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AI and Immunology Considerations in Pandemics and SARS-CoV-2 COVID-19
Published in Louis J. Catania, AI for Immunology, 2021
The explosion of new immunological data through increased research in understanding the immune system, particularly in infectious disease pathogenesis and the application of the knowledge from bioinformatics has led to a better understanding of the importance of the immune system through immunoinformatics (computational immunology). Through increased knowledge of the immune system, AI research, and the cost-effective, specific and effective approaches like in silico immunoinformatics (scientific experimentation and research conducted or produced by means of computer modeling or computer simulation),68 the concerns for emerging and potentially re-surging diseases caused by pathogenic organisms, antigenic variability/complex life cycle of pathogens (see Figure 5.1, COVID-19 life cycle, above), and the need of personalized vaccination can be combated on a molecular level.69
Exploring Klebsiella pneumoniae capsule polysaccharide proteins to design multiepitope subunit vaccine to fight against pneumonia
Published in Expert Review of Vaccines, 2022
Jyotirmayee Dey, Soumya Ranjan Mahapatra, S Lata, Shubhransu Patro, Namrata Misra, Mrutyunjay Suar
Klebsiella pneumoniae has emerged as an urgent public health threat in many industrialized countries worldwide. Infections caused by K. pneumoniae are difficult to treat because these organisms are typically resistant to multiple drugs, and the patients have significant co-morbidities. Given the dearth of new antibiotics and the recent incidence of multidrug-resistant strains, there is a critical need for the development of a vaccine against K. pneumoniae infections [20]. The capsule polysaccharide (CPS) of K. pneumoniae has long been viewed as an important virulence factor that promotes resistance to phagocytosis and serum bactericidal activity. Experimental studies have demonstrated that anti-CPS IgG isolated from human volunteers protects mice against K. pneumoniae sepsis [65]. In present times, the multi-epitope subunit vaccine is preferable than the traditional vaccine for several advantages including safety, higher stability, less allergic, autoimmune responses, and a more convenient production process. High throughput next-generation sequencing and advanced genomics and proteomics technologies have brought about a significant change in the computational immunology approach. With the abundance of genomic data and a plethora of immunoinformatics tools available, a better understanding of the immune response of the human body against a multitude of infectious pathogens can be deciphered [66].
Immunoinformatics: In Silico Approaches and Computational Design of a Multi-epitope, Immunogenic Protein
Published in International Reviews of Immunology, 2019
Armina Alagheband Bahrami, Zahra Payandeh, Saeed Khalili, Alireza Zakeri, Mojgan Bandehpour
The hierarchical and combinatorial properties of the immune system are the main contributors of its complexity. This complexity is evident considering the huge amount of accumulated immunology data. These data are derived from genomic sequencing, clinical practice, and epidemiologic data. The accumulated data is a valuable source for investigators who need information about the mechanisms of immune function, immunological interactions, and pathogenesis [1] of diseases. Thus, this progressive immunological resource needs to be stored, managed, and analyzed. Immunological researchers should harvest the required data from a source with this complexity. The necessity to manage this vast source of data has given rise to the field known as immunoinformatics or computational immunology. Immunoinformatics could be defined as the interface between experimental immunology and computer science. It involves the analysis of biological information using computers and statistical techniques [1]. Immunoinformatics is the understanding of immunological information through exploitation of computational methods and resources. Immunological investigations could be benefited from immunoinformatics tools to deal with huge amount of immune-related data and defining new hypotheses related to immune responses. Since immunological databases and prediction software allow researchers to identify the interplay of the molecules involved in immune response, contemporary they have become an inevitable part of the immunological research [2]. Significant shortening of the time required for experimental procedures is one the desired consequences of employing immunoinformatics approaches. It includes various databases and advanced algorithms capable of helping the progress in research related to biological phenomenon. Bioinformatics is commonly used for modeling the biological systems, predictions of three-dimensional (3D) models for biomolecules, analyzing the genomic and proteomic data, and studying the growth and connectivity of information to discover genes and new functions [3].