A Structural In Silico Analysis of the Immunogenicity of L-Asparaginase from Penicillium cerradense.

L-asparaginase is an essential drug used to treat acute lymphoid leukemia (ALL), a cancer of high prevalence in children. Several adverse reactions associated with L-asparaginase have been observed, mainly caused by immunogenicity and allergenicity. Some strategies have been adopted, such as searching for new microorganisms that produce the enzyme and applying protein engineering. Therefore, this work aimed to elucidate the molecular structure and predict the immunogenic profile of L-asparaginase from Penicillium cerradense, recently revealed as a new fungus of the genus Penicillium and producer of the enzyme, as a motivation to search for alternatives to bacterial L-asparaginase. In the evolutionary relationship, L-asparaginase from P. cerradense closely matches Aspergillus species. Using in silico tools, we characterized the enzyme as a protein fragment of 378 amino acids (39 kDa), including a signal peptide containing 17 amino acids, and the isoelectric point at 5.13. The oligomeric state was predicted to be a homotetramer. Also, this L-asparaginase presented a similar immunogenicity response (T- and B-cell epitopes) compared to Escherichia coli and Dickeya chrysanthemi enzymes. These results suggest a potentially useful L-asparaginase, with insights that can drive strategies to improve enzyme production.

Differential effects of heating modes on the immunogenic potential of soy-derived peptides released after in vitro infant digestion.

During production of soy-based infant formula, soy protein undergoes heating processes. This study investigated the differential impact of heating modes on the immunogenic potential of peptides in soy protein digests. Wet or dry heating was applied, followed by in vitro gastrointestinal infant digestion. The released peptides were analyzed by LC-MS/MS. Bioinformatics tools were utilized to predict and identify potential linear B-cell and T-cell epitopes, as well as to explore cross-reactivity with other legumes. Subsequently, the peptide intensities of the same potential epitope across different experimental conditions were compared. As a result, we confirmed the previously observed enhancing effect of wet heating on infant digestion and inhibitory effect of dry heating. A total of 8,546 peptides were detected in the digests, and 6,684 peptides were with a score over 80. Among them, 29 potential T-cell epitopes and 27 potential B-cell epitopes were predicted. Cross-reactivity between soy and other legumes, including peanut, pea, chickpea, lentil, kidney bean, and lupine, was also detected. Overall, heating and digestion time could modulate the potential to trigger peptide-induced immune responses.

Computer-aided designing of a novel multi­epitope DNA vaccine against severe fever with thrombocytopenia syndrome virus.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne viral disease caused by the SFTS virus (Dabie bandavirus), which has become a substantial risk to public health. No specific treatment is available now, that calls for an effective vaccine. Given this, we aimed to develop a multi-epitope DNA vaccine through the help of bioinformatics. The final DNA vaccine was inserted into a special plasmid vector pVAX1, consisting of CD8+ T cell epitopes, CD4+ T cell epitopes and B cell epitopes (six epitopes each) screened from four genome-encoded proteins--nuclear protein (NP), glycoprotein (GP), RNA-dependent RNA polymerase (RdRp), as well as nonstructural protein (NSs). To ascertain if the predicted structure would be stable and successful in preventing infection, an immunological simulation was run on it. In conclusion, we designed a multi-epitope DNA vaccine that is expected to be effective against Dabie bandavirus, but in vivo trials are needed to verify this claim.

Designing of a multi-epitopes based vaccine against Haemophilius parainfluenzae and its validation through integrated computational approaches.

