Deep Learning Modeling Server for T Cells Opens New Avenues in Immunology Research
A critical component of the human immune system is T cell receptors (TCR). With their diversity and specificity, they are able to recognize and bind to antigens from viruses, pathogens, and tumors, leading to a T cell immune response against infected or diseased cells. A deeper understanding of TCR structures and interactions with their targets can thus have vital implications in advancing our understanding of immunology, even guiding the design of therapeutic drugs and vaccines.
Dr. Brian Pierce, IBBR Fellow and Associate Professor, along with members of his lab recently developed TCRmodel2, a web server that is able to both model TCRs by themselves and in complex with their targets, with high accuracy, speed, and resolution. This development modifies and adapts AlphaFold, a novel deep learning system based on artificial intelligence. TCRmodel2 is available to the public at https://tcrmodel.ibbr.umd.edu where users are able to input sequences of already available or newly discovered TCRs.
This advance in TCR modeling provides a new tool to help better understand how the immune system fights certain viruses and pathogens on a molecular level and will enable the characterization and optimization of TCRs for cancer therapy.