit immunogenic responses against the endemic Monkeypox virus

Monkeypox virus (MPXV) is an orthopoxvirus, causing zoonotic infections in humans with smallpox-like symptoms. The WHO reported MPXV cases in May 2022 and the outbreak caused significant morbidity threats to immunocompromised individuals and children. Currently, no clinically validated therapies are available against MPXV infections. The present study is based on immunoinformatics approaches to design mRNA-based novel vaccine models against MPXV. Three proteins were prioritized based on high antigenicity, low allergenicity, and toxicity values to predict T- and B-cell epitopes. Lead T- and B-cell epitopes were used to design vaccine constructs, linked with epitope-specific linkers and adjuvant to enhance immune responses. Additional sequences, including Kozak sequence, MITD sequence, tPA sequence, Goblin 5', 3' UTRs, and a poly(A) tail were added to design stable and highly immunogenic mRNA vaccine construct. High-quality structures were predicted by molecular modeling and 3D-structural validation of the vaccine construct. Population coverage and epitope-conservancy speculated broader protection of designed vaccine model against multiple MPXV infectious strains. MPXV-V4 was eventually prioritized based on its physicochemical and immunological parameters and docking scores. Molecular dynamics and immune simulations analyses predicted significant structural stability and binding affinity of the top-ranked vaccine model with immune receptors to elicit cellular and humoral immunogenic responses against the MPXV. The pursuance of experimental and clinical follow-up of these prioritized constructs may lay the groundwork to develop safe and effective vaccine against MPXV.Communicated by Ramaswamy H. Sarma.

In-depth discovery and taste presentation mechanism studies on umami peptides derived from fermented sea bass based on peptidomics and machine learning

Umami peptides originating from fermented sea bass impart a distinctive flavor to food. Nevertheless, large-scale and rapid screening for umami peptides using conventional techniques is challenging because of problems such as prolonged duration and complicated operation. Therefore, we aimed to screen fermented sea bass using peptidomics and machine learning approaches. The taste presentation mechanism of umami peptides was assessed by molecular docking of T1R1/T1R3. Seventy umami peptides identified in fermented sea bass predominantly originated from 28 precursor proteins, including troponin, myosin, motor protein, and creatine kinase. Six umami peptides with the lowest energies formed stable complexes by binding to T1R3. SER170, SER147, GLN389, and HIS145 are critical binding sites for T1R1/T1R3. Four dominant interacting surface forces were identified: aromatic interactions, hydrogen bonding, hydrophilic bonds, and solvent-accessible surfaces. Our study unveils a method to screen umami peptides efficiently, providing a basis for further exploration of their flavor in fermented sea bass.

Super epitope dengue vaccine instigated serotype independent immune protection in-silico

Dengue becomes the most common life-threatening infectious arbovirus disease globally, with prevalence in the tropical and subtropical areas. The major clinical features include dengue haemorrhagic fever (DHF) and dengue shock syndrome (DSS), a condition of hypovolemic shock. Four different serotypes of the dengue virus, known as dengue virus serotype (DENV)- 1, 2, 3 and 4 can infect humans. Only one vaccine is available in the market, named Dengvaxia by Sanofi Pasteur, but there is no desired outcome of this treatment due the antibody dependent enhancement (ADE) of the multiple dengue serotypes. As of now, there is no cure against dengue disease. Our goal in this work was to create a subunit vaccine based on several epitopes that would be effective against every serotype of the dengue virus. Here, computational methods like- immunoinformatics and bioinformatics were implemented to find out possible dominant epitopes. A total of 21 epitopes were chosen using various in-silico techniques from the expected 133 major histocompatibility complex (MHC)- I and major histocompatibility complex (MHC)- II epitopes, along with 95 B-cell epitopes which were greatly conserved. Immune stimulant, non-allergenic and non-toxic immunodominant epitopes (super epitopes) with a suitable adjuvant (Heparin-Binding Hemagglutinin Adhesin, HBHA) were used to construct the vaccine. Following the physicochemical analysis, vaccine construct was docked with Toll-like receptors (TLRs) to predict the immune stimulation. Consequently, the optimal docked complex that demonstrated the least amount of ligand-receptor complex deformability was used to conduct the molecular dynamics analysis. By following the codon optimization, the final vaccine molecule was administered into an expressing vector to perform in-silico cloning. The robust immune responses were generated in the in-silico immune simulation analysis. Hence, this study provides a hope to control the dengue infections. For validation of the immune outcomes, in-vitro as well as in-vivo investigations are essential.

Dominant B cell-T cell epitopes instigated robust immune response in-silico against Scrub Typhus

Scrub typhus, a potentially life-threatening infectious disease, is attributed to bacteria Orientia tsutsugamushi (O. tsutsugamushi). The transmission of this illness to humans occurs through the bite of infected chiggers, which are the larval forms of mites belonging to the genus Leptotrombidium. In this research, we developed a subunit vaccine specifically designed to target outer membrane proteins. Immunodominant cytotoxic T-lymphocytes (CTLs), B- lymphocytes (BCLs), and major histocompatibility complex (MHC)- II epitopes were identified using machine learning and bioinformatics approaches. These epitopes were arranged in different combinations with the help of suitable linkers like AAY, KK, GPGPG and adjuvant (cholera toxin B) that resulted in a vaccine construct. Physiochemical properties were assessed, where the predicted solubility (0.571) was higher than threshold value. Tertiary structure was predicted using I-TASSER web server and evaluated using Ramachandran plot (94 % residues in most favourable region) and z-score (-6.04), which had shown the structure to have good stability and residue arrangement. Molecular docking with immune receptors, Toll-like receptor (TLR)-2 and -4 showed good residue interaction with 13 and 5 hydrogen bonds respectively. Molecular dynamics simulations of receptor-ligand complex provided the idea about the strong interaction having 1.524751 × 10-5 eigenvalue. Amino acid sequence of vaccine was converted to nucleotide sequence and underwent codon optimization. The optimized codon sequence was used for in-silico cloning, which provided idea about the possibility of synthesis of vaccine using E. coli as host. Overall, this study provided a promising blueprint for a scrub typhus vaccine, although experimental validation is needed for confirmation. Furthermore, it is crucial to acknowledge that while bioinformatics provides valuable insights, in-vitro and in-vivo studies are imperative for a comprehensive evaluation of vaccine candidate. Thus, the integration of computational predictions with empirical research is essential to validate the efficacy, safety, and real-world applicability of the designed vaccine against Scrub Typhus. Nevertheless, the findings are good to carry forward for in-vitro and in-vivo investigations.

Computational method for designing vaccines applied to virus-like particles (VLPs) as epitope carriers

Nonenveloped virus-like particles (VLPs) are self-assembled oligomeric structures composed of one or more proteins that originate from diverse viruses. Because these VLPs have similar antigenicity to the parental virus, they are successfully used as vaccines against cognate virus infection. Furthermore, after foreign antigenic sequences are inserted in their protein components (chimVLPs), some VLPs are also amenable to producing vaccines against pathogens other than the virus it originates from (these VLPs are named platform or epitope carrier). Designing chimVLP vaccines is challenging because the immunogenic response must be oriented against a given antigen without altering stimulant properties inherent to the VLP. An important step in this process is choosing the location of the sequence modifications because this must be performed without compromising the assembly and stability of the original VLP. Currently, many immunogenic data and computational tools can help guide the design of chimVLPs, thus reducing experimental costs and work. In this study, we analyze the structure of a novel VLP that originate from an insect virus and describe the putative regions of its three structural proteins amenable to insertion. For this purpose, we employed molecular dynamics (MD) simulations to assess chimVLP stability by comparing mutated and wild-type (WT) VLP protein trajectories. We applied this procedure to design a chimVLP that can serve as a prophylactic vaccine against the SARS-CoV-2 virus. The methodology described in this work is generally applicable for VLP-based vaccine development.