Haemophilus parainfluenzae is a Gram-negative opportunist pathogen within the mucus of the nose and mouth without significant symptoms and has an ability to cause various infections ranging from ear, eye, and sinus to pneumonia. A concerning development is the increasing resistance of H. parainfluenzae to beta-lactam antibiotics, with the potential to cause dental infections or abscesses. The principal objective of this investigation is to utilize bioinformatics and immuno-informatic methodologies in the development of a candidate multi-epitope Vaccine. The investigation focuses on identifying potential epitopes for both B cells (B lymphocytes) and T cells (helper T lymphocytes and cytotoxic T lymphocytes) based on high non-toxic and non-allergenic characteristics. The selection process involves identifying human leukocyte antigen alleles demonstrating strong associations with recognized antigenic and overlapping epitopes. Notably, the chosen alleles aim to provide coverage for 90% of the global population. Multi-epitope constructs were designed by using suitable linker sequences. To enhance the immunological potential, an adjuvant sequence was incorporated using the EAAAK linker. The final vaccine construct, comprising 344 amino acids, was achieved after the addition of adjuvants and linkers. This multi-epitope Vaccine demonstrates notable antigenicity and possesses favorable physiochemical characteristics. The three-dimensional conformation underwent modeling and refinement, validated through in-silico methods. Additionally, a protein-protein molecular docking analysis was conducted to predict effective binding poses between the multi-epitope Vaccine and the Toll-like receptor 4 protein. The Molecular Dynamics (MD) investigation of the docked TLR4-vaccine complex demonstrated consistent stability over the simulation period, primarily attributed to electrostatic energy. The docked complex displayed minimal deformation and enhanced rigidity in the motion of residues during the dynamic simulation. Furthermore, codon translational optimization and computational cloning was performed to ensure the reliability and proper expression of the multi-Epitope Vaccine. It is crucial to emphasize that despite these computational validations, experimental research in the laboratory is imperative to demonstrate the immunogenicity and protective efficacy of the developed vaccine. This would involve practical assessments to ascertain the real-world effectiveness of the multi-epitope Vaccine.

Advancing molecular modeling and reverse vaccinology in broad-spectrum yellow fever virus vaccine development.

Yellow fever outbreaks are prevalent, particularly in endemic regions. Given the lack of an established treatment for this disease, significant attention has been directed toward managing this arbovirus. In response, we developed a multiepitope vaccine designed to elicit an immune response, utilizing advanced immunoinformatic and molecular modeling techniques. To achieve this, we predicted B- and T-cell epitopes using the sequences from all structural (E, prM, and C) and nonstructural proteins of 196 YFV strains. Through comprehensive analysis, we identified 10 cytotoxic T-lymphocyte (CTL) and 5T-helper (Th) epitopes that exhibited overlap with B-lymphocyte epitopes. These epitopes were further evaluated for their affinity to a wide range of human leukocyte antigen system alleles and were rigorously tested for antigenicity, immunogenicity, allergenicity, toxicity, and conservation. These epitopes were linked to an adjuvant ( ß -defensin) and to each other using ligands, resulting in a vaccine sequence with appropriate physicochemical properties. The 3D structure of this sequence was created, improved, and quality checked; then it was anchored to the Toll-like receptor. Molecular Dynamics and Quantum Mechanics/Molecular Mechanics simulations were employed to enhance the accuracy of docking calculations, with the QM portion of the simulations carried out utilizing the density functional theory formalism. Moreover, the inoculation model was able to provide an optimal codon sequence that was inserted into the pET-28a( +) vector for in silico cloning and could even stimulate highly relevant humoral and cellular immunological responses. Overall, these results suggest that the designed multi-epitope vaccine can serve as prophylaxis against the yellow fever virus.

A conserved motif in the immune-subdominant RAP-1 related antigen of Babesia bovis contains a B-cell epitope recognized by antibodies from protected cattle.

Introduction: Babesia bovis, a tick-borne apicomplexan parasite causing bovine babesiosis, remains a significant threat worldwide, and improved and practical vaccines are needed. Previous studies defined the members of the rhoptry associated protein-1 (RAP-1), and the neutralization-sensitive rhoptry associated protein-1 related antigen (RRA) superfamily in B. bovis, as strong candidates for the development of subunit vaccines. Both RAP-1 and RRA share conservation of a group of 4 cysteines and amino acids motifs at the amino terminal end (NT) of these proteins. Methods and results: Sequence comparisons among the RRA sequences of several B. bovis strains and other Babesia spp parasites indicate a high level of conservation of a 15-amino acid (15-mer) motif located at the NT of the protein. BlastP searches indicate that the 15-mer motif is also present in adenylate cyclase, dynein, and other ATP binding proteins. AlphaFold2 structure predictions suggest partial exposure of the 15-mer on the surface of RRA of three distinct Babesia species. Antibodies in protected cattle recognize a synthetic peptide representing the 15-mer motif sequence in iELISA, and rabbit antibodies against the 15-mer react with the surface of free merozoites in immunofluorescence. Discussion and conclusion: The presence of the 15-mer-like regions in dynein and ATP-binding proteins provides a rationale for investigating possible functional roles for RRA. The demonstrated presence of a surface exposed B-cell epitope in the 15-mer motif of the B. bovis RRA, which is recognized by sera from protected bovines, supports its inclusion in future subunit epitope-based vaccines against B. bovis.

