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PubMed2026

Immunoinformatics Approach for Optimization of Targeted Vaccine Design: New Paradigm in Clinical Trials and Healthcare Management.

INTRODUCTION: The immunoinformatics approach combines bioinformatics and computational tools, offering a revolutionary method for improving vaccine development by analyzing immune responses at the molecular level. Immunoinformatics enables the creation of customized vaccines designed for specific infections or cancer cells. OBJECTIVE: The primary objective of immunoinformatics is to enhance the vaccine development process by predicting and boosting the body's immune response. It aims to identify potential immunogenic epitopes and biomarkers that are important for creating vaccines with greater specificity and efficacy, especially when dealing with large-scale data. METHODS: Immunoinformatics utilizes a combination of proteomic, genomic, and epigenomic data, as well as machine learning algorithms and artificial intelligence techniques. These tools predict how various immunological components, e.g., T-cell and B-cell epitopes, interact with the immune system. This approach allows researchers to avoid traditional trial-and-error methods, enabling the efficient identification of potential vaccine candidates. Additionally, personalized vaccines can be developed by considering individual genetic and immunological characteristics. RESULTS: The use of immunoinformatics techniques accelerates the screening of vaccine candidates, enhances patient stratification, and optimizes formulations for clinical trials. This approach has been shown to improve vaccine safety, efficacy, and development speed. It also holds promise for managing healthcare on a large scale by producing vaccines tailored to specific populations, thereby improving the overall effectiveness of vaccination programs. CONCLUSION: Immunoinformatics represents a transformative approach to vaccine research, improving clinical trial efficiency and enabling the development of more reliable, flexible, and personalized vaccines. This approach has the potential to significantly enhance global healthcare outcomes by accelerating the vaccine development process and optimizing vaccination strategies.

Immunoinformatics↗
PubMed2005

IMGT, the international ImMunoGeneTics information system: a standardized approach for immunogenetics and immunoinformatics.

IMGT, the international ImMunoGeneTics information system http://imgt.cines.fr, was created in 1989 by the Laboratoire d'ImmunoGénétique Moléculaire (LIGM) (Université Montpellier II and CNRS) at Montpellier, France. IMGT is a high quality integrated knowledge resource specialized in immunoglobulins (IG), T cell receptors (TR), major histocompatibility complex (MHC) of human and other vertebrates, and related proteins of the immune system (RPI) of any species which belong to the immunoglobulin superfamily (IgSF) and to the MHC superfamily (MhcSF). IMGT consists of five databases, ten on-line tools and more than 8,000 HTML pages of Web resources. IMGT provides a common access to standardized data from genome, genetics, proteome and three-dimensional structures. The accuracy and the consistency of IMGT data are based on IMGT-ONTOLOGY, a semantic specification of terms to be used in immunogenetics and immunoinformatics. IMGT-ONTOLOGY comprises six main concepts: IDENTIFICATION, CLASSIFICATION, DESCRIPTION, NUMEROTATION, ORIENTATION and OBTENTION. Based on these concepts, the controlled vocabulary and the annotation rules necessary for the immunogenetics data identification, classification, description and numbering and for the management of IMGT knowledge are defined in the IMGT Scientific chart. IMGT is the international reference in immunogenetics and immunoinformatics for medical research (repertoire analysis of the IG antibody sites and of the TR recognition sites in autoimmune and infectious diseases, AIDS, leukemias, lymphomas, myelomas), veterinary research (IG and TR repertoires in farm and wild life species), genome diversity and genome evolution studies of the adaptive immune responses, biotechnology related to antibody engineering (single chain Fragment variable (scFv), phage displays, combinatorial libraries, chimeric, humanized and human antibodies), diagnostics (detection and follow up of residual diseases) and therapeutical approaches (grafts, immunotherapy, vaccinology). IMGT is freely available at http://imgt.cines.fr.

Journal Article↗
PubMed2003

[Immunoinformatic analysis for the epitopes on SARS virus surface protein].

SARS virus is a recently found coronavirus, which cause human atypical pneumonia through the binding of its spike protein to the receptor on human cells. By using the methods of immunoinformatics, we analyzed the virus surface protein and found that the epitopes, which can be recognized by human immune system, are strikingly changed or disappeared to compare with other common human coronavirus. This result may imply that the escape of SARS virus from human immune surveillance may be the causality plays a very of SARS virus infection. The immunoinformatics is a powerful fool for us to in screen the epitope specificial for SARS virus and identifying the candidate sites for peptide vaccine of SARS virus.

Epitopes↗
PubMed2003

Immunoinformatics--the new kid in town.

