In silico approach for predicting toxicity of peptides and proteins

Designing a Multi-Epitope Subunit Vaccine against VP1 Major Coat Protein of JC Polyomavirus

The JC polyomavirus virus (JCPyV) affects more than 80% of the human population in their early life stage. It mainly affects immunocompromised individuals where virus replication in oligodendrocytes and astrocytes may lead to fatal progressive multifocal encephalopathy (PML). Virus protein 1 (VP1) is one of the major structural proteins of the viral capsid, responsible for keeping the virus alive in the gastrointestinal and urinary tracts. VP1 is often targeted for antiviral drug and vaccine development. Similarly, this study implied immune-informatics and molecular modeling methods to design a multi-epitope subunit vaccine targeting JCPyV. The VP1 protein epitopic sequences, which are highly conserved, were used to build the vaccine. This designed vaccine includes two adjuvants, five HTL epitopes, five CTL epitopes, and two BCL epitopes to stimulate cellular, humoral, and innate immune responses against the JCPyV. Furthermore, molecular dynamics simulation (100 ns) studies were used to examine the interaction and stability of the vaccine protein with TLR4. Trajectory analysis showed that the vaccine and TLR4 receptor form a stable complex. Overall, this study may contribute to the path of vaccine development against JCPyV.

Computer simulation approach to the identification of visfatin-derived angiogenic peptides

Angiogenesis plays an essential role in various normal physiological processes, such as embryogenesis, tissue repair, and skin regeneration. Visfatin is a 52 kDa adipokine secreted by various tissues including adipocytes. It stimulates the expression of vascular endothelial growth factor (VEGF) and promotes angiogenesis. However, there are several issues in developing full-length visfatin as a therapeutic drug due to its high molecular weight. Therefore, the purpose of this study was to develop peptides, based on the active site of visfatin, with similar or superior angiogenic activity using computer simulation techniques.Initially, the active site domain (residues 181∼390) of visfatin was first truncated into small peptides using the overlapping technique. Subsequently, the 114 truncated small peptides were then subjected to molecular docking analysis using two docking programs (HADDOCK and GalaxyPepDock) to generate small peptides with the highest affinity for visfatin. Furthermore, molecular dynamics simulations (MD) were conducted to investigate the stability of the protein-ligand complexes by computing root mean square deviation (RSMD) and root mean square fluctuation(RMSF) plots for the visfatin-peptide complexes. Finally, peptides with the highest affinity were examined for angiogenic activities, such as cell migration, invasion, and tubule formation in human umbilical vein endothelial cells (HUVECs). Through the docking analysis of the 114 truncated peptides, we screened nine peptides with a high affinity for visfatin. Of these, we discovered two peptides (peptide-1: LEYKLHDFGY and peptide-2: EYKLHDFGYRGV) with the highest affinity for visfatin. In an in vitrostudy, these two peptides showed superior angiogenic activity compared to visfatin itself and stimulated mRNA expressions of visfatin and VEGF-A. These results show that the peptides generated by the protein-peptide docking simulation have a more efficient angiogenic activity than the original visfatin.

Insight on the mechanism of hexameric Pseudin-4 against bacterial membrane-mimetic environment

As an alternative to antibiotics, Antimicrobial Peptides (AMPs) possess unique properties including cationic, amphipathic and their abundance in nature, but the exact characteristics of AMPs against bacterial membranes are still undetermined. To estimate the structural stability and functional activity of AMPs, the Pseudin AMPs (Pse-1, Pse-2, Pse-3, and Pse-4) from Hylid frog species, Pseudis paradoxa, an abundantly discovered source for AMPs were examined. We studied the intra-peptide interactions and thermal denaturation stability of peptides, as well as the geometrical parameters and secondary structure profiles of their conformational trajectories. On this basis, the peptides were screened out and the highly stable peptide, Pse-4 was subjected to membrane simulation in order to observe the changes in membrane curvature formed by Pse-4 insertion. Monomeric Pse-4 was found to initiate the membrane disruption; however, a stable multimeric form of Pse-4 might be competent to counterbalance the helix-coil transition and to resist the hydrophobic membrane environment. Eventually, hexameric Pse-4 on membrane simulation exhibited the hydrogen bond formation with E. coli bacterial membrane and thereby, leading to the formation of membrane spanning pore that allowed the entry of excess water molecules into the membrane shell, thus causing membrane deformation. Our report points out the mechanism of Pse-4 peptide against the bacterial membrane for the first time. Relatively, Pse-4 works on the barrel stave model against E. coli bacterial membrane; hence it might act as a good therapeutic scaffold in the treatment of multi-drug resistant bacterial strains.

Computational formulation of a multiepitope vaccine unveils an exceptional prophylactic candidate against Merkel cell polyomavirus

Merkel cell carcinoma (MCC) is a rare neuroendocrine skin malignancy caused by human Merkel cell polyomavirus (MCV), leading to the most aggressive skin cancer in humans. MCV has been identified in approximately 43%-100% of MCC cases, contributing to the highly aggressive nature of primary cutaneous carcinoma and leading to a notable mortality rate. Currently, no existing vaccines or drug candidates have shown efficacy in addressing the ailment caused by this specific pathogen. Therefore, this study aimed to design a novel multiepitope vaccine candidate against the virus using integrated immunoinformatics and vaccinomics approaches. Initially, the highest antigenic, immunogenic, and non-allergenic epitopes of cytotoxic T lymphocytes, helper T lymphocytes, and linear B lymphocytes corresponding to the virus whole protein sequences were identified and retrieved for vaccine construction. Subsequently, the selected epitopes were linked with appropriate linkers and added an adjuvant in front of the construct to enhance the immunogenicity of the vaccine candidates. Additionally, molecular docking and dynamics simulations identified strong and stable binding interactions between vaccine candidates and human Toll-like receptor 4. Furthermore, computer-aided immune simulation found the real-life-like immune response of vaccine candidates upon administration to the human body. Finally, codon optimization was conducted on the vaccine candidates to facilitate the in silico cloning of the vaccine into the pET28+(a) cloning vector. In conclusion, the vaccine candidate developed in this study is anticipated to augment the immune response in humans and effectively combat the virus. Nevertheless, it is imperative to conduct in vitro and in vivo assays to evaluate the efficacy of these vaccine candidates thoroughly. These evaluations will provide critical insights into the vaccine's effectiveness and potential for further development.

Processing Enhances Coix Seed Prolamins Structure and Releases Functional Peptides after Digestion: In Silico and In Vitro Studies

Dipeptidyl peptidase-IV (DPP-IV) is a key target for the treatment of type 2 diabetes mellitus. It is possible that peptides that precisely regulate DPP-IV could be released from coix seed prolamins (CSP), but whether this happens has not yet been investigated. We performed the in silico digestion of CSP and predicted the bioactivity, absorption, transport, toxicity, and allergenicity of the resulting peptides. The simulation predicted that 47 non-toxic bioactive peptides would be released. After screening these, we found that 64.58% of them could possess DPP-IV inhibitory activity. The effect of thermal processing on the amino acid composition and structural properties of CSP was determined, and the DPP-IV inhibitory activity of its digestion-derived peptides was also assessed. The results showed that processing could change the flavour of coix seed and the supply of amino acids. After processing, the spatial conformation of CSP changed from ordered to disordered, and the peptide content and the DPP-IV inhibitory activity of its digestion products significantly increased by 19.89-30.91% and 36.84-42.02%, respectively. These results support the hypothesis that processing can change the protein structure and increase the probability that bioactive peptides will be released. They also have important implications for the development of bioactive peptides and the intensive processing of coix seeds.

A Peptide Vaccine Design Targeting KIT Mutations in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a leading blood cancer subtype that can be caused by 27 gene mutations. Previous studies have explored potential vaccine and drug treatments against AML, but many were proven immunologically insignificant. Here, we targeted this issue and applied various clinical filters to improve immune response. KIT is an oncogenic gene that can cause AML when mutated and is predicted to be a promising vaccine target because of its immunogenic responses when activated. We designed a multi-epitope vaccine targeting mutations in the KIT oncogene using CD8+ and CD4+ epitopes. We selected the most viable vaccine epitopes based on thresholds for percentile rank, immunogenicity, antigenicity, half-life, toxicity, IFNγ release, allergenicity, and stability. The efficacy of data was observed through world and regional population coverage of our vaccine design. Then, we obtained epitopes for optimized population coverage from PCOptim-CD, a modified version of our original Java-based program code PCOptim. Using 24 mutations on the KIT gene, 12 CD8+ epitopes and 21 CD4+ epitopes were obtained. The CD8+ dataset had a 98.55% world population coverage, while the CD4+ dataset had a 65.14% world population coverage. There were five CD4+ epitopes that overlapped with the top CD8+ epitopes. Strong binding to murine MHC molecules was found in four CD8+ and six CD4+ epitopes, demonstrating the feasibility of our results in preclinical murine vaccine trials. We then created three-dimensional (3D) models to visualize epitope-MHC complexes and TCR interactions. The final candidate is a non-toxic and non-allergenic multi-epitope vaccine against KIT mutations that cause AML. Further research would involve murine trials of the vaccine candidates on tumor cells causing AML.