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.

Construction by artificial intelligence and immunovalidation of hypoallergenic mite allergen Der f 36 vaccine.

Background: The house dust mite (HDM) is widely recognized as the most prevalent allergen in allergic diseases. Allergen-specific immunotherapy (AIT) has been successfully implemented in clinical treatment for HDM. Hypoallergenic B-cell epitope-based vaccine designed by artificial intelligence (AI) represents a significant progression of recombinant hypoallergenic allergen derivatives. Method: The three-dimensional protein structure of Der f 36 was constructed using Alphafold2. AI-based tools were employed to predict B-cell epitopes, which were subsequently verified through IgE-reaction testing. Hypoallergenic Der f 36 was then synthesized, expressed, and purified. The reduced allergenicity was assessed by enzyme-linked immunosorbent assay (ELISA), immunoblotting, and basophil activation test. T-cell response to hypoallergenic Der f 36 and Der f 36 was evaluated based on cytokine expression in the peripheral blood mononuclear cells (PBMCs) of patients. The immunogenicity was evaluated and compared through rabbit immunization with hypoallergenic Der f 36 and Der f 36, respectively. The inhibitory effect of the blocking IgG antibody on the specific IgE-binding activity and basophil activation of Der f 36 allergen was also examined. Results: The final selected non-allergic B-cell epitopes were 25-48, 57-67, 107-112, 142-151, and 176-184. Hypoallergenic Der f 36 showed significant reduction in IgE-binding activity. The competitive inhibition of IgE-binding to Der f 36 was investigated using the hypoallergenic Der f 36, and only 20% inhibition could be achieved, which is greatly reduced when compared with inhibition by Der f 36 (98%). The hypoallergenic Der f 36 exhibited a low basophil-stimulating ratio similar to that of the negative control, and it could induce an increasing level of IFN-γ but not Th2 cytokines IL-5 and IL-13 in PBMCs. The vaccine-specific rabbit blocking IgG antibodies could inhibit the patients' IgE binding and basophil stimulation activity of Derf 36. Conclusion: This study represents the first application of an AI strategy to facilitate the development of a B-cell epitope-based hypoallergenic Der f 36 vaccine, which may become a promising immunotherapy for HDM-allergic patients due to its reduced allergenicity and its high immunogenicity in inducing blocking of IgG.

Chimeric Porcine Parvovirus VP2 Virus-like Particles with Epitopes of South African Serotype 2 Foot-and-Mouth Disease Virus Elicits Specific Humoral and Cellular Responses in Mice.

Southern Africa Territories 2 (SAT2) foot-and-mouth disease (FMD) has crossed long-standing regional boundaries in recent years and entered the Middle East. However, the existing vaccines offer poor cross-protection against the circulating strains in the field. Therefore, there is an urgent need for an alternative design approach for vaccines in anticipation of a pandemic of SAT2 Foot-and-mouth disease virus (FMDV). The porcine parvovirus (PPV) VP2 protein can embed exogenous epitopes into the four loops on its surface, assemble into virus-like particles (VLPs), and induce antibodies and cytokines to PPV and the exogenous epitope. In this study, chimeric porcine parvovirus VP2 VLPs (chimeric PPV-SAT2-VLPs) expressing the T-and/or B-cell epitopes of the structural protein VP1 of FMDV SAT2 were produced using the recombinant pFastBac™ Dual vector of baculoviruses in Sf9 and HF cells We used the Bac-to-Bac system to construct the recombinant baculoviruses. The VP2-VLP--SAT2 chimeras displayed chimeric T-cell epitope (amino acids 21-40 of VP1) and/or the B-cell epitope (amino acids 135-174) of SAT FMDV VP1 by substitution of the corresponding regions at the N terminus (amino acids 2-23) and/or loop 2 and/or loop 4 of the PPV VP2 protein, respectively. In mice, the chimeric PPV-SAT2-VLPs induced specific antibodies against PPV and the VP1 protein of SAT2 FMDV. The VP2-VLP-SAT2 chimeras induced specific antibodies to PPV and the VP1 protein specific epitopes of FMDV SAT2. In this study, as a proof-of-concept, successfully generated chimeric PPV-VP2 VLPs expressing epitopes of the structural protein VP1 of FMDV SAT2 that has a potential to prevent FMDV SAT2 and PPV infection in pigs.

