AF2BIND for Binding Site Prediction

AF2BIND is a logistic regression model on top of AlphaFold embeddings that predicts the probability that each residue in a protein is in a pocket. Binding site prediction is the problem of detecting where (which residues) on a protein are likely to interact with other molecules. This is also called a binding pocket, pocket, functional site, or sometimes a hotspot. Not all parts of a protein can be easily bound, so identifying where likely sites are can help scientists understand what the function of an unknown protein is, avoid disrupting important sites when engineering a protein, and decide whether or not a candidate protein is a good drug target.