metadata
license: mit
pretty_name: CASP 16
CASP (Critical Assessment of Structure Prediction) is a community wide experiment to determine and advance the state of the art in computational structural biology. Every two years, participants are invited to submit models for a set of macromolecules and macromolecular complexes (proteins, RNA, ligands) for which the experimental structures are not yet public. In the latest CASP round, CASP16 in 2024, nearly 100 research groups from around the world submitted more than 80,000 models on 100+ modeling entities yielding 300 targets in five prediction categories. Independent assessors then compare the models with experiment. Assessments and results are published in a special issue of the journal PROTEINS (check the latest CASP15 issue here).
CASP16 categories are as follows:
- Single Proteins and Domains: As in previous CASPs, the accuracy of single proteins and where appropriate single protein domains will be assessed, using the established metrics. The major emphasis is now on the fine-grained accuracy of models, whether limitations related to sequence alignment depth and target size are surmounted, and whether interdomain relationships are accurately captured. There is also interest how well the many new deep learning methods perform, including those using large language models. Protein Complexes As in recent CASPs, the ability of current methods to correctly model subunit-subunit and protein-protein interactions will be assessed. We will again work in close collaboration with our CAPRI partners. There was enormous progress in this category in the last CASP, but accuracy was not yet as high as for single proteins, so there is substantial room for a further advance. New in this CASP is the option of predicting stoichiometry. Where possible, targets will initially be released without that information, models collected, followed by re-release with that data provided.
- Accuracy Estimation: Members of the community will again be invited to submit accuracy estimates for multimeric complexes and inter-subunit interfaces provided by others. There is no longer a category for general methods of estimating single protein structure accuracy, since in recent CASPs estimates provided by model builders have been consistently more reliable. However, there will be an emphasis on the reliability of accuracy estimates provided with submitted structures, both overall and at the individual amino acid level. Note that all accuracy estimates are in plddt units, not Angstroms.
- Nucleic acid (NA) structures and complexes: An RNA structure category was introduced in the previous CASP and the results were interesting and provocative. In particular, it appeared that deep learning methods were not yet as effective as more traditional ones for this type of macromolecule. Has that now changed? This CASP we expect to include RNA and DNA single structures and complexes, and complexes of these with proteins.
- Protein-organic ligand complexes: The last round of CASP included this category for the first time. Results indicated that, as with RNA structure, deep learning methods were not yet competitive with more traditional approaches. So there is considerable interest in whether that has now changed. In addition to ligands integral to protein targets, we expect to have several target sets related to drug design.
- Macromolecular conformational ensembles Following the success of deep-learning methods for single structures, it is increasingly important to assess methods for predicting structure ensembles, and CASP included this category for the first time in 2022. While it was clear deep learning methods have considerable potential for generating ensembles, the best procedures are still hotly debated with many new papers appearing. In CASP16, we expect to have a variety of targets for both protein and RNA ensembles.
- Integrative modeling: Deep learning methods combined with sparse experimental data such as SAXS and chemical crosslinking are now being used extensively to obtain the structure of large marcomolecular complexes. To assess effectiveness of these approaches, CASP is reintroducing this category of modeling, provided appropriate targets will be available.