Design of a Multi-Epitope Vaccine against Tuberculosis from Mycobacterium tuberculosis PE_PGRS49 and PE_PGRS56 Proteins by Reverse Vaccinology

Tuberculosis is a disease caused by Mycobacterium tuberculosis, representing the second leading cause of death by an infectious agent worldwide. The available vaccine against this disease has insufficient coverage and variable efficacy, accounting for a high number of cases worldwide. In fact, an estimated third of the world's population has a latent infection. Therefore, developing new vaccines is crucial to preventing it. In this study, the highly antigenic PE_PGRS49 and PE_PGRS56 proteins were analyzed. These proteins were used for predicting T- and B-cell epitopes and for human leukocyte antigen (HLA) protein binding efficiency. Epitopes GGAGGNGSLSS, FAGAGGQGGLGG, GIGGGTQSATGLG (PE_PGRS49), and GTGWNGGKGDTG (PE_PGRS56) were selected based on their best physicochemical, antigenic, non-allergenic, and non-toxic properties and coupled to HLA I and HLA II structures for in silico assays. A construct with an adjuvant (RS09) plus each epitope joined by GPGPG linkers was designed, and the stability of the HLA-coupled construct was further evaluated by molecular dynamics simulations. Although experimental and in vivo studies are still necessary to ensure its protective effect against the disease, this study shows that the vaccine construct is dynamically stable and potentially effective against tuberculosis.

Design of a Synthetic Long Peptide Vaccine Targeting HPV-16 and -18 Using Immunoinformatic Methods

Human papillomavirus types 16 and 18 cause the majority of cervical cancers worldwide. Despite the availability of three prophylactic vaccines based on virus-like particles (VLP) of the major capsid protein (L1), these vaccines are unable to clear an existing infection. Such infected persons experience an increased risk of neoplastic transformation. To overcome this problem, this study proposes an alternative synthetic long peptide (SLP)-based vaccine for persons already infected, including those with precancerous lesions. This new vaccine was designed to stimulate both CD8+ and CD4+ T cells, providing a robust and long-lasting immune response. The SLP construct includes both HLA class I- and class II-restricted epitopes, identified from IEDB or predicted using NetMHCPan and NetMHCIIPan. None of the SLPs were allergenic nor toxic, based on in silico studies. Population coverage studies provided 98.18% coverage for class I epitopes and 99.81% coverage for class II peptides in the IEDB world population's allele set. Three-dimensional structure ab initio prediction using Rosetta provided good quality models, which were assessed using PROCHECK and QMEAN4. Molecular docking with toll-like receptor 2 identified potential intrinsic TLR2 agonist activity, while molecular dynamics studies of SLPs in water suggested good stability, with favorable thermodynamic properties.

Design, in silico and pharmacological evaluation of a peptide inhibitor of BACE-1

Introduction: Alzheimer's disease (AD) is the main type of dementia, caused by the accumulation of amyloid plaques, formed by amyloid peptides after being processed from amyloid precursor protein (APP) by γ- and ß-secretases (BACE-1). Although amyloid peptides have been well established for AD, they have been found in other neurodegenerative diseases, such as Parkinson's disease, Lewy body dementia, and amyotrophic lateral sclerosis. Inhibitors of BACE-1 have been searched and developed, but clinical trials failed due to lack of efficacy or toxicity. Nevertheless, it is still considered a good therapeutic target, as it was proven to remove amyloid peptides and improve memory. Methods: In this work, we designed a peptide based on a sequence obtained from the marine fish Merluccius productus and evaluated it by molecular docking to verify its binding to BACE-1, which was tested experimentally by enzymatic kinetics and cell culture assays. The peptide was injected in healthy mice to study its pharmacokinetics and toxicity. Results: We could obtain a new sequence in which the first N-terminal amino acids and the last one bound to the catalytic site of BACE-1 and showed high stability and hydrophobicity. The synthetic peptide showed a competitive inhibition of BACE-1 and Ki = 94 nM, and when injected in differentiated neurons, it could reduce Aβ42o production. In plasma, its half-life is ∼1 h, clearance is 0.0015 μg/L/h, and Vss is 0.0015 μg/L/h. The peptide was found in the spleen and liver 30 min after injection and reduced its level after that, when it was quantified in the kidneys, indicating its fast distribution and urinary excretion. Interestingly, the peptide was found in the brain 2 h after its administration. Histological analysis showed no morphological alteration in any organ, as well as the absence of inflammatory cells, indicating a lack of toxicity. Discussion: We obtained a new BACE-1 inhibitor peptide with fast distribution to the tissues, without accumulation in any organ, but found in the brain, with the possibility to reach its molecular target, BACE-1, contributing to the reduction in the amyloid peptide, which causes amyloid-linked neurodegenerative diseases.

Study on the In Silico Screening and Characterization, Inhibition Mechanisms, Zinc-Chelate Activity, and Stability of ACE-Inhibitory Peptides Identified in Naked Oat Bran Albumin Hydrolysates

In this study, naked oat bran albumin hydrolysates (NOBAH) were subjected to gel chromatography with Sephadex G-15, reverse phase-high liquid performance separation, and UPLC-ESI-MS/MS identification. Six safe peptides including Gly-Thr-Thr-Gly-Gly-Met-Gly-Thr (GTTGGMGT), Gln-Tyr-Val-Pro-Phe (QYVPF), Gly-Ala-Ala-Ala-Ala-Leu-Val (GAAAALV), Gly-Tyr-His-Gly-His (GYHGH), Gly-Leu-Arg-Ala-Ala-Ala-Ala-Ala-Ala-Glu-Gly-Gly (GLRAAAAAAEGG), and Pro-Ser-Ser-Pro-Pro-Ser (PSSPPS) were identified. Next, in silico screening demonstrated that QYVPF and GYHGH had both angiotensin-I-converting enzyme (ACE) inhibition activity (IC50: 243.36 and 321.94 μmol/L, respectively) and Zinc-chelating ability (14.85 and 0.32 mg/g, respectively). The inhibition kinetics demonstrated that QYVPF and GYHGH were both uncompetitive inhibitors of ACE. Molecular docking showed that QYVPF and GYHGH could bind, respectively, three and five active residues of ACE with short hydrogen bonds (but not belonging to any central pocket). QYVPF and GYHGH could bind, respectively, twenty-two and eleven residues through hydrophobic interactions. Moreover, GYHGH was able to affect zinc tetrahedral coordination in ACE by interacting with His383. The inhibition activities of QYVPF and GYHGH toward ACE were relatively resistant to gastrointestinal digestion. GYHGH improved zinc solubility in the intestines (p > 0.05) because its amino and carboxyl groups were chelating sites for zinc ions. These results suggest the potential applications of naked oat peptides for potential antihypertension or zinc fortification.

Computational approaches for molecular characterization and structure-based functional elucidation of a hypothetical protein from Mycobacterium tuberculosis

Adaptation of infections and hosts has resulted in several metabolic mechanisms adopted by intracellular pathogens to combat the defense responses and the lack of fuel during infection. Human tuberculosis caused by Mycobacterium tuberculosis (MTB) is the world's first cause of mortality tied to a single disease. This study aims to characterize and anticipate potential antigen characteristics for promising vaccine candidates for the hypothetical protein of MTB through computational strategies. The protein is associated with the catalyzation of dithiol oxidation and/or disulfide reduction because of the protein's anticipated disulfide oxidoreductase properties. This investigation analyzed the protein's physicochemical characteristics, protein-protein interactions, subcellular locations, anticipated active sites, secondary and tertiary structures, allergenicity, antigenicity, and toxicity properties. The protein has significant active amino acid residues with no allergenicity, elevated antigenicity, and no toxicity.

Design of a multi-epitope Zika virus vaccine candidate - an in-silico study

Zika virus (ZIKV), an RNA virus, rapidly spreads Aedes mosquito-borne sickness. Currently, there are neither effective vaccines nor therapeutics available to prevent or treat ZIKV infection. In this study, to address these unmet medical needs, we aimed to design B- and T-cell candidate multi-epitope-based subunit against ZIKV using an in silico approach. In this study we applied immunoinformatics, molecular docking, and dynamic simulation assessments targeting the most immunogenic proteins; the capsid (C), envelope (E) proteins and the non-stuctural protein (NS1), described in our previous study, and which predicted immunodominant B and T cell epitopes. The final non-allergenic and highly antigenic multi-epitope was constituted of immunogenic screened-epitopes (3 CTL and 3 HTL) and the β-defensin as an adjuvant that have been linked using EAAAK, AAY, and GPGPG linkers, respectively. The final construct containing 143 amino acids was characterized for its allergenicity, antigenicity, and physiochemical properties; and found to be safe and immunogenic with a good prediction of solubility. The existence of IFN-γ epitopes asserts the capacity to trigger strong immune responses. Subsequently, the molecular docking among vaccine and immune receptors (TLR2/TLR4) was revealed with a good binding affinity with and stable molecular interactions. Molecular dynamics simulation confirmed the stability of the complexes. Finally, the construct was subjected to in silico cloning demonstrating the efficiently of its expression in E.coli. However, this study needs the experimental validation to demonstrate vaccine safety and efficacy.Communicated by Ramaswamy H. Sarma.