The astounding diversity of immune system components (e.g. immunoglobulins, lymphocyte receptors, or cytokines) together with the complexity of the regulatory pathways and network-type interactions makes im munology a combinatorial science. Currently available data represent only a tiny fraction of possible situations and data continues to accrue at an exponential rate. Computational analysis has therefore become an essential element of immunology research with a main role of immunoinformatics being the management and analysis of immunological data. More advanced analyses of the immune system using computational models typically involve conversion of an immunological question to a computational problem, followed by solving of the computational problem and translation of these results into biologically meaningful answers. Major immunoinformatics developments include immunological databases, sequence analysis, structure modelling, mathematical modelling of the immune system, simulation of laboratory experiments, statistical support for immunological experimentation and immunogenomics. In this paper we describe the status and challenges within these sub-fields. We foresee the emergence of immunomics not only as a collective endeavour by researchers to decipher the sequences of T cell receptors, immunoglobulins, and other immune receptors, but also to functionally annotate the capacity of the immune system to interact with the whole array of selfand non-self entities, including genome-to-genome interactions.

Allergy and Immunology↗
PubMed2002

Immunoinformatics and the prediction of immunogenicity.

Immunoinformatics is the application of informatics techniques to molecules of the immune system. One of the key goals of immunoinformatics is the development of computer aided vaccine design (CAVD), or computational vaccinology, and its application to the search for new vaccines. Key to solving this challenge is the prediction of immunogenicity, be that at the level of epitope, subunit vaccine or attenuated pathogen. This paper reviews the current state of play in the prediction of immunogenicity and focuses on well developed methods for the prediction of peptide binding affinity to major histocompatibility complexes, which are the necessary preliminary to the in silico identification of T cell epitopes.

Allergy and Immunology↗
PubMed2005

IMGT-Choreography for immunogenetics and immunoinformatics.

IMGT, the international ImMunoGeneTics information system (http://imgt.cines.fr), was created in 1989 at Montpellier, France. IMGT is a high quality integrated knowledge resource specialized in immunoglobulins (IG), T cell receptors (TR), major histocompatibility complex (MHC) of human and other vertebrates, and related proteins of the immune system (RPI) which belong to the immunoglobulin superfamily (IgSF) and MHC superfamily (MhcSF). IMGT provides a common access to standardized data from genome, proteome, genetics and three-dimensional structures. The accuracy and the consistency of IMGT data are based on IMGT-ONTOLOGY, a semantic specification of terms to be used in immunogenetics and immunoinformatics. IMGT-ONTOLOGY has been formalized using XML Schema (IMGT-ML) for interoperability with other information systems. We are developing Web services to automatically query IMGT databases and tools. This is the first step towards IMGT-Choreography which will trigger and coordinate dynamic interactions between IMGT Web services to process complex significant biological and clinical requests. IMGT-Choreography will further increase the IMGT leadership in immunogenetics and immunoinformatics for medical research (repertoire analysis of the IG antibody sites and of the TR recognition sites in autoimmune and infectious diseases, AIDS, leukemias, lymphomas, myelomas), veterinary research (IG and TR repertoires in farm and wild life species), genome diversity and genome evolution studies of the adaptive immune responses, biotechnology related to antibody engineering (single chain Fragment variable (scFv), phage displays, combinatorial libraries, chimeric, humanized and human antibodies), diagnostics (detection and follow up of residual diseases) and therapeutical approaches (grafts, immunotherapy, vaccinology). IMGT is freely available at http://imgt.cines.fr.

Alleles↗
PubMed2003

Immunoinformatics in personalized medicine.

Diagnosis of human disease has been undergoing steady improvement over the past few centuries. Many ailments that were once considered a single entity have been classified into finer categories on the basis of response to therapy (e.g. type I and type II diabetes), inheritance (e.g. familial and non-familial polyposis coli), histology (e.g. small cell and adenocarcinoma of lung) and most recently transcriptional profiling (e.g. leukaemia, lymphoma). The next dimension in this finer categorization appears to be the typing of the patient rather than the disease i.e. disease X in person of type Y. The problem of personalized medicine is to devise tests which predict the type of individual, especially where the type is correlated with response to therapy. Immunology has been at the forefront of personalized medicine for quite a while, even though the term is not often used in this connection. Blood grouping and cross-matching (for blood transfusion), and anaphylaxis test (for penicillin) are just two examples. In this paper I will argue that immunological tests have an important place in the future of personalized medicine. I will describe methods we developed for personalizing vaccines based on MHC allele frequencies in human populations and methods for predicting peptide binding to class I MHC molecules. In conclusion, I will argue that immunological tests, and consequently immunoinformatics, will play a big role in making personalized medicine a reality.

