Prospective Artificial Intelligence to Dissect the Dengue Immune Response and Discover Therapeutics

Overview

Journal Front Immunol

Specialty Allergy & Immunology

Date 2021 Jul 2

PMID 34211454

Citations 5

Authors

Eriberto N Natali

Lmar M Babrak

Enkelejda Miho

Affiliations

Soon will be listed here.

Abstract

Dengue virus (DENV) poses a serious threat to global health as the causative agent of dengue fever. The virus is endemic in more than 128 countries resulting in approximately 390 million infection cases each year. Currently, there is no approved therapeutic for treatment nor a fully efficacious vaccine. The development of therapeutics is confounded and hampered by the complexity of the immune response to DENV, in particular to sequential infection with different DENV serotypes (DENV1-5). Researchers have shown that the DENV envelope (E) antigen is primarily responsible for the interaction and subsequent invasion of host cells for all serotypes and can elicit neutralizing antibodies in humans. The advent of high-throughput sequencing and the rapid advancements in computational analysis of complex data, has provided tools for the deconvolution of the DENV immune response. Several types of complex statistical analyses, machine learning models and complex visualizations can be applied to begin answering questions about the B- and T-cell immune responses to multiple infections, antibody-dependent enhancement, identification of novel therapeutics and advance vaccine research.

Citing Articles

Phytochemicals of Different Medicinal Herbs as Potential Inhibitors Against Dengue Serotype 2 Virus: A Computational Approach.

Roy D, Manumol M, Alagarasu K, Parashar D, Cherian S Mol Biotechnol. 2024; .

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High throughput long-read sequencing of circulating lymphocytes of the evolutionarily distant sea lamprey reveals diversity and common elements of the variable lymphocyte receptor B (VLRB) repertoire.

Zia A, Orozco A, Fang I, Tang A, Mendoza Viruega A, Dong S Front Immunol. 2024; 15:1427075.

PMID: 39170622 PMC: 11335541. DOI: 10.3389/fimmu.2024.1427075.

The dengue-specific immune response and antibody identification with machine learning.

Natali E, Horst A, Meier P, Greiff V, Nuvolone M, Babrak L NPJ Vaccines. 2024; 9(1):16.

PMID: 38245547 PMC: 10799860. DOI: 10.1038/s41541-023-00788-7.

Exploring the Targets of Dengue Virus and Designs of Potential Inhibitors.

Nath S, Malakar P, Biswas B, Das S, Sabnam N, Nandi S Comb Chem High Throughput Screen. 2023; 27(17):2485-2524.

PMID: 37962048 DOI: 10.2174/0113862073247689231030153054.

Current Trends and Limitations in Dengue Antiviral Research.

Obi J, Gutierrez-Barbosa H, Chua J, Deredge D Trop Med Infect Dis. 2021; 6(4).

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