Immunoinformatics and structural aided approach to develop multi-epitope based subunit vaccine against Mycobacterium tuberculosis

Tuberculosis is a highly contagious disease caused by Mycobacterium tuberculosis (Mtb), which is one of the prominent reasons for the death of millions worldwide. The bacterium has a substantially higher mortality rate than other bacterial diseases, and the rapid rise of drug-resistant strains only makes the situation more concerning. Currently, the only licensed vaccine BCG (Bacillus Calmette-Guérin) is ineffective in preventing adult pulmonary tuberculosis prophylaxis and latent tuberculosis re-activation. Therefore, there is a pressing need to find novel and safe vaccines that provide robust immune defense and have various applications. Vaccines that combine epitopes from multiple candidate proteins have been shown to boost immunity against Mtb infection. This study applies an immunoinformatic strategy to generate an adequate multi-epitope immunization against Mtb employing five antigenic proteins. Potential B-cell, cytotoxic T lymphocyte, and helper T lymphocyte epitopes were speculated from the intended proteins and coupled with 50 s ribosomal L7/L12 adjuvant, and the vaccine was constructed. The vaccine's physicochemical profile demonstrates antigenic, soluble, and non-allergic. In the meantime, docking, molecular dynamics simulations, and essential dynamics analysis revealed that the multi-epitope vaccine structure interacted strongly with Toll-like receptors (TLR2 and TLR3). MM-PBSA analysis was performed to ascertain the system's intermolecular binding free energies accurately. The immune simulation was applied to the vaccine to forecast its immunogenic profile. Finally, in silico cloning was used to validate the vaccine's efficacy. The immunoinformatics analysis suggests the multi-epitope vaccine could induce specific immune responses, making it a potential candidate against Mtb. However, validation through the in-vivo study of the developed vaccine is essential to assess its efficacy and immunogenicity profile, which will assure active protection against Mtb.

An mRNA vaccine for pancreatic cancer designed by applying in silico immunoinformatics and reverse vaccinology approaches

Pancreatic ductal adenocarcinoma is the most prevalent pancreatic cancer, which is considered a significant global health concern. Chemotherapy and surgery are the mainstays of current pancreatic cancer treatments; however, a few cases are suitable for surgery, and most of the cases will experience recurrent episodes. Compared to DNA or peptide vaccines, mRNA vaccines for pancreatic cancer have more promise because of their delivery, enhanced immune responses, and lower proneness to mutation. We constructed an mRNA vaccine by analyzing S100 family proteins, which are all major activators of receptors for advanced glycation end products. We applied immunoinformatic approaches, including physicochemical properties analysis, structural prediction and validation, molecular docking study, in silico cloning, and immune simulations. The designed mRNA vaccine was estimated to have a molecular weight of 165023.50 Da and was highly soluble (grand average of hydropathicity of -0.440). In the structural assessment, the vaccine seemed to be a well-stable and functioning protein (Z score of -8.94). Also, the docking analysis suggested that the vaccine had a high affinity for TLR-2 and TLR-4 receptors. Additionally, the molecular mechanics with generalized Born and surface area solvation analysis of the "Vaccine-TLR-2" (-141.07 kcal/mol) and "Vaccine-TLR-4" (-271.72 kcal/mol) complexes also suggests a strong binding affinity for the receptors. Codon optimization also provided a high expression level with a GC content of 47.04% and a codon adaptation index score 1.0. The appearance of memory B-cells and T-cells was also observed over a while, with an increased level of helper T-cells and immunoglobulins (IgM and IgG). Moreover, the minimum free energy of the mRNA vaccine was predicted at -1760.00 kcal/mol, indicating the stability of the vaccine following its entry, transcription, and expression. This hypothetical vaccine offers a groundbreaking tool for future research and therapeutic development of pancreatic cancer.

Antibacterial Efficacy and Mechanisms of Action of a Novel Beta-Defensin from Snakehead Murrel, Channa striata

Beta-defensins, identified from fishes, constitute a crucial category of antimicrobial peptides important in combating bacterial fish pathogens. The present investigation centers on the molecular and functional characterization of CsDef, a 63-amino acid beta-defensin antimicrobial peptide derived from snakehead murrel (Channa striata). The physicochemical attributes of CsDef align with the distinctive characteristics observed in AMPs. CsDef was recombinantly produced, and the recombinant peptide, rCsDef, exhibited notable antibacterial efficacy against bacterial fish pathogens with an MIC of 16 μM for V. proteolyticus. A. hydrophila exhibited 91% inhibition, E. tarda 92%, and V. harveyi 53% at 32 μM of rCsDef. The rCsDef exhibited a multifaceted mechanism of action against bacteria, i.e., through membrane depolarization, membrane permeabilization, and generation of ROS. The rCsDef was non-hemolytic to hRBCs and non-cytotoxic to normal mammalian cell line CHO-K1. However, it exhibited anticancer properties in MCF-7. rCsDef demonstrated notable stability with respect to pH, temperature, salt, metal ions, and proteases. These findings suggest it is a potential candidate molecule for prospective applications in aquaculture.

An integrated comparative genomics, subtractive proteomics and immunoinformatics framework for the rational design of a Pan-Salmonella multi-epitope vaccine

Salmonella infections pose a significant global public health concern due to the substantial expenses associated with monitoring, preventing, and treating the infection. In this study, we explored the core proteome of Salmonella to design a multi-epitope vaccine through Subtractive Proteomics and immunoinformatics approaches. A total of 2395 core proteins were curated from 30 different isolates of Salmonella (strain NZ CP014051 was taken as reference). Utilizing the subtractive proteomics approach on the Salmonella core proteome, Curlin major subunit A (CsgA) was selected as the vaccine candidate. csgA is a conserved gene that is related to biofilm formation. Immunodominant B and T cell epitopes from CsgA were predicted using numerous immunoinformatics tools. T lymphocyte epitopes had adequate population coverage and their corresponding MHC alleles showed significant binding scores after peptide-protein based molecular docking. Afterward, a multi-epitope vaccine was constructed with peptide linkers and Human Beta Defensin-2 (as an adjuvant). The vaccine could be highly antigenic, non-toxic, non-allergic, and have suitable physicochemical properties. Additionally, Molecular Dynamics Simulation and Immune Simulation demonstrated that the vaccine can bind with Toll Like Receptor 4 and elicit a robust immune response. Using in vitro, in vivo, and clinical trials, our findings could yield a Pan-Salmonella vaccine that might provide protection against various Salmonella species.

Identification of novel T-cell epitopes on monkeypox virus and development of multi-epitopes vaccine using immunoinformatics approaches

Monkeypox virus (MPV) is closely related to the smallpox virus, and previous data from Africa suggest that the smallpox vaccine (VARV) is at least 85% effective in preventing MPV. No multi-epitope vaccine has yet been developed to prevent MPV infection. In this work, we used in silico structural biology and advanced immunoinformatic strategies to design a multi-epitope subunit vaccine against MPV infection. The designed vaccine sequence is adjuvanted with CpG-ODN and includes HTL/CTL epitopes for similar proteins between vaccinia virus (VACV) that induced T-cell production in vaccinated volunteers and the first draft sequence of the MPV genome associated with the suspected outbreak in several countries, May 2022. In addition, the specific binding of the modified vaccine and the immune Toll-like receptor 9 (TLR9) was estimated by molecular interaction studies. Strong interaction in the binding groove as well as good docking scores confirmed the stringency of the modified vaccine. The stability of the interaction was confirmed by a classical molecular dynamics simulation and normal mode analysis. Then, the immune simulation also indicated the ability of this vaccine to induce an effective immune response against MPV. Codon optimization and in silico cloning of the vaccine into the pET-28a (+) vector also showed its expression potential in the E. coli K12 system. The promising data obtained from the various in silico studies indicate that this vaccine is effective against MPV. However, additional in vitro and in vivo studies are still needed to confirm its efficacy.Communicated by Ramaswamy H. Sarma.

Formulation of next-generation polyvalent vaccine candidates against three important poxviruses by targeting DNA-dependent RNA polymerase using an integrated immunoinformatics and molecular modeling approach

BACKGROUND

Poxviruses comprise a group of large double-stranded DNA viruses and are known to cause diseases in humans, livestock animals, and other animal species. The Mpox virus (MPXV; formerly Monkeypox), variola virus (VARV), and volepox virus (VPXV) are among the prevalent poxviruses of the Orthopoxviridae genera. The ongoing Mpox infectious disease pandemic caused by the Mpox virus has had a major impact on public health across the globe. To date, only limited repurposed antivirals and vaccines are available for the effective treatment of Mpox and other poxviruses that cause contagious diseases.

METHODS

The present study was conducted with the primary goal of formulating multi-epitope vaccines against three evolutionary closed poxviruses i.e., MPXV, VARV, and VPXV using an integrated immunoinformatics and molecular modeling approach. DNA-dependent RNA polymerase (DdRp), a potential vaccine target of poxviruses, has been used to determine immunodominant B and T-cell epitopes followed by interactions analysis with Toll-like receptor 2 at the atomic level.

