Researchers Create a New AI Pipeline for Identifying Molecular Interactions

AI developments in chemical biology could unlock new types of disease treatments

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 Assistant Professor of Chemistry Alberto Perez have 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.

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