CASP15 (2022) showed enormous progress in modeling multimolecular protein complexes. The assembly modeling (a.k.a. quaternary structure modeling, oligomeric modeling, multimeric modeling) has been assessed in CASP since 2016 (CASP12). Typically, models were of good accuracy when templates were available for the structure of the whole target complex. After the success of AlphaFold2 in CASP14 (2020), it was expected that deep learning methodology that brought monomeric modeling to qualitatively new level will
CASP14 marked an extraordinary increase in the accuracy of the computed three-dimensional protein structures with the emergence of the advanced deep learning method AlphaFold2. Models built with this method proved to be competitive with the experimental accuracy (GDT_TS> 90) for ~2/3 of the targets and of high accuracy (GDT_TS> 80) for almost 90% of the targets (middle plot). The accuracy of CASP14 models for TBM targets significally superseeded accuracy of models that can be built by simple transcription o
CASP14 marked an extraordinary increase in the accuracy of the computed three-dimensional protein structures with the emergence of the advanced deep learning method AlphaFold2. The CASP14 trend line in the historical progress plot (panel 2, black trendline) starts at a GDT_TS of about 95, and finishes at about 85 for difficult targets. Because of experimental errors and artifacts, a GDT_TS of 100 is highly unlikely. In CASP14, about 2/3 of the 96 targets reached GDT_TS values greater than that, and so are c
Links to predictioncenter.org (18)
scfbio-iitd.res.inSupercomputing Facility for Bioinformatics & Computational Biology, IIT Delhi
Supercomputing Facility for Bioinformatics & Computational Biology, IIT Delhi