RESULTS

Three multi-epitope vaccine constructs, namely DdRp_MPXV (V1), DdRp_VARV (V2), and DdRp_VPXV (V3) were designed. These vaccine constructs were found to be antigenic, non-allergenic, non-toxic, and soluble with desired physicochemical properties. Protein-protein docking and interaction profiling analysis depicts a strong binding pattern between the targeted immune receptor TLR2 and the structural models of the designed vaccine constructs, and manifested a number of biochemical bonds (hydrogen bonds, salt bridges, and non-bonded contacts). State-of-the-art all-atoms molecular dynamics simulations revealed highly stable interactions of vaccine constructs with TLR2 at the atomic level throughout the simulations on 300 nanoseconds. Additionally, the outcome of the immune simulation analysis suggested that designed vaccines have the potential to induce protective immunity against targeted poxviruses.

CONCLUSIONS

Taken together, formulated next-generation polyvalent vaccines were found to have good efficacy against closely related poxviruses (MPXV, VARV, and VPXV) as demonstrated by our extensive immunoinformatics and molecular modeling evaluations; however, further experimental investigations are still needed.

Revealing the diversity of endogenous peptides and parent proteins in human colostrum and mature milk through peptidomics analysis

Endogenous peptides and their parent proteins are important nutritional components with diverse biological functions. The objective of this study was to analyze and compare endogenous peptides and parent proteins found in human colostrum (HC) and human mature milk (HM) using a 4D label-free technique. In total, 5162 and 940 endogenous peptides derived from 258 parent proteins were identified in human milk by database (DB) search and de novo, respectively. Among these peptides, 2446 differentially expressed endogenous peptides with various bioactivities were identified. The Gene Ontology analysis unveiled the cellular components, biological processes, and molecular functions associated with these parent proteins. Metabolic pathway analysis suggested that neutrophil extracellular trap formation had the greatest significance with 24 parent proteins. These findings will offer a fresh perspective on the development of infant formula powder, highlighting the potential for incorporating these changes to enhance its nutritional composition and benefits.

Biodegradation of PVCs through in-vitro identification of Bacillus albus and computational pathway analysis of ABH enzyme

Microplastics pose significant challenges to ecosystems and organisms. They can be ingested by marine and terrestrial species, leading to potential health risks and ecological disruptions. This study aims to address the urgent need for effective remediation strategies by focusing on the biodegradation of microplastics, specifically polyvinyl chloride (PVC) derivatives, using the bacterial strain Bacillus albus. The study provides a comprehensive background on the accumulation of noxious substances in the environment and the importance of harnessing biodegradation as an eco-friendly method for pollutant elimination. The specific objective is to investigate the enzymatic capabilities of Bacillus albus, particularly the alpha/beta hydrolases (ABH), in degrading microplastics. To achieve this, in-silico studies were conducted, including analysis of the ABH protein sequence and its interaction with potential inhibitors targeting PVC derivatives. Docking scores of - 7.2 kcal/mol were obtained to evaluate the efficacy of the interactions. The study demonstrates the promising bioremediation prospects of Bacillus albus for microplastics, highlighting its potential as a key player in addressing microplastic pollution. The findings underscore the urgent need for further experimental validation and practical implementation of Bacillus albus in environmental remediation strategies.

Integrating pan-genome and reverse vaccinology to design multi-epitope vaccine against Herpes simplex virus type-1

Herpes simplex virus type-1 (HSV-1), the etiological agent of sporadic encephalitis and recurring oral (sometimes genital) infections in humans, affects millions each year. The evolving viral genome reduces susceptibility to existing antivirals and, thus, necessitates new therapeutic strategies. Immunoinformatics strategies have shown promise in designing novel vaccine candidates in the absence of a clinically licensed vaccine to prevent HSV-1. However, to encourage clinical translation, the HSV-1 pan-genome was integrated with the reverse-vaccinology pipeline for rigorous screening of universal vaccine candidates. Viral targets were screened from 104 available complete genomes. Among 364 proteins, envelope glycoprotein D being an outer membrane protein with a high antigenicity score (> 0.4) and solubility (> 0.6) was selected for epitope screening. A total of 17 T-cell and 4 B-cell epitopes with highly antigenic, immunogenic, non-toxic properties and high global population coverage were identified. Furthermore, 8 vaccine constructs were designed using different combinations of epitopes and suitable linkers. VC-8 was identified as the most potential vaccine candidate regarding chemical and structural stability. Molecular docking revealed high interactive affinity (low binding energy: - 56.25 kcal/mol) of VC-8 with the target elicited by firm intermolecular H-bonds, salt-bridges, and hydrophobic interactions, which was validated with simulations. Compatibility of the vaccine candidate to be expressed in pET-29(a) + plasmid was established by in silico cloning studies. Immune simulations confirmed the potential of VC-8 to trigger robust B-cell, T-cell, cytokine, and antibody-mediated responses, thereby suggesting a promising candidate for the future of HSV-1 prevention.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-04022-6.

Identification of DPP-IV inhibitory peptides derived from buffalo colostrum: Mining through bioinformatics, in silico and in vitro approaches

Bioactive peptides derived from foods provide physiological health benefits beyond nutrition. This study focused on profiling small peptide inhibitors against two key serine proteases, dipeptidyl peptidase-IV (DPP-IV) and prolyl oligopeptidase (POP). DPP-IV is a well-known protein involved in diverse pathways regulating inflammation, renal, cardiovascular physiology, and glucose homeostasis. POP is yet another key target protein for neurodegenerative disorders. The study evaluated peptide libraries of buffalo colostrum whey and fat globule membrane proteins derived from pepsin and pepsin-pancreatin digestion through in silico web tools and structure-based analysis by molecular docking and binding free-energy estimation, followed by in vitro assay for DPP-IV inhibition for the lead peptides. The bioinformatic study indicated 49 peptides presented motifs with DPP-IV inhibition while 5 peptides with sequences for POP inhibition. In the molecular docking interactions study, 22 peptides interacted with active site residues of DPP-IV and 3 peptides with that of POP. The synthesized peptides, SFVSEVPEL and LTFQHNF inhibited DPP-IV in vitro with an IC50 of 193.5 μM and 1.782 mM, respectively. The study revealed the key residues for inhibition of DPP-IV and POP thus affirming the DPP-IV inhibitory potential of milk-derived peptides.

Reverse vaccinology-based multi-epitope vaccine design against Indian group A rotavirus targeting VP7, VP4, and VP6 proteins

Rotavirus, a primary contributor to severe cases of infantile gastroenteritis on a global scale, results in significant morbidity and mortality in the under-five population, particularly in middle to low-income countries, including India. WHO-approved live-attenuated vaccines are linked to a heightened susceptibility to intussusception and exhibit low efficacy, primarily attributed to the high genetic diversity of rotavirus, varying over time and across different geographic regions. Herein, molecular data on Indian rotavirus A (RVA) has been reviewed through phylogenetic analysis, revealing G1P[8] to be the prevalent strain of RVA in India. The conserved capsid protein sequences of VP7, VP4 and VP6 were used to examine helper T lymphocyte, cytotoxic T lymphocyte and linear B-cell epitopes. Twenty epitopes were identified after evaluation of factors such as antigenicity, non-allergenicity, non-toxicity, and stability. These epitopes were then interconnected using suitable linkers and an N-terminal beta defensin adjuvant. The in silico designed vaccine exhibited structural stability and interactions with integrins (αvβ3 and αIIbβ3) and toll-like receptors (TLR2 and TLR4) indicated by docking and normal mode analyses. The immune simulation profile of the designed RVA multiepitope vaccine exhibited its potential to trigger humoral as well as cell-mediated immunity, indicating that it is a promising immunogen. These computational findings indicate potential efficacy of the designed vaccine against rotavirus infection.

T cell epitope based vaccine design while targeting outer capsid proteins of rotavirus strains infecting neonates: an immunoinformatics approach

Gastrointestinal diarrhea is majorly caused by the rotavirus (RV) in the children who generally are under the age group of 5 years. WHO estimates that ∼95% of the children contract RV infection, by this age. The disease is highly contagious; notably in many cases, it is proven fatal with high mortality rates especially in the developing countries. In India alone, an estimated 145,000 yearly deaths occurs due to RV related gastrointestinal diarrhea. WHO pre-qualified vaccines that are available for RV are all live attenuated vaccines with modest efficacy range between 40 and 60%. Further, the risk of intussusceptions has been reported in some children on RV vaccination. Thus, in a quest to develop alternative candidate to overcome challenges associated with these oral vaccines, we chose immunoinformatics approach to design a multi-epitope vaccine (MEV) while targeting the outer capsid viral proteinsVP4 and VP7 of the neonatal strains of rotavirus. Interestingly, ten epitopes, that is, six CD8+T-cells and four CD4+T-cell epitopes were identified which were predicted to be antigenic, non-allergic, non-toxic and stable. These epitopes were then linked to adjuvants, linkers, and PADRE sequences to create a multi-epitope vaccine for RV. The in silico designed RV-MEV and human TLR5 complex displayed stable interactions during molecular dynamics simulations. Further, the immune simulation studies of RV-MEV corroborated that the vaccine candidate emerges as a promising immunogen. Future investigations while performing in vitro and in vivo analyses with designed RV-MEV construct are highly desirable to warrant the potential of this vaccine candidate in protective immunity against different strains of RVs infecting neonates.Communicated by Ramaswamy H. Sarma.