Construction of novel multi-epitope-based diagnostic biomarker HP16118P and its application in the differential diagnosis of Mycobacterium tuberculosis latent infection.

Tuberculosis (TB) is an infectious disease that significantly threatens human health. However, the differential diagnosis of latent tuberculosis infection (LTBI) and active tuberculosis (ATB) remains a challenge for clinicians in early detection and preventive intervention. In this study, we developed a novel biomarker named HP16118P, utilizing 16 helper T lymphocyte (HTL) epitopes, 11 cytotoxic T lymphocyte (CTL) epitopes, and 8 B cell epitopes identified from 15 antigens associated with LTBI-RD using the IEDB database. We analyzed the physicochemical properties, spatial structure, and immunological characteristics of HP16118P using various tools, which indicated that it is a hydrophilic and relatively stable alkaline protein. Furthermore, HP16118P exhibited good antigenicity and immunogenicity, while being non-toxic and non-allergenic, with the potential to induce immune responses. We observed that HP16118P can stimulate the production of high levels of IFN-γ+ T lymphocytes in individuals with ATB, LTBI, and health controls. IL-5 induced by HP16118P demonstrated potential in distinguishing LTBI individuals and ATB patients (p=0.0372, AUC=0.8214, 95% CI [0.5843 to 1.000]) with a sensitivity of 100% and specificity of 71.43%. Furthermore, we incorporated the GM-CSF, IL-23, IL-5, and MCP-3 induced by HP16118P into 15 machine learning algorithms to construct a model. It was found that the Quadratic discriminant analysis model exhibited the best diagnostic performance for discriminating between LTBI and ATB, with a sensitivity of 1.00, specificity of 0.86, and accuracy of 0.93. In summary, HP16118P has demonstrated strong antigenicity and immunogenicity, with the induction of GM-CSF, IL-23, IL-5, and MCP-3, suggesting their potential for the differential diagnosis of LTBI and ATB.

[Novel tropomyosin consensus B and T epitopes involved in cross-reactivity between 10 different species. An in silico study]. / Nuevos epítopes B y T, consenso de tropomiosina involucradas en reactividad cruzada entre diez especies diferentes. Un estudio in silico.

OBJECTIVE: This study aimed to identify by in silico methods tropomyosin consensus B and T epitopes of shrimp species, house dust mites, insects, and nematodes associated with allergic diseases in tropical countries. METHODS: In silico analysis included tropomyosin from mites (Der p 10, Der f 10, Blo t 10), insects (Aed a 10, Per a 7, Bla g 7), shrimp (Lit v 1, Pen m 1, Pen a 1), and nematode (Asc l 3) all sequences were taken from the UniProt database. Linear IgE epitopes were predicted with AlgPred 2.0 and validated with BepiPred 3.0. MHC-II binding T cell epitopes were predicted using the IEDB server, which implements nine predictive methods (consensus method, combinatorial library, NN-align-2.3, NN- align-2.2, SMM-align, Sturniolo, NetMHCIIpan 3.1, and NetMHCIIpan 3.2) these predictions focused on 10 HLA-DR and 2 HLA-DQ alleles associated with allergic diseases. Subsequently, consensus B and T epitopes present in all species were identified. RESULTS: We identified 12 sequences that behaved as IgE-epitopes and B-cell epitopes, three of them: 160RKYDEVARKLAMVEA174, 192ELEEELRVVGNNLKSLEVSEEKAN215, 251KEVDRLEDELV261 were consensus in all species. Eleven peptides (T-epitopes) showed strong binding (percentile rank ≤ 2.0) to HLA-DRB1*0301, *0402, *0411, *0701, *1101, *1401, HLA-DQA1*03:01/DQB1*03:02, and HLA- DQA1*05:01/DQB1*02:01. Only two T-epitopes were consensus in all species: 167RKLAMVEADLERAEERAEt GEsKIVELEEELRV199, and 218EEeY KQQIKT LTaKLKEAEARAEFAERSV246. Subsequently, we identified 2 B and T epitope sequences and reached a consensus between species 167RKLAMVEA174 and 192ELEEELRV199. CONCLUSIONS: These data describe three sequences that may explain the IgE cross-reactivity between the analyzed species. In addition, the consensus B and T epitopes can be used for further in vitro investigations and may help to design multiple-epitope protein-based immunotherapy for tropomyosin-related allergic diseases.

