AIMC Topic: Vaccinology

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A descriptor-free machine learning framework to improve antigen discovery for bacterial pathogens.

PloS one
Identifying protective antigens (PAs), i.e., targets for bacterial vaccines, is challenging as conducting in-vivo tests at the proteome scale is impractical. Reverse Vaccinology (RV) aids in narrowing down the pool of candidates through computational...

Multi-criteria decision making and its application to in silico discovery of vaccine candidates for Toxoplasma gondii.

Vaccine
Vaccine discovery against eukaryotic parasites is not trivial and few exist. Reverse vaccinology is an in silico vaccine discovery approach, designed to identify vaccine candidates from the thousands of protein sequences encoded by a target genome. P...

Vaccinology in the artificial intelligence era.

Science translational medicine
Artificial intelligence (AI) has already transformed vaccine antigen design and could transform the entire vaccinology pipeline, including immune responses and emerging infectious disease prediction, manufacturing and regulatory processes, clinical t...

NERVE 2.0: boosting the new enhanced reverse vaccinology environment via artificial intelligence and a user-friendly web interface.

BMC bioinformatics
BACKGROUND: Vaccines development in this millennium started by the milestone work on Neisseria meningitidis B, reporting the invention of Reverse Vaccinology (RV), which allows to identify vaccine candidates (VCs) by screening bacterial pathogens gen...

VacSol-ML(ESKAPE) Machine learning empowering vaccine antigen prediction for ESKAPE pathogens.

Vaccine
The ESKAPE family, comprising Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp., poses a significant global threat due to their heightened virulence and extensiv...

Reverse engineering protection: A comprehensive survey of reverse vaccinology-based vaccines targeting viral pathogens.

Vaccine
Vaccines have significantly reduced the impact of numerous deadly viral infections. However, there is an increasing need to expedite vaccine development in light of the recurrent pandemics and epidemics. Also, identifying vaccines against certain vir...

Computational Methods in Immunology and Vaccinology: Design and Development of Antibodies and Immunogens.

Journal of chemical theory and computation
The design of new biomolecules able to harness immune mechanisms for the treatment of diseases is a prime challenge for computational and simulative approaches. For instance, in recent years, antibodies have emerged as an important class of therapeut...

Application of in-silico approaches in subunit vaccines: Overcoming the challenges of antigen and adjuvant development.

Journal of controlled release : official journal of the Controlled Release Society
Subunit vaccines are crucial in preventing modern diseases due to their safety, stability, and ability to elicit targeted immune responses. However, challenges in antigen and adjuvant design hinder their development. Recent advancements in in-silico ...

Artificial intelligence in vaccine research and development: an umbrella review.

Frontiers in immunology
BACKGROUND: The rapid development of COVID-19 vaccines highlighted the transformative potential of artificial intelligence (AI) in modern vaccinology, accelerating timelines from years to months. Nevertheless, the specific roles and effectiveness of ...

Computer Aided Reverse Vaccinology: A Game-changer Approach for Vaccine Development.

Combinatorial chemistry & high throughput screening
One of the most dynamic approaches in biotechnology is reverse vaccinology, which plays a huge role in today's developing vaccines. It has the capability of exploring and identifying the most potent vaccine candidate in a limited period of time. The ...