CASP (Critical Assessment of Structure Prediction) is a community-wide experiment to advance the state of the art in modeling protein structure from amino acid sequence. Every two years, participants are invited to submit models for a set of proteins for which the experimental structures are not yet public. In the latest CASP round, CASP15, nearly 100 groups from around the world submitted more than 53,000 models on 127 modeling targets in 5 prediction categories. Independent assessors then compared the models with experiment, and the results and their implications were discussed at the CASP15 Conference, held December 10–13, 2022, in Antalya, Turkey. Peter Freddolino led a U-M team, spearheaded by postdoctoral fellow Wei Zheng, Ph.D. (competing as "UM-TBM" and "Zheng"), that placed first in the Multimer and Interdomain Prediction categories, and was the top-ranked server and second-ranked group overall in the Regular (domains) category according to the CASP assessor's criteria. Results will be published in an upcoming special issue of the journal Proteins, and slides from the CASP15 presentation given by Peter and Wei can be viewed here:
D-I-TASSER: Integrating Deep Learning with Multi-MSAs and Threading Alignments for Protein Structure Prediction
