Understanding how proteins interact with each other is crucial for developing new treatments and understanding diseases. Thanks to computational advances, a team of researchers led by UF assistant professor of chemistry Alberto Perez has developed a groundbreaking algorithm to identify these molecular interactions.
Perez’s research team included two graduate students from UF, Arup Mondal and Bhumika Singh, and a handful of researchers from Rutgers University and Rensselaer Polytechnic Institute. The team published their findings in Angewandte Chemie, a leading chemistry journal based in Germany.
Named the AF-CBA Pipeline, this innovative tool offers unparalleled accuracy and speed in pinpointing the strongest peptide binders to a specific protein. It does this by using AI to simulate molecular interactions, sorting through thousands of candidate molecules to identify the molecule that interacts best with the protein of interest.
