FragFEATURE is a data-driven computational method for fragment binding prediction. It predicts small molecule fragments preferred by a protein structure using a knowledge base of all previously observed protein-fragment interactions.
Druggability of a protein is its potential to be modulated by drug-like molecules. It is important in the target selection phase. We developed DrugFEATURE to quantify druggability by assessing the microenvironments in potential small-molecule binding sites.
Stanford and Rockefeller researchers have identified and developed dynein-specific inhibitors that have significant medical applications involving mitotic spindle assembly, organelle transport, and primary cilia formation.