OBJETIVO: Este estudio tuvo como objetivo identificar mediante métodos in silico epítopes B y T consenso de tropomiosina de especies de camarón, ácaros del polvo doméstico, insectos y nematodos asociados a enfermedades alérgicas en países tropicales. MÉTODOS: El análisis in silico incluyó tropomiosina de ácaros (Der p 10, Der f 10, Blo t 10), insectos (Aed a 10, Per a 7, Bla g 7), camarones (Lit v 1, Pen m 1, Pen a 1), y nematodo (Asc l 3). Todas las secuencias se tomaron de la base de datos UniProt. Los epítopes IgE lineales se predijeron con AlgPred 2.0 y se validaron con BepiPred 3.0. Los epítopes de células T de unión a MHC-II se predijeron utilizando el servidor IEDB, que implementa nueve métodos predictivos (método de consenso, biblioteca combinatoria, NN-align-2.3, NN-align-2.2, SMM-align, Sturniolo, NetMHCIIpan 3.1 y NetMHCIIpan 3.2). Estas predicciones se centraron en diez alelos HLA-DR y 2 HLA-DQ asociados con enfermedades alérgicas. Posteriormente, se identificaron epítopes consenso B y T presentes en todas las especies. RESULTADOS: Se identificaron 12 secuencias que se comportaron como epítopes de IgE y, también, como epítopes de células B. Tres de ellas: 160RKYDEVARKLAMVEA174, 192ELEEELRVVGNNLKSLEVSEEKAN213 y 251KEVDRLEDELV261, fueron consenso en todas las especies. Once péptidos mostraron una fuerte unión (rango percentil ≤ 2,0) a HLA-DRB1*0301, *0402, *0411, *0701, *1101, *1401 y a HLA HLA-DQA1*03:01/DQB1*03:02, o HLA-DQA1*05:01/DQB1*02:01. Solo se encontraron dos secuencias: 167RKLAMVEADLERAEERAEtGEsKIVELEEELRV199 con fuerte afinidad por HLA-DQA1*03:01/DQB1*03:02, y HLA-DQA1*05:01/DQB1*02:01. Se identificaron dos secuencias que son epítopos B y T, y son consenso entre especies: 167RKLAMVEA174 y 192ELEEELRV199. CONCLUSIONES: Estos datos describen tres secuencias que pueden explicar la reactividad cruzada de IgE entre las especies analizadas. Además, los epítopos B y T consenso se pueden usar para investigaciones in vitro adicionales, y pueden ayudar a diseñar inmunoterapia basada en proteínas de múltiepítopes para enfermedades alérgicas relacionadas con la tropomiosina.

In silico design of a novel multi-epitope vaccine against HCV infection through immunoinformatics approaches.

