CASP

CASP, which stands for Critical Assessment of Techniques for Protein Structure Prediction, is a community-wide experiment (though it is commonly referred to as a competition) for protein structure prediction taking place every two years since 1994.

CASP provides research groups with an opportunity to assess the quality of their methods for protein structure prediction from the primary structure of the protein. As a consequence, CASP provides the research community with an assessment of the state of the art in this field. It is not uncommon for entire research groups to shut down for months while they focus on getting their results ready for CASP.

Protein structures that are either expected to be solved shortly or that have been recently solved, but not yet discussed in public, are used as targets for the prediction. If the given sequence is found (for example, using sequence alignment methods such as BLAST or FASTA) to be similar to a protein sequence of known structure, comparative protein modeling may be used to predict the tertiary structure. Otherwise, other methods such as protein threading or de novo protein structure prediction must be applied.

Evaluation of the results is carried out in the following prediction categories:
 * tertiary structure prediction (all CASPs)
 * secondary structure prediction (dropped after CASP5)
 * prediction of structure complexes (CASP2 only; a separate experiment - CAPRI - carries on this subject)
 * residue-residue contact prediction (starting CASP4)
 * disordered regions prediction (starting CASP5)
 * domain boundary prediction (starting CASP6)
 * function prediction (starting CASP6)
 * model quality assessment (starting CASP7)
 * model refinement (starting CASP7)

Tertiary structure prediction category was further subdivided into
 * homology modeling
 * fold recognition (also called protein threading; Note, this is incorrect as threading is a method)
 * de novo structure prediction Now referred to as 'New Fold' as many methods apply evaluation, or scoring, functions that are biased by knowledge of native protein structures, such an example would be an artificial neural network.

Starting CASP7, categories have been redefined to reflect developments in methods. The 'Template based modeling' category includes all former comparative modeling, homologous fold based models and some analogous fold based models. The 'Template free modeling' category includes models of proteins with previously unseen folds and hard analogous fold based models.

The CASP results are published in special issues of the scientific journal Proteins:, , , ,