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1.
Sci Rep ; 14(1): 10842, 2024 05 12.
Article in English | MEDLINE | ID: mdl-38735993

ABSTRACT

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.


Subject(s)
Epitopes, T-Lymphocyte , Yellow Fever Vaccine , Yellow Fever , Yellow fever virus , Yellow Fever Vaccine/immunology , Yellow fever virus/immunology , Yellow fever virus/genetics , Humans , Yellow Fever/prevention & control , Yellow Fever/immunology , Epitopes, T-Lymphocyte/immunology , Epitopes, B-Lymphocyte/immunology , Vaccinology/methods , Models, Molecular , Vaccine Development , Molecular Dynamics Simulation , T-Lymphocytes, Cytotoxic/immunology
2.
Vet Immunol Immunopathol ; 271: 110754, 2024 May.
Article in English | MEDLINE | ID: mdl-38613865

ABSTRACT

In this computational study, we advanced the understanding of the antigenic properties of the NADC-34-like isolate of the Porcine Reproductive and Respiratory Syndrome Virus (PRRSV), named YC-2020, relevant in veterinary pathology. We utilized sequence comparison analyses of the M and N proteins, comparing them with those of NADC34, identifying substantial amino acid homology that allowed us to highlight conserved epitopes and crucial variants. Through the application of Clustal Omega for multiple sequence alignment and platforms like Vaxijen and AllerTOP for predicting antigenic and allergenic potential, our analyses revealed important insights into the conservation and variation of epitopes essential for the development of effective diagnostic tools and vaccines. Our findings, aligned with initial experimental studies, underscore the importance of these epitopes in the development of targeted immunodiagnostic platforms and significantly contribute to the management and control of PRRSV. However, further studies are required to validate the computational predictions of antigenicity for this new viral isolate. This approach underscores the potential of computational models to enable ongoing monitoring and control of PRRSV evolution in swine. While this study provides valuable insights into the antigenic properties of the novel PRRSV isolate YC-2020 through computational analysis, it is important to acknowledge the limitations inherent to in silico predictions, specifically, the absence of laboratory validation.


Subject(s)
Antigens, Viral , Porcine Reproductive and Respiratory Syndrome , Porcine respiratory and reproductive syndrome virus , Porcine respiratory and reproductive syndrome virus/immunology , Porcine respiratory and reproductive syndrome virus/genetics , Animals , Swine , Porcine Reproductive and Respiratory Syndrome/immunology , Porcine Reproductive and Respiratory Syndrome/virology , Antigens, Viral/immunology , Amino Acid Sequence , Computational Biology , Epitopes/immunology , Sequence Alignment/veterinary
3.
Viruses ; 15(10)2023 10 21.
Article in English | MEDLINE | ID: mdl-37896907

ABSTRACT

mRNA vaccines are a new class of vaccine that can induce potent and specific immune responses against various pathogens. However, the design of mRNA vaccines requires the identification and optimization of suitable antigens, which can be challenging and time consuming. Reverse vaccinology is a computational approach that can accelerate the discovery and development of mRNA vaccines by using genomic and proteomic data of the target pathogen. In this article, we review the advances of reverse vaccinology for mRNA vaccine design against SARS-CoV-2, the causative agent of COVID-19. We describe the steps of reverse vaccinology and compare the in silico tools used by different studies to design mRNA vaccines against SARS-CoV-2. We also discuss the challenges and limitations of reverse vaccinology and suggest future directions for its improvement. We conclude that reverse vaccinology is a promising and powerful approach to designing mRNA vaccines against SARS-CoV-2 and other emerging pathogens.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , COVID-19/prevention & control , COVID-19 Vaccines , Vaccinology/methods , Proteomics , mRNA Vaccines , Vaccines, Synthetic
5.
J Biomol Struct Dyn ; 41(8): 3321-3338, 2023 05.
Article in English | MEDLINE | ID: mdl-35285772

ABSTRACT

Mayaro virus (MAYV) is an arbovirus found in the Americas that can cause debilitating arthritogenic disease. Although it is an emerging virus, the only current approach is vector control, as there are no approved vaccines to prevent MAYV infection nor therapeutics to treat it. In search of an effective vaccine candidate against MAYV, we used immunoinformatics and molecular modeling to attempt to identify promiscuous T-cell epitopes of the nonstructural polyproteins (nsP1, nsP2, nsP3, and nsP4) from 127 MAYV genomes sequenced in the Americas (08 Bolivia, 72 Brazil, 04 French Guiana, 05 Haiti, 20 Peru, 04 Trinidad and Tobago, and 14 Venezuela). For this purpose, consensus sequences of 360 proteins were used to identify short protein sequences that can bind to MHC I class (MHC II). Our analysis revealed 56 potential MHC-I/TCD8+ (29 MHC-II/TCD4+) epitopes, but only 6 (16) TCD8+ (TCD4+) epitopes showed high antigenicity and conservation, non-allergenicity, non-toxicity, and excellent population coverage. Finally, classical and quantum mechanical calculations (QM:MM) were used to improve the quality of the docking calculations, with the QM part of the simulations performed using the density functional theory formalism (DFT). These results provide insights for the advancement of diagnostic platforms, vaccine development, and immunotherapeutic interventions.Communicated by Ramaswamy H. Sarma.


Subject(s)
Arboviruses , Molecular Docking Simulation , Vaccinology/methods , Epitopes, T-Lymphocyte , Vaccines, Subunit , Computational Biology/methods , Epitopes, B-Lymphocyte
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