Alleles↗
PubMed2026

Integrated immunoinformatics for the design of novel multi-epitope vaccine and identification of new drug targets against Stenotrophomonas maltophilia, a multidrug-resistant superbug.

BACKGROUND: Stenotrophomonas maltophilia is a multidrug-resistant opportunistic pathogen causing severe hospital-acquired infections, especially in immunocompromised patients. The absence of an effective vaccine and rising antibiotic resistance underscore the need for novel interventions. This study employed an integrated reverse vaccinology and computational analyses to identify new immunogenic targets, design a multi-epitope vaccine (MEV), and propose potential drug targets. METHODS: A comprehensive immunoinformatics pipeline was employed to assess antigenicity, allergenicity, human similarity, and physicochemical properties of S. maltophilia proteins. Both B- and T-cell epitopes were screened; however, only the top B-cell epitopes were selected for MEV construction, given the extracellular nature of S. maltophilia. MEV-TLR interactions were analyzed through molecular docking and dynamics simulations. In parallel, cytoplasmic proteins were screened via a subtractive genomics approach to identify essential, non-human homologous, and non-microbiome-similar proteins, which were further evaluated for druggability and interaction networks to propose novel therapeutic targets. RESULTS: From a total of 4111 proteins, seven potential immunogenic targets were identified: GspD (WP_108270537.1), FhuE (WP_049451370.1), fimbrial protein (WP_012479122.1), TonB-dependent receptor (WP_169448402.1), TolC family protein (WP_108270106.1), autotransporter beta-barrel OMP (WP_169448945.1), and a hypothetical protein (WP_005407892.1). Subsequently, an MEV was designed using five immunogenic epitopes derived from four of these targets: WP_005407892.1 (ADQDSSNM), WP_049451370.1 (SGKAEQ and GEESKTPS), WP_108270537.1 (GVTSTQSDSERT), and WP_169448945.1 (RELGGDRNE). Molecular docking and molecular dynamics simulations demonstrated strong, stable, and feasible interactions between the MEV and TLR-2 and TLR-4 receptors. Moreover, nine novel drug targets were predicted for S. maltophilia, providing new therapeutic insights. CONCLUSION: The designed MEV and identified immunogenic targets represent promising vaccine candidates against S. maltophilia. Further in vitro and in vivo studies are essential to confirm their safety, immunogenicity, and protective efficacy. Additionally, subtractive genomics analysis revealed nine novel, non-homologous drug targets, offering safer and more specific therapeutic avenues.

Drug targets↗
PubMed2004

New horizons in mouse immunoinformatics: reliable in silico prediction of mouse class I histocompatibility major complex peptide binding affinity.

Quantitative structure-activity relationship (QSAR) analysis is a main cornerstone of modern informatic disciplines. Predictive computational models, based on QSAR technology, of peptide-major histocompatibility complex (MHC) binding affinity have now become a vital component of modern day computational immunovaccinology. Historically, such approaches have been built around semi-qualitative, classification methods, but these are now giving way to quantitative regression methods. The additive method, an established immunoinformatics technique for the quantitative prediction of peptide-protein affinity, was used here to identify the sequence dependence of peptide binding specificity for three mouse class I MHC alleles: H2-D(b), H2-K(b) and H2-K(k). As we show, in terms of reliability the resulting models represent a significant advance on existing methods. They can be used for the accurate prediction of T-cell epitopes and are freely available online ( http://www.jenner.ac.uk/MHCPred).

Algorithms↗
PubMed2006

Immunoinformatics comes of age.

With the burgeoning immunological data in the scientific literature, scientists must increasingly rely on Internet resources to inform and enhance their work. Here we provide a brief overview of the adaptive immune response and summaries of immunoinformatics resources, emphasizing those with Web interfaces. These resources include searchable databases of epitopes and immune-related molecules, and analysis tools for T cell and B cell epitope prediction, vaccine design, and protein structure comparisons. There is an agreeable synergy between the growing collections in immune-related databases and the growing sophistication of analysis software; the databases provide the foundation for developing predictive computational tools, which in turn enable more rapid identification of immune responses to populate the databases. Collectively, these resources contribute to improved understanding of immune responses and escape, and evolution of pathogens under immune pressure. The public health implications are vast, including designing vaccines, understanding autoimmune diseases, and defining the correlates of immune protection.

Amino Acid Sequence↗
PubMed2003

IMGT, the international ImMunoGeneTics information system, http://imgt.cines.fr: the reference in immunoinformatics.