Infection with the hepatitis C virus (HCV) is one of the causes of liver cancer, which is the world's sixth most prevalent and third most lethal cancer. The current treatments do not prevent reinfection; because they are expensive, their usage is limited to developed nations. Therefore, a prophylactic vaccine is essential to control this virus. Hence, in this study, an immunoinformatics method was applied to design a multi-epitope vaccine against HCV. The best B- and T-cell epitopes from conserved regions of the E2 protein of seven HCV genotypes were joined with the appropriate linkers to design a multi-epitope vaccine. In addition, cholera enterotoxin subunit B (CtxB) was included as an adjuvant in the vaccine construct. This study is the first to present this epitopes-adjuvant combination. The vaccine had acceptable physicochemical characteristics. The vaccine's 3D structure was predicted and validated. The vaccine's binding stability with Toll-like receptor 2 (TLR2) and TLR4 was confirmed using molecular docking and molecular dynamics (MD) simulation. The immune simulation revealed the vaccine's efficacy by increasing the population of B and T cells in response to vaccination. In silico expression in Escherichia coli (E. coli) was also successful.

A novel linear B cell epitope of the canine coronavirus nucleocapsid protein identified by a monoclonal antibody.

The infection of canine coronavirus (CCoV) causes a highly contagious disease in dogs with acute gastroenteritis. The efficient serological diagnostics is critical for controlling the disease caused by CCoV. Nucleocapsid (N) protein of CCoV is an important target for developing serological approaches. However, little is known about the antigenic sites in the N protein of CCoV. In this study, we generated a monoclonal antibody (mAb) against the N protein of CCoV, designated as 13E8, through the fusion of the sp2/0 cells with the spleen cells from a mouse immunized with the purified recombinant GST-N protein. Epitope mapping revealed that mAb 13E8 recognized a novel linear B cell epitope in N protein at 294-314aa (named as EP-13E8) by using a serial of truncated N protein through Western blot and ELISA. Sequence analysis showed that the sequence of EP-13E8 was highly conserved (100 %) among different CCoV strains analyzed, but exhibited a low similarity (31.8-63.6 %) with the responding sequence in other coronaviruses of the same genus such as FCoV, PEDV and HCoV except for TGEV (95.5 % identity). Structural assay suggested that the epitope of EP-13E8 were located in the close proximity on the surface of the N protein. Overall, the mAb 13E8 against N protein generated and its epitope EP-13E8 identified here paid the way for further developing epitope-based serological diagnostics for CCoV.

Immunoinformatics and computational approaches driven designing a novel vaccine candidate against Powassan virus.

Powassan virus (POWV) is an arthropod-borne virus (arbovirus) capable of causing severe illness in humans for severe neurological complications, and its incidence has been on the rise in recent years due to climate change, posing a growing public health concern. Currently, no vaccines to prevent or medicines to treat POWV disease, emphasizing the urgent need for effective countermeasures. In this study, we utilize bioinformatics approaches to target proteins of POWV, including the capsid, envelope, and membrane proteins, to predict diverse B-cell and T-cell epitopes. These epitopes underwent screening for critical properties such as antigenicity, allergenicity, toxicity, and cytokine induction potential. Eight selected epitopes were then conjugated with adjuvants using various linkers, resulting in designing of a potentially stable and immunogenic vaccine candidate against POWV. Moreover, molecular docking, molecular dynamics simulations, and immune simulations revealed a stable interaction pattern with the immune receptor, suggesting the vaccine's potential to induce robust immune responses. In conclusion, our study provided a set of derived epitopes from POWV's proteins, demonstrating the potential for a novel vaccine candidate against POWV. Further in vitro and in vivo studies are warranted to advance our efforts and move closer to the goal of combatting POWV and related arbovirus infections.

Enhancing explainable SARS-CoV-2 vaccine development leveraging bee colony optimised Bi-LSTM, Bi-GRU models and bioinformatic analysis.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a single-stranded RNA virus that caused the outbreak of the coronavirus disease 2019 (COVID-19). The COVID-19 outbreak has led to millions of deaths and economic losses globally. Vaccination is the most practical solution, but finding epitopes (antigenic peptide regions) in the SARS-CoV-2 proteome is challenging, costly, and time-consuming. Here, we proposed a deep learning method based on standalone Recurrent Neural networks to predict epitopes from SARS-CoV-2 proteins easily. We optimised the standalone Bidirectional Long Short-Term Memory (Bi-LSTM) and Bidirectional Gated Recurrent Unit (Bi-GRU) with a bioinspired optimisation algorithm, namely, Bee Colony Optimization (BCO). The study shows that LSTM-based models, particularly BCO-Bi-LSTM, outperform all other models and achieve an accuracy of 0.92 and AUC of 0.944. To overcome the challenge of understanding the model predictions, explainable AI using the Shapely Additive Explanations (SHAP) method was employed to explain how Blackbox models make decisions. Finally, the predicted epitopes led to the development of a multi-epitope vaccine. The multi-epitope vaccine effectiveness evaluation is based on vaccine toxicity, allergic response risk, and antigenic and biochemical characteristics using bioinformatic tools. The developed multi-epitope vaccine is non-toxic and highly antigenic. Codon adaptation, cloning, gel electrophoresis assess genomic sequence, protein composition, expression and purification while docking and IMMSIM servers simulate interactions and immunological response, respectively. These investigations provide a conceptual framework for developing a SARS-CoV-2 vaccine.