PyAMPA: a high-throughput prediction and optimization tool for antimicrobial peptides

The alarming rise of antibiotic-resistant bacterial infections is driving efforts to develop alternatives to conventional antibiotics. In this context, antimicrobial peptides (AMPs) have emerged as promising candidates for their ability to target a broad range of microorganisms. However, the development of AMPs with optimal potency, selectivity, and/or stability profiles remains a challenge. To address it, computational tools for predicting AMP properties and designing novel peptides have gained increasing attention. PyAMPA is a novel platform for AMP discovery. It consists of five modules, namely AMPScreen, AMPValidate, AMPSolve, AMPMutate, and AMPOptimize, that allow high-throughput proteome inspection, candidate screening, and optimization through point-mutation and genetic algorithms. The platform also offers additional tools for predicting and evaluating AMP properties, including antimicrobial and cytotoxic activity, and peptide half-life. By providing innovative and accessible inroads into AMP motifs in proteomes, PyAMPA will enable advances in AMP development and potential translation into clinically useful molecules. PyAMPA is available at: https://github.com/SysBioUAB/PyAMPA.

IMPORTANCE

This paper introduces PyAMPA, a new bioinformatics platform designed for the discovery and optimization of antimicrobial peptides (AMPs). It addresses the urgent need for new antimicrobials due to the rise of antibiotic-resistant infections. PyAMPA, with its five predictive modules -AMPScreen, AMPValidate, AMPSolve, AMPMutate and AMPOptimize, enables high-throughput screening of proteomes to identify potential AMP motifs and optimize them for clinical use. Its unique approach, combining prediction, design, and optimization tools, makes PyAMPA a robust solution for developing new AMP-based therapies, offering a significant advance in combatting antibiotic resistance.

Bioinformatics design of a peptide vaccine containing sarcoma antigen NY-SAR-35 epitopes against breast cancer and evaluation of its immunological function in BALB/c mouse model

The development of a cancer vaccine has become an essential focus in the field of medical biotechnology and immunology. In our study, the NY-SAR-35 cancer/testis antigen was targeted to design a novel peptide vaccine using bioinformatics tools, and BALB/c mice were used to evaluate the vaccine's immunological function. This evaluation involved assessing peptide-specific IgG levels in the serum via ELISA and measuring the levels of IFN-γ, IL-4, and granzyme B in the supernatant of cultured splenocytes. The final vaccine construct consisted of two T lymphocyte epitopes linked by the AAY linker. This construct displayed high antigenicity, non-allergenicity, non-toxicity, stability, and ability to induce IFN-γ and IL-4. It showed stable dynamics with both human MHC-I and II molecules, as well as mouse MHC-II molecules, and revealed strong Van der Waals and electrostatic energies. Emulsifying our peptide vaccine in incomplete Freund's adjuvant resulted in a remarkable increase in the levels of IgG. The splenocytes of mice that received the combination of peptide and adjuvant displayed a noteworthy increase in IFN-γ, IL-4, and granzyme B secretion. Additionally, their lymphocytes exhibited higher proliferation rates compared to the control group. Our data demonstrated that our vaccine could stimulate a robust immune response, making it a promising candidate for cancer prevention. However, clinical trials are necessary to assess its efficacy in humans.

An Immunoinformatic-Based In Silico Identification on the Creation of a Multiepitope-Based Vaccination Against the Nipah Virus

The zoonotic viruses pose significant threats to public health. Nipah virus (NiV) is an emerging virus transmitted from bats to humans. The NiV causes severe encephalitis and acute respiratory distress syndrome, leading to high mortality rates, with fatality rates ranging from 40% to 75%. The first emergence of the disease was found in Malaysia in 1998-1999 and later in Bangladesh, Cambodia, Timor-Leste, Indonesia, Singapore, Papua New Guinea, Vietnam, Thailand, India, and other South and Southeast Asian nations. Currently, no specific vaccines or antiviral drugs are available. The potential advantages of epitope-based vaccines include their ability to elicit specific immune responses while minimizing potential side effects. The epitopes have been identified from the conserved region of viral proteins obtained from the UniProt database. The selection of conserved epitopes involves analyzing the genetic sequences of various viral strains. The present study identified two B cell epitopes, seven cytotoxic T lymphocyte (CTL) epitopes, and seven helper T lymphocyte (HTL) epitope interactions from the NiV proteomic inventory. The antigenic and physiological properties of retrieved protein were analyzed using online servers ToxinPred, VaxiJen v2.0, and AllerTOP. The final vaccine candidate has a total combined coverage range of 80.53%. The tertiary structure of the constructed vaccine was optimized, and its stability was confirmed with the help of molecular simulation. Molecular docking was performed to check the binding affinity and binding energy of the constructed vaccine with TLR-3 and TLR-5. Codon optimization was performed in the constructed vaccine within the Escherichia coli K12 strain, to eliminate the danger of codon bias. However, these findings must require further validation to assess their effectiveness and safety. The development of vaccines and therapeutic approaches for virus infection is an ongoing area of research, and it may take time before effective interventions are available for clinical use.

Bioinformatics tools for the study of bioactive peptides from vegetal sources: evolution and future perspectives

Bioactive peptides from vegetal sources have been shown to have functional properties as anti-inflammatory, antioxidant, antihypertensive or antidiabetic capacity. For this reason, they have been proposed as an interesting and promising alternative to improve human health. In recent years, the numerous advances in the bioinformatics field for in silico prediction have speeded up the discovery of bioactive peptides, also reducing the associated costs when using an integrated approach between the classical and bioinformatics discovery. This review aims to provide an overview of the evolution, limitations and latest advances in the field of bioinformatics and computational tools, and specifically make a critical and comprehensive insight into computational techniques used to study the mechanism of interaction that allows the explanation of plant bioactive peptide functionality. In particular, molecular docking is considered key to explain the different functionalities that have been previously identified. The assumptions to simplify such a high complex environment implies a degree of uncertainty that can only be guaranteed and validated by in vitro or in vivo studies, however, the combination of databases, software and bioinformatics applications with the classical approach has become a promising procedure for the study of bioactive peptides.

Mining Bovine Milk Proteins for DPP-4 Inhibitory Peptides Using Machine Learning and Virtual Proteolysis

Dipeptidyl peptidase-IV (DPP-4) enzyme inhibitors are a promising category of diabetes medications. Bioactive peptides, particularly those derived from bovine milk proteins, play crucial roles in inhibiting the DPP-4 enzyme. This study describes a comprehensive strategy for DPP-4 inhibitory peptide discovery and validation that combines machine learning and virtual proteolysis techniques. Five machine learning models, including GBDT, XGBoost, LightGBM, CatBoost, and RF, were trained. Notably, LightGBM demonstrated superior performance with an AUC value of 0.92 ± 0.01. Subsequently, LightGBM was employed to forecast the DPP-4 inhibitory potential of peptides generated through virtual proteolysis of milk proteins. Through a series of in silico screening process and in vitro experiments, GPVRGPF and HPHPHL were found to exhibit good DPP-4 inhibitory activity. Molecular docking and molecular dynamics simulations further confirmed the inhibitory mechanisms of these peptides. Through retracing the virtual proteolysis steps, it was found that GPVRGPF can be obtained from β-casein through enzymatic hydrolysis by chymotrypsin, while HPHPHL can be obtained from κ-casein through enzymatic hydrolysis by stem bromelain or papain. In summary, the integration of machine learning and virtual proteolysis techniques can aid in the preliminary determination of key hydrolysis parameters and facilitate the efficient screening of bioactive peptides.