Optimization, characterization, comparison of self-assembly VLP of capsid protein L1 in yeast and reverse vaccinology design against human papillomavirus type 52

BACKGROUND

Vaccination is the one of the agendas of many countries to reduce cervical cancer caused by the Human papillomavirus. Currently, VLP-based vaccine is the most potent vaccine against HPV, which could be produced by a variety of expression systems. Our study focuses on a comparison of recombinant protein expression L1 HPV52 using two common yeasts, Pichia pastoris and Hansenula polymorpha that have been used for vaccine production on an industrial scale. We also applied bioinformatics approach using reverse vaccinology to design alternative multi-epitope vaccines in recombinant protein and mRNA types.

RESULTS

Our study found that P. pastoris relatively provided higher level of L1 protein expression and production efficiency compared to H. polymorpha in a batch system. However, both hosts showed self-assembly VLP formation and stable integration during protein induction. The vaccine we have designed exhibited high immune activation and safe in computational prediction. It is also potentially suitable for production in a variety of expression systems.

CONCLUSION

By monitoring the overall optimization parameter assessment, this study can be used as the basis reference for large-scale production of the HPV52 vaccine.

Advances in Computational and Bioinformatics Tools and Databases for Designing and Developing a Multi-Epitope-Based Peptide Vaccine

A vaccine is defined as a biologic preparation that trains the immune system, boosts immunity, and protects against a deadly microbial infection. They have been used for centuries to combat a variety of contagious illnesses by means of subsiding the disease burden as well as eradicating the disease. Since infectious disease pandemics are a recurring global threat, vaccination has emerged as one of the most promising tools to save millions of lives and reduce infection rates. The World Health Organization reports that immunization protects three million individuals annually. Currently, multi-epitope-based peptide vaccines are a unique concept in vaccine formulation. Epitope-based peptide vaccines utilize small fragments of proteins or peptides (parts of the pathogen), called epitopes, that trigger an adequate immune response against a particular pathogen. However, conventional vaccine designing and development techniques are too cumbersome, expensive, and time-consuming. With the recent advancement in bioinformatics, immunoinformatics, and vaccinomics discipline, vaccine science has entered a new era accompanying a modern, impressive, and more realistic paradigm in designing and developing next-generation strong immunogens. In silico designing and developing a safe and novel vaccine construct involves knowledge of reverse vaccinology, various vaccine databases, and high throughput techniques. The computational tools and techniques directly associated with vaccine research are extremely effective, economical, precise, robust, and safe for human use. Many vaccine candidates have entered clinical trials instantly and are available prior to schedule. In light of this, the present article provides researchers with up-to-date information on various approaches, protocols, and databases regarding the computational designing and development of potent multi-epitope-based peptide vaccines that can assist researchers in tailoring vaccines more rapidly and cost-effectively.

In silico design and immunoinformatics analysis of a universal multi-epitope vaccine against monkeypox virus

Monkeypox virus (MPXV) outbreaks have been reported in various countries worldwide; however, there is no specific vaccine against MPXV. In this study, therefore, we employed computational approaches to design a multi-epitope vaccine against MPXV. Initially, cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), linear B lymphocytes (LBL) epitopes were predicted from the cell surface-binding protein and envelope protein A28 homolog, both of which play essential roles in MPXV pathogenesis. All of the predicted epitopes were evaluated using key parameters. A total of 7 CTL, 4 HTL, and 5 LBL epitopes were chosen and combined with appropriate linkers and adjuvant to construct a multi-epitope vaccine. The CTL and HTL epitopes of the vaccine construct cover 95.57% of the worldwide population. The designed vaccine construct was found to be highly antigenic, non-allergenic, soluble, and to have acceptable physicochemical properties. The 3D structure of the vaccine and its potential interaction with Toll-Like receptor-4 (TLR4) were predicted. Molecular dynamics (MD) simulation confirmed the vaccine's high stability in complex with TLR4. Finally, codon adaptation and in silico cloning confirmed the high expression rate of the vaccine constructs in strain K12 of Escherichia coli (E. coli). These findings are very encouraging; however, in vitro and animal studies are needed to ensure the potency and safety of this vaccine candidate.

Purification, Identification, and Inhibitory Mechanisms of a Novel ACE Inhibitory Peptide from Torreya grandis

Torreya grandis meal has a high protein content and an appropriate amino acid ratio, making it an excellent protein source for producing ACE inhibitory peptides. To promote its application in food, medicine, and other fields, an alkaline protease hydrolysate of Torreya grandis was used in this study to isolate and identify a novel angiotensin-converting enzyme inhibitory peptide, VNDYLNW (VW-7), using ultrafiltration, gel chromatography purification, LC-MS/MS, and in silico prediction. The results show that the IC₅₀ value of VW-7 was 205.98 µM. The Lineweaver-Burk plot showed that VW-7 had a mixed-type inhibitory effect on ACE. Meanwhile, according to the results of molecular docking, VW-7 demonstrated a strong affinity for ACE (binding energy -10 kcal/mol). VW-7 was bound to ACE through multiple binding sites. In addition, VW-7 could remain active during gastrointestinal digestion in vitro. Nitric oxide (NO) generation in human endothelial cells could rise after receiving a pretreatment with VW-7. These results indicated that Torreya grandis meal protein can be developed into products with antihypertensive function, and VW-7 has broad application prospects in the field of antihypertensive.

An immunoinformatics approach to epitope-based vaccine design against PspA in Streptococcus pneumoniae

BACKGROUND

Streptococcus pneumoniae (SPN) is the agent responsible for causing respiratory diseases, including pneumonia, which causes severe health hazards and child deaths globally. Antibiotics are used to treat SPN as a first-line treatment, but nowadays, SPN is showing resistance to several antibiotics. A vaccine can overcome this global problem by preventing this deadly pathogen. The conventional methods of wet-laboratory vaccine design and development are an intense, lengthy, and costly procedure. In contrast, epitope-based in silico vaccine designing can save time, money, and energy. In this study, pneumococcal surface protein A (PspA), one of the major virulence factors of SPN, is used to design a multi-epitope vaccine.

METHODS

For designing the vaccine, the sequence of PspA was retrieved, and then, phylogenetic analysis was performed. Several CTL epitopes, HTL epitopes, and LBL epitopes of PspA were all predicted by using several bioinformatics tools. After checking the antigenicity, allergenicity, and toxicity scores, the best epitopes were selected for the vaccine construction, and then, physicochemical and immunological properties were analyzed. Subsequently, vaccine 3D structure prediction, refinement, and validation were performed. Molecular docking, molecular dynamic simulation, and immune simulation were performed to ensure the binding between HLA and TLR4. Finally, codon adaptation and in silico cloning were performed to transfer into a suitable vector.

RESULTS

The constructed multi-epitope vaccine showed a strong binding affinity with the receptor molecule TLR4. Analysis of molecular dynamic simulation, C-immune simulation, codon adaptation, and in silico cloning validated that our designed vaccine is a suitable candidate against SPN.

CONCLUSION

The in silico analysis has proven the vaccine as an alternative medication to combat against S. pneumoniae. The designated vaccine can be further tested in the wet lab, and a novel vaccine can be developed.

Preparation, Purification, and Identification of Novel Feather Keratin-Derived Peptides with Antioxidative and Xanthine Oxidase Inhibitory Activities

Feather keratin is an underappreciated protein resource of high quality, with limited bioavailability, and it urgently requires eco-friendly methods to enhance its value. Here, we report on the preparation, purification, and identification of novel peptides with antioxidant and xanthine oxidase (XOD) inhibitory activities from fermented feather broth, using Bacillus licheniformis 8-4. Two peptides, namely, DLCRPCGPTPLA (DA-12) and ANSCNEPCVR (AR-10), displayed remarkable 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical and 2,2'-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) radical scavenging abilities with half-maximal inhibitory concentrations (IC₅₀) values of 0.048, 0.034, and 0.95, 0.84 mg/mL, respectively. These values exceed those of the previously reported feather keratin-derived antioxidant peptides. Another peptide, GNQQVHLQSQDM (GM-12), demonstrated XOD activity inhibition, with an IC₅₀ value of 12.15 mg/mL, and it quenched the fluorescence of XOD. Furthermore, after simulating gastrointestinal digestion, DA-12, AR-10, and GM-12 retained their biological activities. Meanwhile, DA-12 and GM-12 showed an unexpected synergistic inhibition on XOD activity accompanied by fluorescence quenching. This study provides new insights into the potential applications of feather keratin, including functionalized feed with antioxidative and antigout (anti-hyperuricemia) activities.

