UNSPECIFIED (2023) Riding the wave of innovation: immunoinformatics in fish disease control. PeerJ, 11 (NA). pp. 1-53. ISSN 2167-8359
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Official URL: http://dx.doi.org/10.7717/peerj.16419
Abstract
The spread of infectious illnesses has been a significant factor restricting aquaculture production. To maximise aquatic animal health, vaccination tactics are very successful and cost-efficient for protecting fish and aquaculture animals against many disease pathogens. However, due to the increasing number of immunological cases and their complexity, it is impossible to manage, analyse, visualise, and interpret such data without the assistance of advanced computational techniques. Hence, the use of immunoinformatics tools is crucial, as they not only facilitate the management of massive amounts of data but also greatly contribute to the creation of fresh hypotheses regarding immune responses. In recent years, advances in biotechnology and immunoinformatics have opened up new research avenues for generating novel vaccines and enhancing existing vaccinations against outbreaks of infectious illnesses, thereby reducing aquaculture losses. This review focuses on understanding in silico epitope-based vaccine design, the creation of multi-epitope vaccines, the molecular interaction of immunogenic vaccines, and the application of immunoinformatics in fish disease based on the frequency of their application and reliable results. It is believed that it can bridge the gap between experimental and computational approaches and reduce the need for experimental research, so that only wet laboratory testing integrated with in silico techniques may yield highly promising results and be useful for the development of vaccines for fish.
Item Type: | Article |
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Uncontrolled Keywords: | adjuvant, aquaculture, computational biotechnology, fish diseases, immunoinformatics, in silico epitope-based vaccine design, linker selection, molecular docking, molecular dynamics simulation, vaccines |
Subjects: | Q Science > Q Science (General) |
Divisions: | Science |
ID Code: | 106147 |
Deposited By: | Yanti Mohd Shah |
Deposited On: | 09 Jun 2024 09:10 |
Last Modified: | 09 Jun 2024 09:10 |
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