Subtractive proteomics-based vaccine targets annotation and reverse vaccinology approaches to identify multiepitope vaccine against Plesiomonas shigelloides

Plesiomonas shigelloides, an aquatic bacterium belonging to the Enterobacteriaceae family, is a frequent cause of gastroenteritis with diarrhea and gastrointestinal severe disease. Despite decades of research, discovering a licensed and globally accessible vaccine is still years away. Developing a putative vaccine that can combat the Plesiomonas shigelloides infection by boosting population immunity against P. shigelloides is direly needed. In the framework of the current study, the entire proteome of P. shigelloides was explored using subtractive genomics integrated with the immunoinformatics approach for designing an effective vaccine construct against P. shigelloides. The overall stability of the vaccine construct was evaluated using molecular docking, which demonstrated that MEV showed higher binding affinities with toll-like receptors (TLR4: 51.5 ± 10.3, TLR2: 60.5 ± 9.2) and MHC receptors(MHCI: 79.7 ± 11.2 kcal/mol, MHCII: 70.4 ± 23.7). Further, the therapeutic efficacy of the vaccine construct for generating an efficient immune response was evaluated by computational immunological simulation. Finally, computer-based cloning and improvement in codon composition without altering amino acid sequence led to the development of a proposed vaccine. In a nutshell, the findings of this study add to the existing knowledge about the pathogenesis of this infection. The schemed MEV can be a possible prophylactic agent for individuals infected with P. shigelloides. Nevertheless, further authentication is required to guarantee its safeness and immunogenic potential.

Recent advances in the development of antimicrobial peptides against ESKAPE pathogens

Multi-drug resistant ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) are a global health threat. The severity of the problem lies in its impact on mortality, therapeutic limitations, the threat to public health, and the costs associated with managing infections caused by these resistant strains. Effectively addressing this challenge requires innovative approaches to research, the development of new antimicrobials, and more responsible antibiotic use practices globally. Antimicrobial peptides (AMPs) are a part of the innate immune system of all higher organisms. They are short, cationic and amphipathic molecules with broad-spectrum activity. AMPs interact with the negatively charged bacterial membrane. In recent years, AMPs have attracted considerable interest as potential antibiotics. However, AMPs have low bioavailability and short half-lives, which may be circumvented by chemical modification. This review presents recent in vitro and in silico strategies for the modification of AMPs to improve their stability and application in preclinical experiments.

Evaluation of humoral and cellular immune responses against Vibrio cholerae using oral immunization by multi-epitope-phage-based vaccine

INTRODUCTION

Cholera is a severe gastrointestinal disease that manifests with rapid onset of diarrhea, vomiting, and high mortality rates. Due to its widespread occurrence in impoverished communities with poor water sanitation, there is an urgent demand for a cost-effective and highly efficient vaccine. Multi-epitope vaccines containing dominant immunological epitopes and adjuvant compounds have demonstrated potential in boosting the immune response.

MATERIAL AND METHODS

B and T epitopes of OMPU, OMPW, TCPA, CTXA, and CTXB proteins were predicted using bioinformatics methods. Subsequently, highly antigenic multi-epitopes that are non-allergenic and non-toxic were synthesized. These multi-epitopes were then cloned into the pCOMB phagemid. A plasmid M13KO7ΔpIII containing all helper phage proteins except pIII was created to produce the recombinant phage. Female Balb/c mice were divided into three groups and immunized accordingly. The mice received the helper phage, recombinant phage or PBS via gavage feeding thrice within two weeks. Serum samples were collected before and after immunization for the ELISA test as well as evaluating immune system induction through ELISpot testing of spleen lymphocytes.

RESULTS

The titer of the recombinant phage was determined to be 1011 PFU/ml. The presence of the recombinant phage was confirmed through differences in optical density between sample and control groups in the ELISA phage technique, as well as by observing transduction activity, which demonstrated successful production of a recombinant phage displaying the Vibrio multi-epitope on M13 phage pIII. ELISA results revealed significant differences in phage antibodies before and after inoculation, particularly notable in the negative control mice. Mice treated with multi-epitope phages exhibited antibodies against Vibrio cholerae lysate. Additionally, ELISpot results indicated activation of cellular immunity in mice receiving both Vibrio and helper phage.

CONCLUSION

This study emphasizes the potential of multi-epitope on phage to enhance both cellular and humoral immunity in mice, demonstrating how phages can be used as adjuvants to stimulate mucosal immunity and act as promising candidates for oral vaccination.

A novel peptide derived from Zingiber cassumunar rhizomes exhibits anticancer activity against the colon adenocarcinoma cells (Caco-2) via the induction of intrinsic apoptosis signaling

This paper presents the initial exploration of the free radical scavenging capabilities of peptides derived from protein hydrolysates (PPH) obtained from Zingiber cassumunar rhizomes (Phlai). To replicate the conditions of gastrointestinal digestion, a combination of pepsin and pancreatin proteolysis was employed to generate these hydrolysates. Subsequently, the hydrolysate underwent fractionation using molecular weight cut-off membranes at 10, 5, 3, and 0.65 kDa. The fraction with a molecular weight less than 0.65 kDa exhibited the highest levels ABTS, DPPH, FRAP, and NO radical scavenging activity. Following this, RP-HPLC was used to further separate the fraction with a molecular weight less than 0.65 kDa into three sub-fractions. Among these, the F5 sub-fraction displayed the most prominent radical-scavenging properties. De novo peptide sequencing via quadrupole-time-of-flight-electron spin induction-mass spectrometry identified a pair of novel peptides: Asp-Gly-Ile-Phe-Val-Leu-Asn-Tyr (DGIFVLNY or DY-8) and Ile-Pro-Thr-Asp-Glu-Lys (IPTDEK or IK-6). Database analysis confirmed various properties, including biological activity, toxicity, hydrophilicity, solubility, and potential allergy concerns. Furthermore, when tested on the human adenocarcinoma colon (Caco-2) cell line, two synthetic peptides demonstrated cellular antioxidant activity in a concentration-dependent manner. These peptides were also assessed using the FITC Annexin V apoptosis detection kit with PI, confirming the induction of apoptosis. Notably, the DY-8 peptide induced apoptosis, upregulated mRNA levels of caspase-3, -8, and -9, and downregulated Bcl-2, as confirmed by real-time quantitative polymerase chain reaction (RT-qPCR). Western blot analysis indicated increased pro-apoptotic Bax expression and decreased anti-apoptotic Bcl-2 expression in Caco-2 cells exposed to the DY-8 peptide. Molecular docking analysis revealed that the DY-8 peptide exhibited binding affinity with Bcl-2, Bcl-xL, and Mcl-1, suggesting potential utility in combating colon cancer as functional food ingredients.

Exploring the Relationship between Small Peptides and the T1R1/T1R3 Umami Taste Receptor for Umami Peptide Prediction: A Combined Approach

Umami peptides are known for enhancing the taste experience by binding to oral umami T1R1 and T1R3 receptors. Among them, small peptides (composed of 2-4 amino acids) constitute nearly 40% of reported umami peptides. Given the diversity in amino acids and peptide sequences, umami small peptides possess tremendous untapped potential. By investigating 168,400 small peptides, we screened candidates binding to T1R1/T1R3 through molecular docking and molecular dynamics simulations, explored bonding types, amino acid characteristics, preferred binding sites, etc. Utilizing three-dimensional molecular descriptors, bonding information, and a back-propagation neural network, we developed a predictive model with 90.3% accuracy, identifying 24,539 potential umami peptides. Clustering revealed three classes with distinct logP (-2.66 ± 1.02, -3.52 ± 0.93, -2.44 ± 1.23) and asphericity (0.28 ± 0.12, 0.26 ± 0.11, 0.25 ± 0.11), indicating significant differences in shape and hydrophobicity (P < 0.05) among potential umami peptides binding to T1R1/T1R3. Following clustering, nine representative peptides (CQ, DP, NN, CSQ, DMC, TGS, DATE, HANR, and STAN) were synthesized and confirmed to possess umami taste through sensory evaluations and electronic tongue analyses. In summary, this study provides insights into exploring small peptide interactions with umami receptors, advancing umami peptide prediction models.

