Can artificial intelligence predict and design immunological synapses?

Science / Life Sciences

Our immune system is a powerful defense network that protects us from harmful invaders such as viruses and bacteria, as well as internal threats such as cancer. T cells, a type of white blood cell, play a key role. They use T cell receptors (TCRs) to recognize specific protein fragments, or peptides, on the surface of other cells. This recognition triggers an immune response that eliminates the infected or abnormal cells.

This project will investigate whether artificial intelligence can predict this complex recognition process. We will analyze data on TCRs and peptides, including their amino acid sequences and 3D structures, using machine learning and deep learning. The goal is to develop models that can accurately predict which TCRs will bind to specific peptides. These models will improve our understanding of the immune system and aid in the diagnosis of disease. In addition, we will use generative models to design new TCRs that can precisely target specific peptides, such as those found on cancer cells, potentially leading to the development of innovative immunotherapies.

Amount invested

Grant Serrapilheira: R$ 350.000,00 (R$ 200.000,00 + R$ 150.000,00 optional bonuses aimed at the integration and training of individuals from underrepresented groups in science)

Open Calls

Science Call 7
  • Topics
  • computing