Scientists have developed a new method to better predict which peptides (small proteins) can effectively bind to specific HLA molecules. HLA molecules are like display cases on cells that present peptides to the immune system. If the immune system recognizes a peptide as foreign, it can trigger an immune response to destroy the cell. This is particularly important in cancer immunotherapy, where the goal is to stimulate the immune system to attack cancer cells.
The researchers used a combination of predictive algorithms and dynamic simulations to improve the accuracy of peptide binding predictions. This approach allowed them to establish a strong correlation between the predicted binding affinity and the actual binding affinity observed in laboratory experiments. This means that their method can help reduce the need for time-consuming and expensive laboratory tests to confirm peptide binding.
Funding
This study was supported by Mahidol University [R016010006, R016010005, R016034008, and Basic Research Fund: fiscal year 2022: BRF1-027/2565], Siriraj Research Fund, Faculty of Medicine Siriraj Hospital, Mahidol University [R015832018], and Program Management Unit-Competitiveness (PMUC) [C10F630063/1], and Chulalongkorn University [CE66_036_2300_008].
Original Paper
Title of original paper: In silico advancements in Peptide-MHC interaction: A molecular dynamics study of predicted glypican-3 peptides and HLA-A*11:01
Journal: Heliyon
DOI: https://doi.org/10.1016/j.heliyon.2024.e36654