T and B cell epitope analysis for the immunogenicity evaluation and mitigation of antibody-based therapeutics.

The surge in the clinical use of therapeutic antibodies has reshaped the landscape of pharmaceutical therapy for many diseases, including rare and challenging conditions. However, the administration of exogenous biologics could potentially trigger unwanted immune responses such as generation of anti-drug antibodies (ADAs). Real-world experiences have illuminated the clear correlation between the ADA occurrence and unsatisfactory therapeutic outcomes as well as immune-related adverse events. By retrospectively examining research involving immunogenicity analysis, we noticed the growing emphasis on elucidating the immunogenic epitope profiles of antibody-based therapeutics aiming for mechanistic understanding the immunogenicity generation and, ideally, mitigating the risks. As such, we have comprehensively summarized here the progress in both experimental and computational methodologies for the characterization of T and B cell epitopes of therapeutics. Furthermore, the successful practice of epitope-driven deimmunization of biotherapeutics is exceptionally highlighted in this article.

In silico designed novel multi-epitope mRNA vaccines against Brucella by targeting extracellular protein BtuB and LptD.

Brucella, a gram-negative intracellular bacterium, causing Brucellosis, a zoonotic disease with a range of clinical manifestations, from asymptomatic to fever, fatigue, loss of appetite, joint and muscle pain, and back pain, severe patients have developed serious diseases affecting various organs. The mRNA vaccine is an innovative type of vaccine that is anticipated to supplant traditional vaccines. It is widely utilized for preventing viral infections and for tumor immunotherapy. However, research regarding its effectiveness in preventing bacterial infections is limited. In this study, we analyzed the epitopes of two proteins of brucella, the TonB-dependent outer membrane receptor BtuB and the LPS assembly protein LptD, which is involved in nutrient transport and LPS synthesis in Brucella. In order to effectively stimulate cellular and humoral immunity, we utilize a range of immunoinformatics tools such as VaxiJen, AllergenFPv.1.0 and SignalP 5.0 to design proteins. Finally, five cytotoxic T lymphocyte (CTL) cell epitopes, ten helper T lymphocyte (HTL) cell epitopes, and eight B cell epitopes were selected to construct the vaccine. Computer simulations are also used to verify the immune response of the vaccine. The codon optimization, in silico cloning showed that the vaccine can efficiently transcript and translate in E. coli. The secondary structure of mRNA vaccines and the secondary and tertiary structures of vaccine peptides were predicted and then docked with TLR-4. Finally, the stability of the developed vaccine was confirmed through molecular dynamics simulation. These analyses showed that the design the multi-epitope mRNA vaccine could potentially target extracellular protein of prevalent Brucella, which provided novel strategies for developing the vaccine.

Single-residue linear and conformational B cell epitopes prediction using random and ESM-2 based projections.

B cell epitope prediction methods are separated into linear sequence-based predictors and conformational epitope predictions that typically use the measured or predicted protein structure. Most linear predictions rely on the translation of the sequence to biologically based representations and the applications of machine learning on these representations. We here present CALIBER 'Conformational And LInear B cell Epitopes pRediction', and show that a bidirectional long short-term memory with random projection produces a more accurate prediction (test set AUC=0.789) than all current linear methods. The same predictor when combined with an Evolutionary Scale Modeling-2 projection also improves on the state of the art in conformational epitopes (AUC = 0.776). The inclusion of the graph of the 3D distances between residues did not increase the prediction accuracy. However, the long-range sequence information was essential for high accuracy. While the same model structure was applicable for linear and conformational epitopes, separate training was required for each. Combining the two slightly increased the linear accuracy (AUC 0.775 versus 0.768) and reduced the conformational accuracy (AUC = 0.769).