An integrated in silico approach for the identification of novel potential drug target and chimeric vaccine against Neisseria meningitides strain 331401 serogroup X by subtractive genomics and reverse vaccinology

Neisseria meningitidis, commonly known as the meningococcus, leads to substantial illness and death among children and young adults globally, revealing as either epidemic or sporadic meningitis and/or septicemia. In this study, we have designed a novel peptide-based chimeric vaccine candidate against the N. meningitidis strain 331,401 serogroup X. Through rigorous analysis of subtractive genomics, two essential cytoplasmic proteins, namely UPI000012E8E0(UDP-3-O-acyl-GlcNAc deacetylase) and UPI0000ECF4A9(UDP-N-acetylglucosamine acyltransferase) emerged as potential drug targets. Additionally, using reverse vaccinology, the outer membrane protein UPI0001F4D537 (Membrane fusion protein MtrC) identified by subcellular localization and recognized for its known indispensable role in bacterial survival was identified as a novel chimeric vaccine target. Following a careful comparison of MHC-I, MHC-II, T-cell, and B-cell epitopes, three epitopes derived from UPI0001F4D537 were linked with three types of linkers-GGGS, EAAAK, and the essential PADRE-for vaccine construction. This resulted in eight distinct vaccine models (V1-V8). Among them V1 model was selected as the final vaccine construct. It exhibits exceptional immunogenicity, safety, and enhanced antigenicity, with 97.7 % of its residues in the Ramachandran plot's most favored region. Subsequently, the vaccine structure was docked with the TLR4/MD2 complex and six different HLA allele receptors using the HADDOCK server. The docking resulted in the lowest HADDOCK score of 39.3 ± 9.0 for TLR/MD2. Immune stimulation showed a strong immune response, including antibodies creation and the activation of B-cells, T Cytotoxic cells, T Helper cells, Natural Killer cells, and interleukins. Furthermore, the vaccine construct was successfully expressed in the Escherichia coli system by reverse transcription, optimization, and ligation in the pET-28a (+) vector for the expression study. The current study proposes V1 construct has the potential to elicit both cellular and humoral responses, crucial for the developing an epitope-based vaccine against N. meningitidis strain 331,401 serogroup X.

Intranasal Delivery of Cell-Penetrating Therapeutic Peptide Enhances Brain Delivery, Reduces Inflammation, and Improves Neurologic Function in Moderate Traumatic Brain Injury

Following traumatic brain injury (TBI), secondary brain damage due to chronic inflammation is the most predominant cause of the delayed onset of mood and memory disorders. Currently no therapeutic approach is available to effectively mitigate secondary brain injury after TBI. One reason is the blood-brain barrier (BBB), which prevents the passage of most therapeutic agents into the brain. Peptides have been among the leading candidates for CNS therapy due to their low immunogenicity and toxicity, bioavailability, and ease of modification. In this study, we demonstrated that non-invasive intranasal (IN) administration of KAFAK, a cell penetrating anti-inflammatory peptide, traversed the BBB in a murine model of diffuse, moderate TBI. Notably, KAFAK treatment reduced the production of proinflammatory cytokines that contribute to secondary injury. Furthermore, behavioral tests showed improved or restored neurological, memory, and locomotor performance after TBI in KAFAK-treated mice. This study demonstrates KAFAK's ability to cross the blood-brain barrier, to lower proinflammatory cytokines in vivo, and to restore function after a moderate TBI.

Epitope screening and self-assembled nanovaccine molecule design of PDCoV-S protein based on immunoinformatics

Based on the whole virus or spike protein of pigs, δ coronavirus (PDCoV) as an immunogen may have unrelated antigenic epitope interference. Therefore, it is essential for screening and identifying advantageous protective antigen epitopes. In addition, immunoinformatic tools are described as an important aid in determining protective antigenic epitopes. In this study, the primary, secondary, and tertiary structures of vaccines were measured using ExPASy, PSIPRED 4.0, and trRosetta servers. Meanwhile, the molecular docking analysis and vector of the candidate nanovaccine were constructed. The immune response of the candidate vaccine was simulated and predicted using the C-ImmSim server. This experiment screened B cell epitopes with strong immunogenicity and high conservation, CTL epitopes, and Th epitopes with IFN-γ and IL-4 positive spike proteins. Ferritin is used as a self-assembled nanoparticle element for designing candidate nanovaccine. After analysis, it has been found to be soluble, stable, non-allergenic, and has a high affinity for its target receptor, TLR-3. The preliminary simulation analysis results show that the candidate nanovaccine has the ability to induce a humoral and cellular immune response. Therefore, it may provide a new theoretical basis for research on coronavirus self-assembled nanovaccines. It may be an effective candidate vaccine for controlling and preventing PDCoV.

Techno-Functions and Safety Concerns of Plant-Based Peptides in Food Matrices

Plant-based peptides (PBPs) benefit functional food development and environmental sustainability. Proteolysis remains the primary method of peptide production because it is a mild and nontoxic technique. However, potential safety concerns still emanate from toxic or allergenic sequences, amino acid racemization, iso-peptide bond formation, Maillard reaction, dose usage, and frequency. The main aim of this review is to investigate the techno-functions of PBPs in food matrices, as well as their safety concerns. The distinctive characteristics of PBPs exhibit their techno-functions for improving food quality and functionality by contributing to several crucial food formulations and processing. The techno-functions of PBPs include solubility, hydrophobicity, bitterness, foaming, oil-binding, and water-holding capacities, which subsequently affect food matrices. The safety and quality of foodstuff containing PBPs depend on the proper source of plant proteins, the selection of processing approaches, and compliance with legal regulations for allergen labeling and safety evaluations. The safety concerns in allergenicity and toxicity were discussed. The conclusion is that food technologists must apply safe limits and consider potential allergenic components generated during the development of food products with PBPs. Therefore, functional food products containing PBPs can be a promising strategy to provide consumers with wholesome health benefits.

Designing a smallpox B-cell and T-cell multi-epitope subunit vaccine using a comprehensive immunoinformatics approach

Smallpox is a highly contagious human disease caused by the variola virus. Although the disease was eliminated in 1979 due to its highly contagious nature and historical pathogenicity, with a mortality rate of up to 30%, this virus is an important candidate for biological weapons. Currently, vaccines are the critical measures to prevent this virus infection and spread. In this study, we designed a peptide vaccine using immunoinformatics tools, which have the potential to activate human immunity against variola virus infection efficiently. The design of peptides derives from vaccine-candidate proteins showing protective potential in vaccinia WR strains. Potential non-toxic and nonallergenic T-cell and B-cell binding and cytokine-inducing epitopes were then screened through a priority prediction using special linkers to connect B-cell epitopes and T-cell epitopes, and an appropriate adjuvant was added to the vaccine construction to enhance the immunogenicity of the peptide vaccine. The 3D structure display, docking, and free energy calculation analysis indicate that the binding affinity between the vaccine peptide and Toll-like receptor 3 is high, and the vaccine receptor complex is highly stable. Notably, the vaccine we designed is obtained from the protective protein of the vaccinia and combined with preventive measures to avoid side effects. This vaccine is highly likely to produce an effective and safe immune response against the variola virus infection in the body.

IMPORTANCE

In this work, we designed a vaccine with a cluster of multiple T-cell/B-cell epitopes, which should be effective in inducing systematic immune responses against variola virus infection. Besides, this work also provides a reference in vaccine design for preventing monkeypox virus infection, which is currently prevalent.

In silico and in vivo discovery of antioxidant sea cucumber peptides with antineurodegenerative properties

Since oxidative stress is often associated with neurodegenerative diseases, antioxidants are likely to confer protection against neurodegeneration. Despite an increasing number of food-derived peptides being identified as antioxidants, their antineurodegenerative potentials remain largely unexplored. Here, a sea cucumber peptide preparation - the peptide-rich fraction of <3 kDa (UF<3K) obtained by ultrafiltration from Apostichopus japonicus protein hydrolyzate - was found to protect PC12 cells and Caenorhabditis elegans from neurodegeneration by reducing oxidative stress and apoptosis, demonstrating its in vitro and in vivo neuroprotective effects. As many food-originated peptides are cryptides (cryptic peptides - short amino acid sequences encrypted in parent proteins) released in quantities by protein hydrolysis, UF<3K was subjected to sequencing analysis. As expected, a large repertoire of peptides were identified in UF<3K, establishing a sea cucumber cryptome (1238 peptides in total). Then 134 peptides were randomly selected from the cryptome (>10%) and analyzed for their antioxidant activities using a number of in silico bioinformatic programs as well as in vivo experimental assays in C. elegans. From these results, a novel antioxidant peptide - HoloPep#362 (FETLMPLWGNK) - was shown to not only inhibit aggregation of neurodegeneration-associated polygluatmine proteins but also ameliorate behavioral deficits in proteotoxicity nematodes. Proteomic analysis revealed an increased expression of several lysosomal proteases by HoloPep#362, suggesting proteostasis maintenance as a mechanism for its antineurodegenerative action. These findings provide an insight into the health-promoting potential of sea cucumber peptides as neuroprotective nutraceuticals and also into the importance of training in silico peptide bioactivity prediction programs with in vivo experimental data.

