AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Epitopes

Showing 11 to 20 of 50 articles

Clear Filters

Training of epitope-TCR prediction models with healthy donor-derived cancer-specific T cells.

Methods in cell biology
Discovery of epitope-specific T-cell receptors (TCRs) for cancer therapies is a time consuming and expensive procedure that usually requires a large amount of patient cells. To maximize information from and minimize the need of precious samples in ca...

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...

Epitope Identification of an mGlu5 Receptor Nanobody Using Physics-Based Molecular Modeling and Deep Learning Techniques.

Journal of chemical information and modeling
The world has witnessed a revolution in therapeutics with the development of biological medicines such as antibodies and antibody fragments, notably nanobodies. These nanobodies possess unique characteristics including high specificity and modulatory...

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...

Deep learning predictions of TCR-epitope interactions reveal epitope-specific chains in dual alpha T cells.

Nature communications
T cells have the ability to eliminate infected and cancer cells and play an essential role in cancer immunotherapy. T cell activation is elicited by the binding of the T cell receptor (TCR) to epitopes displayed on MHC molecules, and the TCR specific...

HLAIImaster: a deep learning method with adaptive domain knowledge predicts HLA II neoepitope immunogenic responses.

Briefings in bioinformatics
While significant strides have been made in predicting neoepitopes that trigger autologous CD4+ T cell responses, accurately identifying the antigen presentation by human leukocyte antigen (HLA) class II molecules remains a challenge. This identifica...

Prediction of Paratope-Epitope Pairs Using Convolutional Neural Networks.

International journal of molecular sciences
Antibodies play a central role in the adaptive immune response of vertebrates through the specific recognition of exogenous or endogenous antigens. The rational design of antibodies has a wide range of biotechnological and medical applications, such ...

Enhancing tuberculosis vaccine development: a deconvolution neural network approach for multi-epitope prediction.

Scientific reports
Tuberculosis (TB) a disease caused by Mycobacterium tuberculosis (Mtb) poses a significant threat to human life, and current BCG vaccinations only provide sporadic protection, therefore there is a need for developing efficient vaccines. Numerous immu...

Geometric epitope and paratope prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Identifying the binding sites of antibodies is essential for developing vaccines and synthetic antibodies. In this article, we investigate the optimal representation for predicting the binding sites in the two molecules and emphasize the ...

Machine-learning-based structural analysis of interactions between antibodies and antigens.

Bio Systems
Computational analysis of paratope-epitope interactions between antibodies and their corresponding antigens can facilitate our understanding of the molecular mechanism underlying humoral immunity and boost the design of new therapeutics for many dise...