IMGT, the international ImMunoGeneTics information system (http://imgt.cines.fr), is a high quality integrated information system specializing in immunoglobulins (IG), T cell receptors (TR), major histocompatibility complex (MHC) and related proteins of the immune system of human and other vertebrates, created in 1989, by the Laboratoire d'ImmunoGénétique Moléculaire (LIGM), at the Université Montpellier II, CNRS, Montpellier, France. IMGT is the global reference in immunogenetics and immunoinformatics and provides a common access to standardized data which include nucleotide and protein sequences, oligonucleotide primers, gene maps, genetic polymorphisms, specificities, 2D and 3D structures. IMGT includes three sequence databases (IMGT/LIGM-DB, IMGT/MHC-DB hosted at EBI, IMGT/PRIMER-DB), one genome database (IMGT/GENE-DB), one 3D structure database (IMGT/3Dstructure-DB), Web resources comprising 8000 HTML pages ("IMGT Marie-Paule page") and interactive tools for sequence (IMGT/V-QUEST, IMGT/JunctionAnalysis, IMGT/Allele-Align, IMGT/PhyloGene) and genome (IMGT/GeneSearch, IMGT/GeneView, IMGT/LocusView) analysis. IMGT data are expertly annotated according to the rules of the IMGT Scientific chart, based on the IMGT-ONTOLOGY concepts. IMGT tools are particularly useful for the analysis of the IG and TR repertoires in physiological normal and pathological situations. IMGT has important applications in medical research (repertoire analysis in autoimmune diseases, AIDS, leukemias, lymphomas, myelomas), biotechnology related to antibody engineering (phage displays, combinatorial libraries) and therapeutic approaches (graft, immunotherapy). IMGT is freely available at http://imgt.cines.fr.

Animals↗
PubMed2026

An immunoinformatics-based multi-epitope vaccine candidate confers cross-protection against two Actinobacillus pleuropneumoniae serovars.

Porcine contagious pleuropneumonia (PCP) is caused by Actinobacillus pleuropneumoniae (APP) and inflicts heavy economic losses on the swine industry. However, existing inactivated vaccines provide limited cross-protection, highlighting the need for improved vaccine strategies. In this study, we combined pangenome analysis with subtractive proteomics to screen the APP core genome and identified 11 potential antigens. Seven of them showed immunoreactivity by ELISA and Western blotting. These antigens, together with the ApxI-III toxins, were used for T and B cell epitope prediction. On this basis, a multi-epitope fusion protein MVAPP was constructed. In silico molecular docking with swine immune receptors and immune simulations suggested that MVAPP has the potential to induce immune responses. In the mouse model, that MVAPP elicited specific antibody responses, shifted the splenic T-cell subset distribution toward CD4+ T cells, and provided partial protection against challenge with strains from two serovars. In conclusion, MVAPP represents a potential multi-epitope vaccine candidate for further development against APP.

Animals↗
PubMed2004

IMGT-ONTOLOGY and IMGT databases, tools and Web resources for immunogenetics and immunoinformatics.

The international ImMunoGeneTics information system (IMGT; http://imgt.cines.fr), is a high quality integrated information system specialized in immunoglobulins (IG), T cell receptors (TR), major histocompatibility complex (MHC), and related proteins of the immune system (RPI) of human and other vertebrates, created in 1989, by the Laboratoire d'ImmunoGénétique Moléculaire (LIGM; Université Montpellier II and CNRS) at Montpellier, France. IMGT provides a common access to standardized data which include nucleotide and protein sequences, oligonucleotide primers, gene maps, genetic polymorphisms, specificities, 2D and 3D structures. IMGT consists of several sequence databases (IMGT/LIGM-DB, IMGT/MHC-DB, IMGT/PRIMER-DB), one genome database (IMGT/GENE-DB) and one 3D structure database (IMGT/3Dstructure-DB), interactive tools for sequence analysis (IMGT/V-QUEST, IMGT/JunctionAnalysis, IMGT/PhyloGene, IMGT/Allele-Align), for genome analysis (IMGT/GeneSearch, IMGT/GeneView, IMGT/LocusView) and for 3D structure analysis (IMGT/StructuralQuery), and Web resources ("IMGT Marie-Paule page") comprising 8000 HTML pages. IMGT other accesses include SRS, FTP, search by BLAST, etc. By its high quality and its easy data distribution, IMGT has important implications in medical research (repertoire in autoimmune diseases, AIDS, leukemias, lymphomas, myelomas), veterinary research, genome diversity and genome evolution studies of the adaptive immune responses, biotechnology related to antibody engineering (single chain Fragment variable (scFv), phage displays, combinatorial libraries) and therapeutical approaches (grafts, immunotherapy). IMGT is freely available at http://imgt.cines.fr.

Animals↗