Identification of potential vaccine targets for elicitation of host immune cells against SARS-CoV-2 by reverse vaccinology approach.

The COVID-19 pandemic has emerged as a critical global health crisis, demanding urgent and effective strategies for containment. While some knowledge exists about epitope sequences recognized by human immune cells and their activation of CD8+ T cells within the HLA context, comprehensive information remains limited. This study employs reverse vaccinology to explore antigenic HLA-restricted T-cell epitopes capable of eliciting durable immunity. Screening reveals 187 consensus epitopes, with 23 offering broad population coverage worldwide, spanning over 5000 HLA alleles. Sequence alignment analysis highlights the genetic distinctiveness of these peptides from Homo sapiens and their intermediate to high TAP binding efficiency. Notably, these epitopes share 100 % sequence identity across strains from nine countries, indicating potential for a uniform protective immune response among diverse ethnic populations. Docking simulations further confirm their binding capacity with the HLA allele, validating them as promising targets for SARS-CoV-2 immune recognition. The anticipated epitopes are connected with suitable linkers and adjuvant, and then assessed for its translational efficacy within a bacterial expression vector through computational cloning. Through docking, it is observed that the chimeric vaccine construct forms lasting hydrogen bonds with Toll-like receptor (TLR4), while immune simulation illustrates an increased cytotoxic response aimed at CD8+ T cells. This comprehensive computational analysis suggests the chimeric vaccine construct's potential to provoke a robust immune response against SARS-CoV-2. By delineating these antigenic fragments, our study offers valuable insights into effective vaccine and immunotherapy development against COVID-19, contributing significantly to global efforts in combating this infectious threat.

Production and immunological characterization of the novel single-chain variable fragment (scFv) antibodies against the epitopes on Opisthorchis viverrini cathepsin F (OvCatF).

BACKGROUND: Opisthorchis viverrini infection is a significant health problem in several countries, especially Southeast Asia. The infection causes acute gastro-hepatic symptoms and also long-term infection leading to carcinogenesis of an aggressive bile duct cancer (cholangiocarcinoma; CCA). Hence, the early diagnosis of O. viverrini infection could be the way out of this situation. Still, stool examination by microscopic-based methods, the current diagnostic procedure is restricted by low parasite egg numbers in the specimen and unprofessional laboratorians. The immunological procedure provides a better chance for diagnosis of the infection. Hence, this study aims to produce single-chain variable fragment (scFv) antibodies for use as a diagnostic tool for O. viverrini infection. METHODS: This study uses phage display technologies to develop the scFv antibodies against O. viverrini cathepsin F (OvCatF). The OvCatF-deduced amino acid sequence was analyzed and predicted for B-cell epitopes used for short peptide synthesis. The synthetic peptides were used to screen the phage library simultaneously with OvCatF recombinant protein (rOvCatF). The potentiated phages were collected, rescued, and reassembled in XL1-blue Escherichia coli (E. coli) as a propagative host. The positive clones of phagemids were isolated, and the single-chain variable (scFv) fragments were sequenced, computationally predicted, and molecular docked. The complete scFv fragments were digested from the phagemid, subcloned into the pOPE101 expression vector, and expressed in XL1-blue E. coli. Indirect ELISA and Western analysis were used to verify the detection efficiency. RESULTS: The scFv phages specific to OvCatF were successfully isolated, subcloned, and produced as a recombinant protein. The recombinant scFv antibodies were purified and refolded to make functional scFv. The evaluation of specific recognition of the particular epitopes and detection limit results by both computational and laboratory performances demonstrated that all three recombinant scFv antibodies against OvCatF could bind specifically to rOvCatF, and the lowest detection concentration in this study was only one hundred nanograms. CONCLUSION: Our produced scFv antibodies will be the potential candidates for developing a practical diagnostic procedure for O. viverrini infection in humans in the future.