Design peptide and multi-epitope protein vaccine candidates against monkeypox virus using reverse vaccinology approach: an in-silico study

Monkeypox is a zoonotic virus that has recently affected different countries worldwide. On July 23, 2022, the WHO declared the outbreak of monkeypox as a public health emergency of international concern. Surveillance studies conducted in Central Africa in the 1980s and later during outbreaks in the same region showed smallpox vaccines to be clinically somewhat effective against Monkeypox virus. However, there is no specific vaccine against this virus. This research used bioinformatics techniques to establish a novel multi-epitope vaccine candidate against Monkeypox that can induce a strong immune response. Five well-known antigenic proteins (E8L, A30L, A35R, A29L, and B21R) of the virus were picked and assessed as possible immunogenic peptides. Two suitable peptide candidates were selected according to bio-informatics analysis. Based upon in silico evaluation, two multi-epitope vaccine candidates (ALALAR and ALAL) were built with rich-epitope domains consisting of high-ranking T and B-cell epitopes. After predicting and evaluating the 3D structure of the protein candidates, the most efficient 3D models were considered for docking studies with Toll-like receptor 4 (TLR4) and the HLA-A * 11:01, HLA-A*01:01, HLA-A*02:01, HLA-A*03:01, HLA-A*07:02, HLA-A*15:01, HLA-A*30:01 receptors. Subsequently, molecular dynamics (MD) simulation of up to 150 nanoseconds was employed to assess the durability of the interaction of the vaccine candidates with immune receptors. MD studies showed that M5-HLA-A*11:01, ALAL-TLR4, and ALALAR-TLR4 complexes were stable during simulation. Analysis of the in silico outcomes indicates that the M5 peptide and ALAL and ALALAR proteins may be suitable vaccine candidates against the Monkeypox virus.Communicated by Ramaswamy H. Sarma.

Multi-pathogen based chimeric vaccine to fight against COVID-19 and concomitant coinfections

BACKGROUND

COVID-19 has proved to be a fatal disease of the year 2020, due to which thousands of people globally have lost their lives, and still, the infection cases are at a high rate. Experimental studies suggested that SARS-CoV-2 interacts with various microorganisms, and this coinfection is accountable for the augmentation of infection severity.

METHODS AND RESULTS

In this study, we have designed a multi-pathogen vaccine by involving the immunogenic proteins from S. pneumonia, H. influenza, and M. tuberculosis, as they are dominantly associated with SARS-CoV-2. A total of 8 antigenic protein sequences were selected to predict B-cell, HTL, and CTL epitopes restricted to the most prevalent HLA alleles. The selected epitopes were antigenic, non-allergenic, and non-toxic and were linked with adjuvant and linkers to make the vaccine protein more immunogenic, stable, and flexible. The tertiary structure, Ramachandran plot, and discontinuous B-cell epitopes were predicted. Docking and MD simulation study has shown efficient binding of the chimeric vaccine with the TLR4 receptor.

CONCLUSION

The in silico immune simulation analysis has shown a high level of cytokines and IgG after a three-dose injection. Hence, this strategy could be a better way to decrease the disease's severity and could be used as a weapon to prevent this pandemic.

Valorization of Salmo salar Skin Waste for the Synthesis of Angiotensin Converting Enzyme-1 (ACE1) Inhibitory Peptides

One of potential inhibitors which is widely used for the clinical treatment of COVID-19 in comorbid patients is Angiostensin Converting Enzyme-1 (ACE1) inhibitor. A safer peptide-based ACE1 inhibitor derived from salmon skin collagen, that is considered as the by-product of the fish processing industry have been investigated in this study. The inhibitory activity against ACE1 was examined using in vitro and in silico methods. In vitro analysis includes the extraction of acid-soluble collagen, characterization using FTIR, Raman, UV-Vis, XRD, cytotoxicity assay, and determination of inhibition against ACE1. In silico method visualizes binding affinity, molecular interaction, and inhibition type of intact collagen and active peptides derived from collagen against ACE1 using molecular docking. The results of FTIR spectra detected amide functional groups (A, B, I, II, III) and imine proline/hydroxyproline, while the results of Raman displayed peak absorption of amide I, amide III, proline/hydroxyproline ring, phenylalanine, and protein backbone. Furthermore, UV-Vis spectra showed typical collagen absorption at 230 nm and based on XRD data, the chain types in the samples were α-helix. ACE1 inhibition activity was obtained in a concentration-dependent manner where the highest was 82.83% and 85.84% at concentrations of 1000, and 2000 µg/mL, respectively, and showed very low cytotoxicity at the concentration less than 1000 µg/mL. In silico study showed an interaction between ACE1 and collagen outside the active site with the affinity of - 213.89 kcal/mol. Furthermore, the active peptides of collagen displayed greater affinity compared to lisinopril, namely HF (His-Phe), WYT (Trp-Tyr-Thr), and WF (Trp-Phe) of - 11.52; - 10.22; - 9.58 kcal/mol, respectively. The salmon skin-derived collagen demonstrated ACE1 inhibition activity with a non-competitive inhibition mechanism. In contrast, the active peptides were predicted as potent competitive inhibitors against ACE1. This study indicated that valorization of fish by-product can lead to the production of a promising bioactive compound to treat COVID-19 patient with diabetic comorbid.

Graphical Abstract

Machine learning-driven multifunctional peptide engineering for sustained ocular drug delivery

Sustained drug delivery strategies have many potential benefits for treating a range of diseases, particularly chronic diseases that require treatment for years. For many chronic ocular diseases, patient adherence to eye drop dosing regimens and the need for frequent intraocular injections are significant barriers to effective disease management. Here, we utilize peptide engineering to impart melanin binding properties to peptide-drug conjugates to act as a sustained-release depot in the eye. We develop a super learning-based methodology to engineer multifunctional peptides that efficiently enter cells, bind to melanin, and have low cytotoxicity. When the lead multifunctional peptide (HR97) is conjugated to brimonidine, an intraocular pressure lowering drug that is prescribed for three times per day topical dosing, intraocular pressure reduction is observed for up to 18 days after a single intracameral injection in rabbits. Further, the cumulative intraocular pressure lowering effect increases ~17-fold compared to free brimonidine injection. Engineered multifunctional peptide-drug conjugates are a promising approach for providing sustained therapeutic delivery in the eye and beyond.

Structural vaccinology-based design of multi-epitopes vaccine against Streptococcus gordonii and validation using molecular modeling and immune simulation approaches

Streptococcus gordonii is an oral bacterium colonizing the dental cavity and leading to plaque formation. This pervasive colonizer is also the etiologic agent of bacterial endocarditis and has a major role in infective endocarditis. The bacteria reach the heart through oral bleeding, leading to inflammation of cardiovascular valves. Over the past 50 years, it has shown a significant pathogenic role in immunocompromised and neutropenic patients. Since antibiotic resistance has created prophylaxis failure towards infective endocarditis, a potent therapeutic candidate is needed. Therefore, multi-epitopes vaccine offers advantages over the other approaches. Thus, herein, numerous molecular-omics tools were exploited to mine immunogenic peptides, i.e., T-cell and B-cell epitopes, and construct a vaccine sequence. Our findings revealed a total of 24 epitopes, including CTL, HTL, and B-cell are responsible for imparting immune responses, which were combined with the help of different linkers, and MEVC was constructed. Multifactorial validation of the candidate vaccine was performed to minimize the risk factors. The final sequence was docked with TLR2 to validate its conformation compatibility with receptor and long-term interactions stability. Our analysis revealed that the vaccine construct is immunogenic and non-allergenic. The construct also established various contacts with the immune receptor. Finally, the vaccine sequence was reverse-translated, optimized for codon usage, and analyzed for expression in the Escherichia coli K12 strain. Maximum expression was noted with a CAI score of 0.95. In silico immune simulation revealed that the antigen was neutralized on the 3rd day after injection. In conclusion, the current study warrants validation of the vaccine construct both in in vitro and in vivo models for accurate therapeutic intervention.

In silico and experimental methods for designing a potent anticancer arazyme-herceptin fusion protein in HER2-positive breast cancer

CONTEXT

Breast cancer is the most prevalent type of malignancies among women worldwide and is associated with serious physical and mental consequences. Current chemotherapies may lack successful outcomes; thus, the development of targeted recombinant immunotoxins is plausible. The predicted B cell and T cell epitopes of arazyme of the fusion protein are able to elicit immune response. The results of codon adaptation tool of herceptin-arazyme have improved from 0.4 to 1. The in silico immune simulation results showed significant response for immune cells. In conclusion, our findings show that the known multi-epitope fusion protein may activate humoral and cellular immune responses and maybe a possible candidate for breast cancer treatment.

METHODS

In this study, the selected monoclonal antibody constituting herceptin and the bacterial metalloprotease, arazyme, was used with different peptide linkers to design a novel fusion protein to predict different B cell and T cell epitopes by the means of the relevant databases. Modeler 10.1 and I-TASSER online server were used to predict and validate the 3D structure and then docked to HER2-receptor using HADDOCK2.4 web server. The molecular dynamics (MD) simulations of the arazyme-linker-herceptin-HER2 complex were performed by GROMACS 2019.6 software. The sequence of arazyme-herceptin was optimized for the expression in prokaryotic host using online servers and cloned into pET-28a plasmid. The recombinant pET28a was transferred into the Escherichia coli BL21DE3. Expression and binding affinity of arazyme-herceptin and arazyme to human breast cancer cell lines (SK-BR-3/HER2 + and MDA-MB-468/HER2 -) were validated by the SDS-PAGE and cell‑ELISA, respectively.

