• Lindsay Osman posted an update a month ago

    PANDORA’s rapid processing capabilities allow the production of twenty 3D models in roughly five minutes. The deep learning algorithms can readily access the substantial datasets provided by PANDORA, which is highly customizable, easy to install, and supports parallel processing.

    The major histocompatibility complex (MHC) protein family demonstrates remarkable polymorphism and polygenicity in humans. By binding peptides, which originate from the fragmentation of various pathogenic antigens, these molecules facilitate their presentation to T cells. The T cell receptors recognize epitopes, which are peptides, triggering an immune response. This chapter describes a docking protocol for predicting peptide binding to an MHC protein using the GOLD software. Using a combinatorial peptide library for the docking process, the protocol begins. The protocol’s conclusion is the derivation of a quantitative matrix (QM) that precisely accounts for the effect of each amino acid at every position within the peptide.

    Short peptides, frequently nine residues long, are recognized by CD8 T cells, which are presented by class I major histocompatibility complex (MHC I) molecules on the surface of antigen-presenting cells. The transporter associated with antigen processing (TAP) facilitates the transfer of epitope peptides from the cytosol, either directly or as N-terminal extended precursors up to 16 residues long, to MHC I molecules located within the endoplasmic reticulum. Enhancing the prediction of TAP binding affinity, this chapter describes the use of the TAPREG tool, which now allows for the identification of potential CD8 T cell epitope precursors that are subsequently transported by TAP. Public access to TAPREG is free of cost, found at http//imed.med.ucm.es/Tools/tapreg/.

    Mammalian cell-surface T cell epitopes undergo a multifaceted antigen processing and presentation procedure. A significant obstacle to epitope creation lies in C-terminal antigen processing, which determines the C-terminus of the definitive epitope and subsequently restricts the peptide pool for downstream presentation. We have previously shown (Amengual-Rigo and Guallar, Sci Rep 111(11)1-8, 2021) that NetCleave is a top-tier algorithm in predicting C-terminal processing, a crucial aspect for developing peptide-based vaccination strategies. The chapter presents a pipeline for maximizing the utility of NetCleave, an open-source, re-trainable algorithm for predicting C-terminal antigen processing by MHC-I and MHC-II pathways.

    Immunoinformatics is a new branch of science that is the outcome of the coming together of immunology and computer science. Developing multi-epitope vaccines necessitates accurate prediction methods for pinpointing B-cell epitopes. Discontinuous and linear B cell epitopes are the two types found. In the primary protein sequence, the residues that form linear epitopes are positioned contiguously. The three-dimensional arrangement of the protein spatially groups the amino acids that compose discontinuous epitopes. erstress signals inhibitor The interaction of antibodies with B cell epitopes found on antigens is an important aspect of immune responses to antigenic challenges, and this forms the foundation of several immunological procedures. The identification of B cell epitopes in an antigen is indispensable for the development of multi-epitope-based vaccines. Online tools are employed in this chapter to explain the prediction of linear B cell epitopes in an antigen, along with their allergenicity, antigenicity, and toxicity.

    Precisely anticipating B cell epitopes is critical to vaccine design and development, especially concerning preventative measures against emerging pathogens. Preventive vaccines largely function by inducing the production of extremely specific neutralizing antibodies. Online prediction tools, readily available, are the subject of this chapter, which examines their capacity to forecast B cell epitopes in proteins. By referencing the Immune Epitope Database (IEDB), a final assessment of these predictions is performed.

    EPIPOX, an online platform, facilitates the design of epitope-based vaccines to combat orthopoxviruses. The shared T cell epitopes of eight pathogenic orthopoxviruses, including variola minor and major, monkeypox, cowpox, and vaccinia viruses, are the basis of EPIPOX. Users in EPIPOX can choose T cell epitopes by considering the predicted binding to diverse major histocompatibility complex (MHC) proteins, together with various attributes potentially impacting their immunogenicity. EPIPOX, a tool among others, allows for the separation of epitopes, considering their arrangement within the virion and the antigens’ expression pattern over time. Overall, the annotations within EPIPOX are curated to allow for a calculated and effective strategy in the development of T-cell epitope-based vaccines. We present EPIPOX’s key aspects and exemplify its usage in the current chapter by isolating orthopoxvirus-specific T-cell epitopes, engineered to boost their immunogenicity. EPIPOX is publicly available and free of cost at the web address http//bio.med.ucm.es/epipox/.