Bioactive peptides in dry-cured ham: A comprehensive review of preparation methods, metabolic stability, safety, health benefits, and regulatory frameworks

Dry-cured hams contain abundant bioactive peptides with significant potential for the development of functional foods. However, the limited bioavailability of food-derived bioactive peptides has hindered their utilization in health food development. Moreover, there is insufficient regulatory information regarding bioactive peptides and related products globally. This review summarizes diverse bioactive peptides derived from dry-cured ham and by-products originating from various countries and regions. The bioactivity, preparation techniques, bioavailability, and metabolic stability of these bioactive peptides are described, as well as the legal and regulatory frameworks in various countries. The primary objectives of this review are to dig deeper into the functionality of dry-cured ham and provide theoretical support for the commercialization of bioactive peptides from food sources, especially the dry-cured ham.

Antibacterial Properties and Efficacy of LL-37 Fragment GF-17D3 and Scolopendin A2 Peptides Against Resistant Clinical Strains of Staphylococcus aureus, Pseudomonas aeruginosa, and Acinetobacter baumannii In Vitro and In Vivo Model Studies

Pseudomonas aeruginosa, Staphylococcus aureus, and Acinetobacter baumannii have emerged as major clinical threats owing to the increasing prevalence of ventilator-associated pneumonia caused by multidrug-resistant or extensively drug-resistant strains. The present study aimed to assess the antibacterial effects and efficacy of LL-37 fragment GF-17D3 and synthetic Scolopendin A2 peptides against resistant clinical strains in vitro and in vivo models. P. aeruginosa, S. aureus, and A. baumannii were isolated from clinical infections. Their antibiotic resistance and minimum inhibitory concentration were assessed. LL-37 fragment GF-17D3 peptide was selected from available databases. Scolopendin A2 peptide's 6th amino acid (proline) was substituted with lysine and peptides and MICs were determined. The biofilm inhibitory activity was quantified at sub MIC concentrations. Synergetic effects of Scolopendin A2 and imipenem were assessed by checkerboard. After mice nasal infection with P. aeruginosa, peptides LD50 was determined. Isolates harbored complete resistance toward the majority of antibiotics and MIC values ranged between 1 and > 512 µg/ml. The majority of isolates exhibited strong biofilm activity. Synthetic peptides showed lower MIC values than antibiotic agents and the lowest MIC values were obtained for synthetic peptides in combination with antibiotics. The Synergisms effect of Scolopendin A2 with imipenem was also determined. Scolopendin A2 was found to have antibacterial efficacy against P. aeruginosa, S. aureus, and A. baumannii with MIC 64 µg/ml, 8 µg/ml, and 16 µg/ml, respectively, and LL37 showed antibacterial efficacy against P. aeruginosa, S. aureus, and A. baumannii with MIC 128 µg/ml, 32 µg/ml, and 32 µg/ml, respectively. Both AMPs decreased biofilms by ≥ 96% at 1 × MIC. The biofilm inhibitory activity was measured at sub MIC concentrations of the peptides and the results demonstrated that Scolopendin A2 exhibited anti-biofilm activity at 1/4 × MIC and 1/2 × MIC concentrations was 47.9 to 63.8%, although LL37 among 1/4 × MIC and 1/2 × MIC concentrations was 21.3 to 49.6% against three pathogens. The combination of Scolopendin A2 and antibiotics demonstrated synergistic activity-resistant strains with FIC values ≤ 0.5 for three pathogens, while LL37 and antibiotics showed synergistic activity FIC values ≤ 0.5 for only P. aeruginosa. Infection model Scolopendin A2 with Imipenem (2 × MIC) was efficacious in vivo, with a 100% survival rate following treatment at 2 × MIC after 120 h. The mRNA expression of biofilm-related genes was decreased for both peptides. Synthesis Scolopendin A2 decreased the expression of biofilm formation genes compared to the control group. Synthetic Scolopendin A2 exhibits antimicrobial activity without causing toxicity on the human epithelial cell line. Based on our findings, it seems that synthetic Scolopendin A2 is an appropriate antimicrobial source. That could be a promising option in combination with antibiotics for a topical medication and in the prevention of acute and chronic infections caused by multidrug-resistant bacteria. Nevertheless, additional experiments are required to assess another potential of this novel AMP.

Development of a defibrinated human blood hemolysis assay for rapid testing of hemolytic activity compared to computational prediction

Cytotoxicity studies determining hemolytic properties of antimicrobial peptides or other drugs are an important step in the development of novel therapeutics for clinical use. Hemolysis is an affordable, accessible, and rapid method for initial assessment of cellular toxicity for all drugs under development. However, variability in species of red blood cells and protocols used may result in significant differences in results. AMPs generally possess higher selectivity for bacterial cells but can have toxicity against host cells at high concentrations. Knowing the hemolytic activity of the peptides we are developing contributes to our understanding of their potential toxicity. Computational approaches for predicting hemolytic activity of AMPs exist and were tested head-to-head with our experimental results.

RESULTS

Starting with an observation of high hemolytic activity of LL-37 peptide against human red blood cells that were collected in EDTA, we explored alternative approaches to develop a more robust, accurate and simple hemolysis assay using defibrinated human blood. We found significant differences between the sensitivity of defibrinated red blood cells and EDTA treated red blood cells.

SIGNIFICANCE

Accurately determining the hemolytic activity using human red blood cells will allow for a more robust calculation of the therapeutic index of our potential antimicrobial compounds, a critical measure in their pre-clinical development.

CONCLUSION

We introduce a standardized, more accurate protocol for assessing hemolytic activity using defibrinated human red blood cells. This approach, facilitated by the increased commercial availability of de-identified human blood and defibrination methods, offers a robust tool for evaluating toxicity of emerging drug compounds, especially AMPs.

Immunoinformatics-Based Design of Multi-epitope DNA and mRNA Vaccines Against Zika Virus

In this study, we used an immunoinformatics approach to predict antigenic epitopes of Zika virus (ZIKV) proteins to assist in designing a vaccine antigen against ZIKV. We performed the prediction of CD8+ T-lymphocyte and antigenic B-cell epitopes of ZIKV proteins. The binding interactions of T-cell epitopes with major histocompatibility complex class I (MHC-I) proteins were assessed. We selected the antigenic, conserved, nontoxic, and immunogenic epitopes, which indicated significant interactions with the human leucocyte antigen (HLA-A and HLA-B) alleles and worldwide population coverage of 76.35%. The predicted epitopes were joined with the help of linkers and an adjuvant. The vaccine antigen was then analyzed through molecular docking with TLR3 and TLR8, and it was in silico cloned in the pVAX1 vector to be used as a DNA vaccine and designed as a mRNA vaccine.

A novel approach to design chimeric multi epitope vaccine against Leishmania exploiting infected host cell proteome

Leishmaniasis is a major infectious disease having high mortality which could be attributed to lack of a suitable vaccine candidate. We propose a novel approach to design multiepitope vaccine to leishmaniasis exploiting specific membrane proteome from infected macrophage from host. The MHC-I, MHC-II and BC epitopes predicted for unique proteins from the infected macrophages and Leishmania and a MEV designed in various combinations (1a-1m). The epitope arrangements 1a, 1k, 1l, and 1 m showed a strong antigenicity profile and immune response. The molecular dynamics simulation indicate the 1k, 1l, and 1 m constructs have strong affinity toward TLR-2, TLR-3, and TLR-4. Overall the structural and immunogenicity profile suggests 1k is top candidate. Further, a computational model system with TLR-2, TLR-3, TLR-4, BCR, MHC-I and MHC-II was generated for 1k construct to understand the MEV interactions with immune components. Dihedral distribution and distance was enumerated to understand the movement of immune components towards 1k. The results indicate 1k has strong affinity for the immune response molecules especially TLR-3, BCR and MHC-II are coming in close contact with the MEV through the simulation. The study suggests that designed multi-epitope vaccine 1k has potential to induce proper immune response but warrants further studies.