A multi-epitope based vaccine against the surface proteins expressed in cyst and trophozoite stages of parasite Entamoeba histolytica

Entamoeba histolytica, an anaerobic parasite, infects humans and other primates and causes fatal diseases, such as amebiasis, amebic liver abscesses, and many others. Thousands of people are infected and dying due to the need for a proper protective cure, especially in poor sanitizing regions, such as Latin America, Asia, and Africa. Around 10% of the world population is infected by E. histolytica every year. Consequently, novel preventive approaches are required to eliminate the threats of the parasite. A designed vaccine targeting the exposed proteins that are common between cyst and trophozoite stages of the parasite's life cycle would be an effective way to repress the impact of the parasite. Therefore, an in silico bioinformatics approach was performed to design an effective vaccine targeting surface proteins common between both stages of the parasite's life cycle using B-cell and T-cell epitopes. The epitopes derived from the conserved portions of the proteins and their corresponding isomers specific to the parasite suggested that the vaccine could benefit cross-protection. Furthermore, the three-dimensional structure of the designed vaccine was modelled, refined, and validated using multiple bioinformatics tools. The physiological properties and solubility were also predicted using different algorithmic tools and found to be highly soluble in nature. The vaccine was found interactcted with TLR immune receptors, and the stability was observed via dynamics simulation. Codon optimization and cloning were performed for expression analysis. Immune simulation prediction anticipated significant immune responses with a high IgG and IgM antibodies expression, Th and Tc cells population, B-cell population, memory cells, INF-γ, and IL-2 cytokines. Therefore, the constructed multi-epitope putative vaccine can effectively neutralize the parasite's harmful effects.

TNFepitope: A webserver for the prediction of TNF-α inducing epitopes

Tumor Necrosis Factor alpha (TNF-α) is a pleiotropic pro-inflammatory cytokine that is crucial in controlling the signaling pathways within the immune cells. Recent studies reported that higher expression levels of TNF-α are associated with the progression of several diseases, including cancers, cytokine release syndrome in COVID-19, and autoimmune disorders. Thus, it is the need of the hour to develop immunotherapies or subunit vaccines to manage TNF-α progression in various disease conditions. In the pilot study, we proposed a host-specific in-silico tool for predicting, designing, and scanning TNF-α inducing epitopes. The prediction models were trained and validated on the experimentally validated TNF-α inducing/non-inducing epitopes from human and mouse hosts. Firstly, we developed alignment-free (machine learning based models using composition-based features of peptides) methods for predicting TNF-α inducing peptides and achieved maximum AUROC of 0.79 and 0.74 for human and mouse hosts, respectively. Secondly, an alignment-based (using BLAST) method has been used for predicting TNF-α inducing epitopes. Finally, a hybrid method (combination of alignment-free and alignment-based method) has been developed for predicting epitopes. Hybrid approach achieved maximum AUROC of 0.83 and 0.77 on an independent dataset for human and mouse hosts, respectively. We have also identified potential TNF-α inducing peptides in different proteins of HIV-1, HIV-2, SARS-CoV-2, and human insulin. The best models developed in this study has been incorporated in the webserver TNFepitope (https://webs.iiitd.edu.in/raghava/tnfepitope/), standalone package and GitLab (https://gitlab.com/raghavalab/tnfepitope).

Identification and molecular interactions of novel ACE inhibitory peptides from rapeseed protein

Plant-derived bioactive peptides have drawn much attention because of their physiological functions. This study aimed to evaluate bioactive peptides in rapeseed protein and identify novel angiotensin Ⅰ-converting enzyme (ACE) inhibitory peptides using bioinformatics methods. A total of 24 kinds of bioactive peptides were encrypted in the 12 selected rapeseed proteins by analysis in BIOPEP-UWM, with higher occurrence frequency of dipeptidyl peptidase Ⅳ (DPP-Ⅳ) inhibitory peptides (0.5727-0.7487) and ACE inhibitory peptides (0.3500-0.5364). Novel ACE inhibitory peptides FQW, FRW and CPF were identified by in silico proteolysis, and they had strong inhibitory effects on ACE in vitro, showing IC₅₀ values of 44.84 ± 1.48 μM, 46.30 ± 1.39 μM and 131.35 ± 3.87 μM, respectively. Molecular docking results displayed that these three peptides were able to interact with ACE active site via hydrogen bonds and hydrophobic interactions, and coordinate with Zn²⁺. It suggested that rapeseed protein could be a good source for the production of ACE inhibitory peptides.

PP19128R, a Multiepitope Vaccine Designed to Prevent Latent Tuberculosis Infection, Induced Immune Responses In Silico and In Vitro Assays

Background: Latent tuberculosis infection (LTBI) is the primary source of active tuberculosis (ATB), but a preventive vaccine against LTBI is lacking. Methods: In this study, dominant helper T lymphocyte (HTL), cytotoxic T lymphocyte (CTL), and B-cell epitopes were identified from nine antigens related to LTBI and regions of difference (RDs). These epitopes were used to construct a novel multiepitope vaccine (MEV) based on their antigenicity, immunogenicity, sensitization, and toxicity. The immunological characteristics of the MEV were analyzed with immunoinformatics technology and verified by enzyme-linked immunospot assay and Th1/Th2/Th17 cytokine assay in vitro. Results: A novel MEV, designated PP19128R, containing 19 HTL epitopes, 12 CTL epitopes, 8 B-cell epitopes, toll-like receptor (TLR) agonists, and helper peptides, was successfully constructed. Bioinformatics analysis showed that the antigenicity, immunogenicity, and solubility of PP19128R were 0.8067, 9.29811, and 0.900675, respectively. The global population coverage of PP19128R in HLA class I and II alleles reached 82.24% and 93.71%, respectively. The binding energies of the PP19128R-TLR2 and PP19128R-TLR4 complexes were -1324.77 kcal/mol and -1278 kcal/mol, respectively. In vitro experiments showed that the PP19128R vaccine significantly increased the number of interferon gamma-positive (IFN-γ⁺) T lymphocytes and the levels of cytokines, such as IFN-γ, tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and IL-10. Furthermore, positive correlations were observed between PP19128R-specific cytokines in ATB patients and individuals with LTBI. Conclusions: The PP19128R vaccine is a promising MEV with excellent antigenicity and immunogenicity and no toxicity or sensitization that can induce robust immune responses in silico and in vitro. This study provides a vaccine candidate for the prevention of LTBI in the future.

Production of Food-Derived Bioactive Peptides with Potential Application in the Management of Diabetes and Obesity: A Review

The prevalence of diabetes mellitus and obesity is increasing worldwide. Bioactive peptides are naturally present in foods or in food-derived proteins. Recent research has shown that these bioactive peptides have an array of possible health benefits in the management of diabetes and obesity. First, this review will summarize the top-down and bottom-up production methods of the bioactive peptides from different protein sources. Second, the digestibility, bioavailability, and metabolic fate of the bioactive peptides are discussed. Last, the present review will discuss and explore the mechanisms by which these bioactive peptides help against obesity and diabetes based on in vitro and in vivo studies. Although several clinical studies have demonstrated that bioactive peptides are beneficial in alleviating diabetes and obesity, more double-blind randomized controlled trials are needed in the future. This review has provided novel insights into the potential of food-derived bioactive peptides as functional foods or nutraceuticals to manage obesity and diabetes.

A web server for predicting and scanning of IL-5 inducing peptides using alignment-free and alignment-based method

Interleukin-5 (IL-5) can act as an enticing therapeutic target due to its pivotal role in several eosinophil-mediated diseases. The aim of this study is to develop a model for predicting IL-5 inducing antigenic regions in a protein with high precision. All models in this study have been trained, tested and validated on experimentally validated 1907 IL-5 inducing and 7759 non-IL-5 inducing peptides obtained from IEDB. Our primary analysis indicates that IL-5 inducing peptides are dominated by certain residues like Ile, Asn, and Tyr. It was also observed that binders of a wide range of HLA alleles can induce IL-5. Initially, alignment-based methods have been developed using similarity and motif search. These alignment-based methods provide high precision but poor coverage. In order to overcome this limitation, we explore alignment-free methods which are mainly machine learning-based models. Firstly, models have been developed using binary profiles and eXtreme Gradient Boosting-based model achieved a maximum AUC of 0.59. Secondly, composition-based models have been developed and our dipeptide-based random forest model achieved a maximum AUC of 0.74. Thirdly, random forest model developed using selected 250 dipeptides and achieved AUC 0.75 and MCC 0.29 on validation dataset; best among alignment-free models. In order to improve the performance, we developed an ensemble or hybrid method that combined alignment-based and alignment-free methods. Our hybrid method achieved AUC 0.94 with MCC 0.60 on a validation/independent dataset. The best hybrid model developed in this study has been incorporated into the user-friendly web server and a standalone package named 'IL5pred' (https://webs.iiitd.edu.in/raghava/il5pred/).