    Tumor-specific neoantigens are important players in the success of tumor immunotherapy strategies. Developing accurate and efficient methods for predicting neoantigens is a matter of considerable interest. Utilizing next-generation sequencing data, TSNAD represents the first one-stop neoantigen prediction tool, with the TSNAdb database offering both anticipated and confirmed neoantigens, derived from pan-cancer immunogenomics analyses. Regarding clinical application, this chapter discusses TSNAD and TSNAdb in the context of neoantigens. The most recent iteration of TSNAD can be accessed through the provided URL: https//pgx.zju.edu.cn/tsnad At https://pgx.zju.edu.cn/tsnadb, the latest edition of TSNAdb is readily available.

    Allergic diseases are becoming increasingly common, presenting a serious public health challenge. Environmental and food allergens, transmitted through either the respiratory or gastrointestinal passages, are the principal catalysts for allergic diseases. Clinical progress in allergy management is constrained by the absence of sufficiently purified allergens for diagnostic purposes. In addition, immunotherapeutic vaccines require the alteration of allergen sequences and structures through the application of protein-engineering techniques. All these methods depend on the sequence, structure, and location of epitopes on allergens. For this reason, a considerable number of databases have been established to serve as archives of allergen molecular data. This chapter explores the five most important and commonly used allergen databases, valuable resources for molecular allergology researchers.

    Numerous strategies have been adopted to analyze responses directed at specific epitopes, both in non-self antigens, such as those arising from infectious diseases and allergies, and in self-antigens, including those pertaining to transplant rejection, autoimmune issues, and cancerous growth. Beyond this, epitope-focused data, and the associated immunological surroundings, are imperative for the development and refinement of predictive algorithms and workflows in the creation of customized vaccines and diagnostics. The methodology employed to create, disseminate, and freely provide the Immune Epitope Database (IEDB) and the Cancer Epitope Database and Analysis Resource (CEDAR) — two sister resources designed to specifically house this data — for the scientific community is described in this chapter.

    Computational advancements have spurred the discovery of vaccine prospects, such as epitope peptides. However, epitope peptides commonly exhibit low immunogenicity, requiring platforms possessing adjuvant properties to confirm the immunogenicity and antigenicity of vaccine subunit antigens in living organisms. Given their physicochemical properties, silicon microparticles are being researched as possible new vaccine delivery adjuvants. Methodologies for the creation and functionalization of mesoporous silicon microparticles (MSMPs), capable of carrying antigens such as viral peptides, proteins, or carbohydrates, are explored within this chapter. This strategy is particularly effective when delivering epitopes that have been identified through computational means.

    The development of effective vaccine design strategies relies heavily on the recognition and application of epitopes. Chemical conjugation is the standard method for attaching epitopes to a carrier protein. Our computational epitope grafting procedure, explained in detail in this chapter, seeks to pinpoint the most advantageous grafting location in a carrier protein/scaffold. An independently validated example of an epitope, the mota epitope, has been chosen for demonstration. Sufficient detail is presented in this chapter for the wet experimentalist to implement this computational methodology in their research objectives. The scripts/programs, comprehensively described in this chapter, are freely accessible using the provided link.

    CD4+ T cell immunogenicity, a cornerstone of immunity and with great promise for vaccine improvement, encounters a substantial hurdle in the form of antigen complexity. This chapter presents a thorough examination of a pipeline adaptable to nearly all complex antigens, overcoming the challenges they pose. Mass spectrometry procedures are applied to characterize antigens, revealing the various protein sources and their corresponding abundances. A reconstituted in vitro antigen processing system is employed, in conjunction with bioinformatics tools, to determine the priority order of candidate selections. Employing PBMCs from HLA-typed individuals, the immunogenicity of candidate peptides is ultimately validated ex vivo. Crucially prioritizing candidate epitopes, this protocol assembles the essential data needed for executing the entire pipeline.

    Human immune monitoring studies indicate a significantly more complex picture of T-cell epitope recognition than previously appreciated, which murine models have not adequately reflected. The complexity is heightened by the greater number of HLA loci in humans, the standard heterozygosity for these loci in the outbred population, and the numerous peptides each HLA restriction element can bind with a sufficient affinity for antigen presentation.

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