Immune targeting of filarial glutaredoxin through a multi-epitope peptide-based vaccine: A reverse vaccinology approach

Despite the efforts of global programme to eliminate lymphatic filariasis (GPELF), the threat of lymphatic filariasis (LF) still looms over humanity in terms of long-term disabilities, and morbidities across the globe. In light of this situation, investigators have chosen to focus on the development of immunotherapeutics targeting the physiologically important filarial-specific proteins. Glutaredoxin (16.43 kDa) plays a pivotal role in filarial redox biology, serving as a vital contributor. In the context of the intra-host survival of filarial parasites, this antioxidant helps in mitigating the oxidative stress imposed by the host immune system. Given its significant contribution, the development of a vaccine targeting glutaredoxin holds promise as a new avenue for achieving a filaria-free world. Herein, multi-epitope-based vaccine was designed using advanced immunoinformatics approach. Initially, 4B-cell epitopes and 6 T-cell epitopes (4 MHC I and 2 MHC II) were identified from the 146 amino acid long sequence of glutaredoxin of the human filarid, Wuchereria bancrofti. Subsequent clustering of these epitopes with linker peptides finalized the vaccine structure. To boost TLR-mediated innate immunity, TLR-specific adjuvants were incorporated into the designed vaccine. After that, experimental analyses confirm the designed vaccine, Vac4 as anefficient ligand of human TLR5 to elicit protective innate immunity against filarial glutaredoxin. Immune simulation further demonstrated abundant levels of IgG and IgM as crucial contributors in triggering vaccine-induced adaptive responses in the recipients. Hence, to facilitate the validation of immunogenicity of the designed vaccine, Vac4 was cloned in silico in pET28a(+) expression vector for recombinant production. Taken together, our findings suggest that vaccine-mediated targeting of filarial glutaredoxin could be a future option for intervening LF on a global scale.

Systems approach to design multi-epitopic peptide vaccine candidate against fowl adenovirus structural proteins for Gallus gallus domesticus

Introduction

Fowl adenovirus (FAdV) is a significant pathogen in poultry, causing various diseases such as hepatitis-hydropericardium, inclusion body hepatitis, and gizzard erosion. Different serotypes of FAdV are associated with specific conditions, highlighting the need for targeted prevention strategies. Given the rising prevalence of FAdV-related diseases globally, effective vaccination and biosecurity measures are crucial. In this study, we explore the potential of structural proteins to design a multi-epitope vaccine targeting FAdV.

Methods

We employed an in silico approach to design the multi-epitope vaccine. Essential viral structural proteins, including hexon, penton, and fiber protein, were selected as vaccine targets. T-cell and B-cell epitopes binding to MHC-I and MHC-II molecules were predicted using computational methods. Molecular docking studies were conducted to validate the interaction of the multi-epitope vaccine candidate with chicken Toll-like receptors 2 and 5.

Results

Our in silico methodology successfully identified potential T-cell and B-cell epitopes within the selected viral structural proteins. Molecular docking studies revealed strong interactions between the multi-epitope vaccine candidate and chicken Toll-like receptors 2 and 5, indicating the structural integrity and immunogenic potential of the designed vaccine.

Discussion

The designed multi-epitope vaccine presents a promising approach for combating FAdV infections in chickens. By targeting essential viral structural proteins, the vaccine is expected to induce a robust immunological response. The in silico methodology utilized in this study provides a rapid and cost-effective means of vaccine design, offering insights into potential vaccine candidates before experimental validation. Future studies should focus on in vitro and in vivo evaluations to further assess the efficacy and safety of the proposed vaccine.

Bioinformatics approach for structure modeling, vaccine design, and molecular docking of Brucella candidate proteins BvrR, OMP25, and OMP31

Brucellosis is a zoonotic disease with significant economic and healthcare costs. Despite the eradication efforts, the disease persists. Vaccines prevent disease in animals while antibiotics cure humans with limitations. This study aims to design vaccines and drugs for brucellosis in animals and humans, using protein modeling, epitope prediction, and molecular docking of the target proteins (BvrR, OMP25, and OMP31). Tertiary structure models of three target proteins were constructed and assessed using RMSD, TM-score, C-score, Z-score, and ERRAT. The best models selected from AlphaFold and I-TASSER due to their superior performance according to CASP 12 - CASP 15 were chosen for further analysis. The motif analysis of best models using MotifFinder revealed two, five, and five protein binding motifs, however, the Motif Scan identified seven, six, and eight Post-Translational Modification sites (PTMs) in the BvrR, OMP25, and OMP31 proteins, respectively. Dominant B cell epitopes were predicted at (44-63, 85-93, 126-137, 193-205, and 208-237), (26-46, 52-71, 98-114, 142-155, and 183-200), and (29-45, 58-82, 119-142, 177-198, and 222-251) for the three target proteins. Additionally, cytotoxic T lymphocyte epitopes were detected at (173-181, 189-197, and 202-210), (61-69, 91-99, 159-167, and 181-189), and (3-11, 24-32, 167-175, and 216-224), while T helper lymphocyte epitopes were displayed at (39-53, 57-65, 150-158, 163-171), (79-87, 95-108, 115-123, 128-142, and 189-197), and (39-47, 109-123, 216-224, and 245-253), for the respective target protein. Furthermore, structure-based virtual screening of the ZINC and DrugBank databases using the docking MOE program was followed by ADMET analysis. The best five compounds of the ZINC database revealed docking scores ranged from (- 16.8744 to - 15.1922), (- 16.0424 to - 14.1645), and (- 14.7566 to - 13.3222) for the BvrR, OMP25, and OMP31, respectively. These compounds had good ADMET parameters and no cytotoxicity, while DrugBank compounds didn't meet Lipinski's rule criteria. Therefore, the five selected compounds from the ZINC20 databases may fulfill the pharmacokinetics and could be considered lead molecules for potentially inhibiting Brucella's proteins.

VISH-Pred: an ensemble of fine-tuned ESM models for protein toxicity prediction

Peptide- and protein-based therapeutics are becoming a promising treatment regimen for myriad diseases. Toxicity of proteins is the primary hurdle for protein-based therapies. Thus, there is an urgent need for accurate in silico methods for determining toxic proteins to filter the pool of potential candidates. At the same time, it is imperative to precisely identify non-toxic proteins to expand the possibilities for protein-based biologics. To address this challenge, we proposed an ensemble framework, called VISH-Pred, comprising models built by fine-tuning ESM2 transformer models on a large, experimentally validated, curated dataset of protein and peptide toxicities. The primary steps in the VISH-Pred framework are to efficiently estimate protein toxicities taking just the protein sequence as input, employing an under sampling technique to handle the humongous class-imbalance in the data and learning representations from fine-tuned ESM2 protein language models which are then fed to machine learning techniques such as Lightgbm and XGBoost. The VISH-Pred framework is able to correctly identify both peptides/proteins with potential toxicity and non-toxic proteins, achieving a Matthews correlation coefficient of 0.737, 0.716 and 0.322 and F1-score of 0.759, 0.696 and 0.713 on three non-redundant blind tests, respectively, outperforming other methods by over $10\%$ on these quality metrics. Moreover, VISH-Pred achieved the best accuracy and area under receiver operating curve scores on these independent test sets, highlighting the robustness and generalization capability of the framework. By making VISH-Pred available as an easy-to-use web server, we expect it to serve as a valuable asset for future endeavors aimed at discerning the toxicity of peptides and enabling efficient protein-based therapeutics.

Development of multi epitope subunit vaccines against emerging carp viruses Cyprinid herpesvirus 1 and 3 using immunoinformatics approach

Cyprinid herpesvirus is a causative agent of a destructive disease in common and koi carp (Cyprinus carpio), which leads to substantial global financial losses in aquaculture industries. Among the strains of C. herpesvirus, C. herpesvirus 1 (CyHV-1) and C. herpesvirus 3 (CyHV-3) are known as highly pathogenic to carp fishes in Europe, Asia, and Africa. To date, no effective vaccine has been developed to combat these viruses. This study aimed to develop unique multi-epitope subunit vaccines targeting the CyHV-1 and CyHV-3 using a reverse vaccinology approach. The study began with a comprehensive literature review to identify the most critical proteins, which were then subjected to in silico analyses to predict highly antigenic epitopes. These analyses involved assessing antigenicity, transmembrane topology screening, allergenecity, toxicity, and molecular docking approaches. We constructed two multi-epitope-based vaccines incorporating a suitable adjuvant and appropriate linkers. It revealed that both the vaccines are non-toxic and immunogenic. The tertiary structures of the vaccine proteins were generated, refined, and validated to ensure their suitability. The binding affinity between the vaccine constructs and TLR3 and TLR5 receptors were assessed by molecular docking studies. Molecular dynamics simulations indicated that vaccine construct V1 exhibited greater stability with both TLR3 and TLR5 based on RMSD analysis. Hydrogen bond analysis revealed a stronger binding affinity between the vaccine constructs and TLR5 compared to TLR3. Furthermore, MM-PBSA analysis suggested that both vaccine constructs exhibited a better affinity for TLR5. Considering all aspects, the results suggest that in silico development of CyHV vaccines incorporating multiple epitopes holds promise for management of diseases caused by CyHV-1 and CyHV-3. However, further in vivo trials are highly recommended to validate the efficacies of these vaccines.