Musculus senhousei as a promising source of bioactive peptides protecting against alcohol-induced liver injury

Alcohol-induced liver injury has become a leading risk for human health, however, effective strategies for the prevention or treatment are still lacking. Hence, the present study explored the potential of Musculus senhousei as a source of hepatoprotective peptides against alcoholic liver injury using in vitro, in vivo and in silico methods. Results indicated that Musculus senhousei peptides (MSP, extracted by simulated gastrointestinal digestion of cooked mussel) exhibited notable antioxidant (ABTS and DPPH assays) and alcohol dehydrogenase (ADH) stabilizing activity in vitro. The ingestion of MSP markedly alleviated alcohol-induced liver injury in mice, as indicated by the decrease of serum transaminases (AST and ALT). In line with in vitro assays, significantly increased hepatic ADH activity and activated antioxidative defense system (GSH, SOD, GSH-Px and CAT) were observed, whereas the oxidative stress (MDA) was decreased. Peptidomic analysis revealed over 6000 peptides with favorable amino acid compositions, and a total of 20 potentially novel peptides with bioactivity and bioavailability were excavated among 746 of the most influential peptides using an in silico strategy. Peptides (i.e. WLPMKL, WLWLPA, RLC and RCL) were further synthesized and validated in vitro to be bioactive. These findings suggest that Musculus senhousei can be an ideal source of bioactive peptides for the prevention of alcoholic liver injury.

A comparative study of the arazyme-based fusion proteins with various ligands for more effective targeting cancer therapy: an in-silico analysis

Background and purpose

Recently, the use of immunotoxins for targeted cancer therapy has been proposed, to find new anticancer drugs with high efficacy on tumor cells with minimal side effects on normal cells. we designed and compared several arazyme (AraA)-based fusion proteins with different ligands to choose the best-targeted therapy for interleukin 13 receptor alpha 2 (IL13Rα2)-overexpressed cancer cells. For this purpose, IL13Rα2 was selected as a receptor and IL13 and IL13.E13K were evaluated as native and mutant ligands, respectively. In addition, Pep-1 and A2b11 were chosen as the peptide ligands for targeted cancer therapy.

Experimental approach

Several bioinformatics servers were used for designing constructs and optimization. The structures of the chimeric proteins were predicted and verified by I-TASSER, Q-Mean, ProSA, Ramachandran plot, and Verify3D program. Physicochemical properties, toxicity, and antigenicity were predicted by ProtParam, ToxinPred, and VaxiJen. HawkDock, LigPlot⁺, and GROMACS software were used for docking and molecular dynamics simulation of the ligand-receptor interaction.

Findings/Results

The in silico results showed AraA-A2b11 has higher values of confidence score and Q-mean score was obtained for high-resolution crystal structures. All chimeric proteins were stable, non-toxic, and non-antigenic. AraA-(A(EAAAK)₄ALEA(EAAAK)₄A)₂-IL13 retained its natural structure and based on ligand-receptor docking and molecular dynamic analysis, the binding ability of AraA-(A(EAAAK)₄ALEA(EAAAK)₄A)₂-IL13 to IL13Rα2 was sufficiently strong.

Conclusion and implications

Based on the bioinformatics result AraA-(A(EAAAK)₄ALEA(EAAAK)₄A)₂-IL13 was a stable fusion protein with two separate domains and high affinity with the IL13Rα2 receptor. Therefore, AraA-(A(EAAAK)₄ALEA(EAAAK)₄A)₂-IL13 fusion protein could be a new potent candidate for target cancer therapy.

Bioinformatics analysis of structural protein to approach a vaccine candidate against Vibrio cholerae infection

The bacteria Vibrio cholerae causes cholera, an acute diarrheal infection that can lead to dehydration and even death. Over 100,000 people die each year as a result of epidemic diseases; vaccination has emerged as a successful strategy for combating cholera. This study uses bioinformatics tools to create a multi-epitope vaccine against cholera infection using five structural polyproteins from the V. cholerae (CTB, TCPA, TCPF, OMPU, and OMPW). The antigenic retrieved protein sequence were analyzed using BCPred and IEDB bioinformatics tools to predict B cell and T cell epitopes, respectively, which were then linked with flexible linkers together with an adjuvant to boost it immunogenicity. The construct has a theoretical PI of 6.09, a molecular weight of 53.85 kDa, and an estimated half-life for mammalian reticulocytes in vitro of 4.4 h. These results demonstrate the construct's longevity. The vaccine design was docked against the human toll-like receptor (TLR) to evaluate compatibility and effectiveness; also other additional post-vaccination assessments were carried out on the designed vaccine. Through in silico cloning, its expression was determined. The results show that it has a CAI value of 0.1 and GC contents of 58.97% which established the adequate expression and downstream processing of the vaccine construct, and our research demonstrated that the multi-epitope subunit vaccine exhibits antigenic characteristics. Additionally, we carried out an in silico immunological simulation to examine the immune reaction to an injection. Our results strongly suggest that the vaccine candidate on further validation would induce immune response against the V. cholerae infection.

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

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

A Systematic Review of Deep Learning Methodologies Used in the Drug Discovery Process with Emphasis on In Vivo Validation

The discovery and development of new drugs are extremely long and costly processes. Recent progress in artificial intelligence has made a positive impact on the drug development pipeline. Numerous challenges have been addressed with the growing exploitation of drug-related data and the advancement of deep learning technology. Several model frameworks have been proposed to enhance the performance of deep learning algorithms in molecular design. However, only a few have had an immediate impact on drug development since computational results may not be confirmed experimentally. This systematic review aims to summarize the different deep learning architectures used in the drug discovery process and are validated with further in vivo experiments. For each presented study, the proposed molecule or peptide that has been generated or identified by the deep learning model has been biologically evaluated in animal models. These state-of-the-art studies highlight that even if artificial intelligence in drug discovery is still in its infancy, it has great potential to accelerate the drug discovery cycle, reduce the required costs, and contribute to the integration of the 3R (Replacement, Reduction, Refinement) principles. Out of all the reviewed scientific articles, seven algorithms were identified: recurrent neural networks, specifically, long short-term memory (LSTM-RNNs), Autoencoders (AEs) and their Wasserstein Autoencoders (WAEs) and Variational Autoencoders (VAEs) variants; Convolutional Neural Networks (CNNs); Direct Message Passing Neural Networks (D-MPNNs); and Multitask Deep Neural Networks (MTDNNs). LSTM-RNNs were the most used architectures with molecules or peptide sequences as inputs.

Immunoinformatic prediction of potential immunodominant epitopes from cagW in order to investigate protection against Helicobacter pylori infection based on experimental consequences

Helicobacter pylori is a leading cause of stomach cancer and peptic ulcers. Thus, identifying epitopes in H. pylori antigens is important for disease etiology, immunological surveillance, enhancing early detection tests, and developing optimal epitope-based vaccines. We used immunoinformatic and computational methods to create a potential CagW epitope candidate for H. pylori protection. The cagW gene of H. pylori was amplified and cloned into pcDNA3.1 (+) for injection into the muscles of healthy BALB/c mice to assess the impact of the DNA vaccine on interleukin levels. The results will be compared to a control group of mice that received PBS or cagW-pcDNA3.1 (+) vaccinations. An analysis of CagW protein antigens revealed 8 CTL and 7 HTL epitopes linked with AYY and GPGPG, which were enhanced by adding B-defensins to the N-terminus. The vaccine's immunogenicity, allergenicity, and physiochemistry were validated, and its strong activation of TLRs (1, 2, 3, 4, and 10) suggests it is antigenic. An in-silico cloning and immune response model confirmed the vaccine's expression efficiency and predicted its impact on the immune system. An immunofluorescence experiment showed stable and bioactive cagW gene expression in HDF cells after cloning the whole genome into pcDNA3.1 (+). In vivo vaccination showed that pcDNA3.1 (+)-cagW-immunized mice had stronger immune responses and a longer plasmid DNA release window than control-plasmid-immunized mice. After that, bioinformatics methods predicted, developed, and validated the three-dimensional structure. Many online services docked it with Toll-like receptors. The vaccine was refined using allergenicity, antigenicity, solubility, physicochemical properties, and molecular docking scores. Virtual-reality immune system simulations showed an impressive reaction. Codon optimization and in-silico cloning produced E. coli-expressed vaccines. This study suggests a CagW epitopes-protected H. pylori infection. These studies show that the proposed immunization may elicit particular immune responses against H. pylori, but laboratory confirmation is needed to verify its safety and immunogenicity.

Identification of Bacterial Strains and Development of anmRNA-Based Vaccine to Combat Antibiotic Resistance in Staphylococcus aureus via In Vitro and In Silico Approaches

The emergence of antibiotic-resistant microorganisms is a significant concern in global health. Antibiotic resistance is attributed to various virulent factors and genetic elements. This study investigated the virulence factors of Staphylococcus aureus to create an mRNA-based vaccine that could help prevent antibiotic resistance. Distinct strains of the bacteria were selected for molecular identification of virulence genes, such as spa, fmhA, lukD, and hla-D, which were performed utilizing PCR techniques. DNA extraction from samples of Staphylococcus aureus was conducted using the Cetyl Trimethyl Ammonium Bromide (CTAB) method, which was confirmed and visualized using a gel doc; 16S rRNA was utilized to identify the bacterial strains, and primers of spa, lukD, fmhA, and hla-D genes were employed to identify the specific genes. Sequencing was carried out at Applied Bioscience International (ABI) in Malaysia. Phylogenetic analysis and alignment of the strains were subsequently constructed. We also performed an in silico analysis of the spa, fmhA, lukD, and hla-D genes to generate an antigen-specific vaccine. The virulence genes were translated into proteins, and a chimera was created using various linkers. The mRNA vaccine candidate was produced utilizing 18 epitopes, linkers, and an adjuvant, known as RpfE, to target the immune system. Testing determined that this design covered 90% of the population conservancy. An in silico immunological vaccine simulation was conducted to verify the hypothesis, including validating and predicting secondary and tertiary structures and molecular dynamics simulations to evaluate the vaccine’s long-term viability. This vaccine design may be further evaluated through in vivo and in vitro testing to assess its efficacy.

Vaccinomics Approach for Multi-Epitope Vaccine Design against Group A Rotavirus Using VP4 and VP7 Proteins

Rotavirus A is the most common cause of Acute Gastroenteritis globally among children <5 years of age. Due to a segmented genome, there is a high frequency of genetic reassortment and interspecies transmission which has resulted in the emergence of novel genotypes. There are concerns that monovalent (Rotarix: GlaxoSmithKline Biologicals, Rixensart, Belgium) and pentavalent (RotaTeq: MERCK & Co., Inc., Kenilworth, NJ, USA) vaccines may be less effective against non-vaccine strains, which clearly shows the demand for the design of a vaccine that is equally effective against all circulating genotypes. In the present study, a multivalent vaccine was designed from VP4 and VP7 proteins of RVA. Epitopes were screened for antigenicity, allergenicity, homology with humans and anti-inflammatory properties. The vaccine contains four B-cell, three CTL and three HTL epitopes joined via linkers and an N-terminal RGD motif adjuvant. The 3D structure was predicted and refined preceding its docking with integrin. Immune simulation displayed promising results both in Asia and worldwide. In the MD simulation, the RMSD value varied from 0.2 to 1.6 nm while the minimum integrin amino acid fluctuation (0.05-0.1 nm) was observed with its respective ligand. Codon optimization was performed with an adenovirus vector in a mammalian expression system. The population coverage analysis showed 99.0% and 98.47% in South Asia and worldwide, respectively. These computational findings show potential against all RVA genotypes; however, in-vitro/in-vivo screening is essential to devise a meticulous conclusion.

Insights into Common Octopus (Octopus vulgaris) Ink Proteome and Bioactive Peptides Using Proteomic Approaches

The common octopus (Octopus vulgaris) is nowadays the most demanded cephalopod species for human consumption. This species was also postulated for aquaculture diversification to supply its increasing demand in the market worldwide, which only relies on continuously declining field captures. In addition, they serve as model species for biomedical and behavioral studies. Body parts of marine species are usually removed before reaching the final consumer as by-products in order to improve preservation, reduce shipping weight, and increase product quality. These by-products have recently attracted increasing attention due to the discovery of several relevant bioactive compounds. Particularly, the common octopus ink has been described as having antimicrobial and antioxidant properties, among others. In this study, the advanced proteomics discipline was applied to generate a common octopus reference proteome to screen potential bioactive peptides from fishing discards and by-products such as ink. A shotgun proteomics approach by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) using an Orbitrap Elite instrument was used to create a reference dataset from octopus ink. A total of 1432 different peptides belonging to 361 non-redundant annotated proteins were identified. The final proteome compilation was investigated by integrated in silico studies, including gene ontology (GO) term enrichment, pathways, and network studies. Different immune functioning proteins involved in the innate immune system, such as ferritin, catalase, proteasome, Cu/Zn superoxide dismutase, calreticulin, disulfide isomerase, heat shock protein, etc., were found in ink protein networks. Additionally, the potential of bioactive peptides from octopus ink was addressed. These bioactive peptides can exert beneficial health properties such as antimicrobial, antioxidant, antihypertensive, and antitumoral properties and are therefore considered lead compounds for developing pharmacological, functional foods or nutraceuticals.

MERS virus spike protein HTL-epitopes selection and multi-epitope vaccine design using computational biology

MERS-CoV, a zoonotic virus, poses a serious threat to public health globally. Thus, it is imperative to develop an effective vaccination strategy for protection against MERS-CoV. Immunoinformatics and computational biology tools provide a faster and more cost-effective strategy to design potential vaccine candidates. In this work, the spike proteins from different strains of MERS-CoV were selected to predict HTL-epitopes that show affinity for T-helper MHC-class II HTL allelic determinant (HLA-DRB1:0101). The antigenicity and conservation of these epitopes among the selected spike protein variants in different MERS-CoV strains were analyzed. The analysis identified five epitopes with high antigenicity: QSIFYRLNGVGITQQ, DTIKYYSIIPHSIRS, PEPITSLNTKYVAPQ, INGRLTTLNAFVAQQ and GDMYVYSAGHATGTT. Then, a multi-epitope vaccine candidate was designed using linkers and adjuvant molecules. Finally, the vaccine construct was subjected to molecular docking with TLR5 (Toll-like receptor-5). The proposed vaccine construct had strong binding energy of -32.3 kcal/mol when interacting with TLR5.Molecular dynamics simulation analysis showed that the complex of the vaccine construct and TLR5 is stable. Analysis using in silico immune simulation also showed that the prospective multi-epitope vaccine design had the potential to elicit a response within 70 days, with the immune system producing cytokines and immunoglobulins. Finally, codon adaptation and in silico cloning analysis showed that the candidate vaccine could be expressed in the Escherichia coli K12 strain. Here we also designed support vaccine construct MEV-2 by using B-cell and CD8+ CTL epitopes to generate the complete immunogenic effect. This study opens new avenues for the extension of research on MERS vaccine development.Communicated by Ramaswamy H. Sarma.

Immunoinformatics aided approach for predicting potent cytotoxic T cell epitopes of respiratory syncytial virus

Respiratory syncytial virus (RSV) is an infectious viral pathogen that causing serious respiratory infection in adults and neonates. The only approved therapies for RSV are the monoclonal antibodies palivizumab and its derivative motavizumab. Both treatments are expensive and require a hospital setting for administration. A vaccine represents a safe, effective and cheaper alternative for preventing RSV infection. In silico prediction methods have proven to be valuable in speeding up the process of vaccine design. In this study, reverse vaccinology methods were used to predict the cytotoxic T lymphocytes (CTL) epitopes from the entire proteome of RSV strain A. From amongst 3402 predicted binders to 12 high frequency alleles from the Immune Epitope Database (IEDB), 567 had positive processing scores while 327 epitopes were predicted to be immunogenic. A thorough examination of the 327 epitopes for possible antigenicity, allergenicity and toxicity resulted in 95 epitopes with desirable properties. A BLASTp analysis revealed 94 unique and non-homologous epitopes that were subjected to molecular docking across the 12 high frequency alleles. The final dataset of 70 epitopes contained 13 experimentally proven and 57 unique epitopes from a total of 11 RSV proteins. From our findings on selected T-cell-specific RSV antigen epitopes, notably the four epitopes confirmed to exhibit stable binding by molecular dynamics. The prediction pipeline used in this study represents an effective way to screen the immunogenic epitopes from other pathogens.Communicated by Ramaswamy H. Sarma.

In silico designing of a novel polyvalent multi-subunit peptide vaccine leveraging cross-immunity against human visceral and cutaneous leishmaniasis: an immunoinformatics-based approach

CONTEXT

Leishmaniasis is a group of vector-borne infectious diseases caused by over 20 pathogenic Leishmania species that are endemic in many tropical and subtropical countries. The emergence of drug-resistant strains, the adverse side effects of anti-Leishmania drugs, and the absence of a preventative vaccination strategy threaten the sensitive population. Recently, many groups of researchers have exploited the field of reverse vaccinology to develop vaccines, focusing chiefly on inducing immunity against either visceral or cutaneous leishmaniasis.

METHODS

This present work involves retrieving twelve experimentally validated leishmanial antigenic protein sequences from the UniProt database, followed by their antigenicity profiling employing ANTIGENpro and Vaxijen 2.0 servers. MHC-binding epitopes for the same were predicted using both NetCTL 1.2 and SYFPEITHI servers, while epitopes for B cell were computed using ABCpred and BepiPred 2.0 servers. The screened epitopes with significantly higher scores were utilized for designing the vaccine construct with appropriate linkers and natural adjuvant. The secondary and tertiary structures of the synthetic peptide were determined by conditional random fields, shallow neural networks, and profile-profile threading alignment with iterative structure assembly simulations, respectively. The 3-D vaccine model was validated through CASP10-tested refinement and the MolProbity web server. Molecular docking and multi-scale normal mode analysis simulation were performed to analyze the best vaccine-TLR complex. Finally, computational immune simulation findings revealed promising cellular and humoral immune responses, suggesting that the engineered chimeric peptide is a potential broad-spectrum vaccine against visceral and cutaneous leishmaniasis.

Synthesis, modification and application of fish skin gelatin-based hydrogel as sustainable and versatile bioresource of antidiabetic peptide

Gelatin hydrogel is widely employed in various fields, however, commercially available gelatin hydrogels are mostly derived from mammalian which has many disadvantages due to the supply and ethical issues. In this study, the properties of hydrogels from fish-derived collagen fabricated with varying Glutaraldehyde (GA) determined. The antidiabetic properties of salmon gelatin (SG) and tilapia gelatin (TG) was also evaluated against α-glucosidase. Glutaraldehyde-crosslinked salmon gelatin and tilapia gelatin were used, and compared with different concentrations of GA by 0.05 %, 0.1 %, and 0.15 %. Water absorbency, swelling, porosity, pore size and water retention of the hydrogels were dependent on the degree of crosslinking. The synthesis of hydrogels was confirmed by FTIR study. Scanning electron microscope (SEM) observation showed that all hydrogels have a porous structure with irregular shapes and heterogeneous morphology. Performance tests showed that gelatin-GA 0.05 % mixture had the best performance. Antidiabetic bioactivity in vitro and in silico tests showed that the active peptides of SG and TG showed a high binding affinity to α-glucosidase enzyme. In conclusion, SG and TG cross-linked GA 0.05 % have the potential as an antidiabetic agent and as a useful option over mammalian-derived gelatin.

New Bioactive Peptides from the Mediterranean Seagrass Posidonia oceanica (L.) Delile and Their Impact on Antimicrobial Activity and Apoptosis of Human Cancer Cells

The demand for new molecules to counter bacterial resistance to antibiotics and tumor cell resistance is increasingly pressing. The Mediterranean seagrass Posidonia oceanica is considered a promising source of new bioactive molecules. Polypeptide-enriched fractions of rhizomes and green leaves of the seagrass were tested against Gram-positive (e.g., Staphylococcus aureus, Enterococcus faecalis) and Gram-negative bacteria (e.g., Pseudomonas aeruginosa, Escherichia coli), as well as towards the yeast Candida albicans. The aforementioned extracts showed indicative MIC values, ranging from 1.61 μg/mL to 7.5 μg/mL, against the selected pathogens. Peptide fractions were further analyzed through a high-resolution mass spectrometry and database search, which identified nine novel peptides. Some discovered peptides and their derivatives were chemically synthesized and tested in vitro. The assays identified two synthetic peptides, derived from green leaves and rhizomes of P. oceanica, which revealed interesting antibiofilm activity towards S. aureus, E. coli, and P. aeruginosa (BIC50 equal to 17.7 μg/mL and 70.7 μg/mL). In addition, the natural and derivative peptides were also tested for potential cytotoxic and apoptosis-promoting effects on HepG2 cells, derived from human hepatocellular carcinomas. One natural and two synthetic peptides were proven to be effective against the "in vitro" liver cancer cell model. These novel peptides could be considered a good chemical platform for developing potential therapeutics.

Design of a multi-epitopic vaccine against Epstein-Barr virus via computer-based methods

Background

Scientific findings have shown that Epstein-Barr virus (EBV) plays a key role in the development of some tumor diseases. Therefore, this study intends to take a practical step in controlling the pathogenicity of this virus by designing an effective vaccine based on the virus Capsid Envelope and Epstein–Barr nuclear immunogen (EBNA) Proteins Epitopes. Currently, there are no effective drugs or vaccines to treat or prevent EBV infection. So, we applied a computer-based strategy to design an epitope vaccine

Results

We designed a powerful multi-epitope peptide vaccine against EBV using in silico analysis. The vaccine is made up of 844 amino acids derived from three different types of proteins (Envelope, Capsid, EBNA) found in two different viral strains. responses. These epitopes have a high immunogenic capacity and are not likely to cause allergies. To enhance the vaccine immunogenicity, we used rOv-ASP-1, a recombinant Onchocerca volvulus activation associated protein-1, as an adjuvant and linked it to the vaccine’s N and C terminus. The physicochemical and immunological properties of the vaccine structure were evaluated. The proposed vaccine was stable, with a stability index of 33.57 and a pI of 10.10, according to bioinformatic predictions. Docking analysis revealed that the vaccine protein binds correctly with immunological receptors.

Conclusion

Our results demonstrated that the multi-epitope vaccine might be potentially immunogenic and induce humoral and cellular immune responses against EBV. This vaccine can interact appropriately with immunological receptors Also, it has a high-quality structure and suitable characteristics such as high stability.

Finding epitopes of Klebsiella pneumoniae outer membrane protein-K17 (OMPK17) and introducing a 25-mer peptide of it as a vaccine candidate

No approved vaccine exists for Klebsiella pneumoniae yet. Outer membrane protein-K17 (OMPK17) is involved in K. pneumoniae pathogenesis. No information has been found about OMPK17 dominant epitopes in the literature. Therefore, this study aimed to predict both T cell and B cell epitopes of K. pneumoniae OMPK17 via immunoinformatics approaches. Both T cell (class-I and II) and B cell (linear and discontinuous) epitopes of OMPK17 were predicted. Several screening analyses were performed including clustering, immunogenicity, human similarity, toxicity, allergenicity, conservancy, docking, and structural/physicochemical suitability. The results showed that some regions of OMPK17 have more potential as epitopes. The most possible epitopes were found via several analyses including the selection of higher-scoring epitopes, the epitopes predicted with more tools, more immunogenic epitopes, the epitopes capable of producing interferon-gamma, the epitopes with more dissimilarity to human peptides, and non-toxic and non-allergenic epitopes. By comparing the best T cell and B cell epitopes, we reached a 25-mer peptide containing both T cell (class-I and class-II) and B cell (linear) epitopes and comprising appropriate physicochemical characteristics that are required for K. pneumoniae vaccine development. The in vitro/in vivo study of this peptide is recommended to clarify its actual efficiency and efficacy.

Supplementary information

The online version contains supplementary material available at 10.1007/s11756-023-01371-0.

In Silico Methodologies to Improve Antioxidants' Characterization from Marine Organisms

Marine organisms have been reported to be valuable sources of bioactive molecules that have found applications in different industrial fields. From organism sampling to the identification and bioactivity characterization of a specific compound, different steps are necessary, which are time- and cost-consuming. Thanks to the advent of the -omic era, numerous genome, metagenome, transcriptome, metatranscriptome, proteome and microbiome data have been reported and deposited in public databases. These advancements have been fundamental for the development of in silico strategies for basic and applied research. In silico studies represent a convenient and efficient approach to the bioactivity prediction of known and newly identified marine molecules, reducing the time and costs of "wet-lab" experiments. This review focuses on in silico approaches applied to bioactive molecule discoveries from marine organisms. When available, validation studies reporting a bioactivity assay to confirm the presence of an antioxidant molecule or enzyme are reported, as well. Overall, this review suggests that in silico approaches can offer a valuable alternative to most expensive approaches and proposes them as a little explored field in which to invest.

Recent Advances in In Vitro and In Vivo Studies of Antioxidant, ACE-Inhibitory and Anti-Inflammatory Peptides from Legume Protein Hydrolysates

Consumption of legumes has been shown to enhance health and lower the risk of cardiovascular disease and specific types of cancer. ACE inhibitors, antioxidants, and synthetic anti-inflammatories are widely used today; however, they have several undesirable side effects. Thus, researchers have focused on finding ACE inhibitors, antioxidant, and anti-inflammatory peptides from natural sources, such as legumes. Recently, in vitro and in vivo research has shown the bioactive peptides generated from legume protein hydrolysates, such as antioxidant, anti-hypertensive, anticancer, anti-proliferative, anti-inflammatory, etc., in the context of different disease mitigation. Therefore, this review aims to describe the recent advances in in vitro and in vivo studies of antioxidant, anti-hypertensive and anti-inflammatory peptides isolated from legume-derived protein hydrolysates. The results indicated that antioxidant legumes peptides are characterized by short-chain sequence amino acids and possess anti-hypertensive properties by reducing systolic blood pressure (SBP) in spontaneously hypertensive rats (SHR).

Design and In Silico Validation of a Novel MZF-1-Based Multi-Epitope Vaccine to Combat Metastatic Triple Negative Breast Cancer

Immunotherapy is emerging as a potential therapeutic strategy for triple negative breast cancer (TNBC) owing to the immunogenic landscape of its tumor microenvironment. Interestingly, peptide-based cancer vaccines have garnered a lot of attention as one of the most promising cancer immunotherapy regimens. Thus, the present study intended to design a novel, efficacious peptide-based vaccine against TNBC targeting myeloid zinc finger 1 (MZF1), a transcription factor that has been described as an oncogenic inducer of TNBC metastasis. Initially, the antigenic peptides from MZF1 were identified and evaluated based on their likelihood to induce immunological responses. The promiscuous epitopes were then combined using a suitable adjuvant (50S ribosomal L7/L12 protein) and linkers (AAY, GPGPG, KK, and EAAAK) to reduce junctional immunogenicity. Furthermore, docking and dynamics analyses against TLR-4 and TLR-9 were carried out to understand more about their structural stability and integrity. Finally, the constructed vaccine was subjected to in silico cloning and immune simulation studies. Overall, the findings imply that the designed chimeric vaccine could induce strong humoral and cellular immune responses in the desired organism. In light of these findings, the final multi-epitope vaccine could be used as an effective prophylactic treatment for TNBC and may pave the way for future research.