Critical Assessment of protein Structure Prediction

thumb|right|250px|A target structure (ribbons) and 354 template-based predictions superimposed (gray Calpha backbones); from CASP8 Critical Assessment of Structure Prediction (CASP), sometimes called Critical Assessment of Protein Structure Prediction, is a community-wide, worldwide experiment for protein structure prediction taking place every two years since 1994. CASP provides research groups with an opportunity to objectively test their structure prediction methods and delivers an independent assessment of the state of the art in protein structure modeling to the research community and software users. Even though the primary goal of CASP is to help advance the methods of identifying protein three-dimensional structure from its amino acid sequence many view the experiment more as a "world championship" in this field of science. More than 100 research groups from all over the world participate in CASP on a regular basis and it is not uncommon for entire groups to suspend their other research for months while they focus on getting their servers ready for the experiment and on performing the detailed predictions.

==Selection of target proteins== In order to ensure that no predictor can have prior information about a protein's structure that would put them at an advantage, it is important that the experiment be conducted in a double-blind fashion: Neither predictors nor the organizers and assessors know the structures of the target proteins at the time when predictions are made. Targets for structure prediction are either structures soon-to-be solved by X-ray crystallography or NMR spectroscopy, or structures that have just been solved (mainly by one of the structural genomics centers) and are kept on hold by the Protein Data Bank. If the given sequence is found to be related by common descent to a protein sequence of known structure (called a template), comparative protein modeling may be used to predict the tertiary structure. Templates can be found using sequence alignment methods (e.g. BLAST or HHsearch) or protein threading methods, which are better in finding distantly related templates. Otherwise, de novo protein structure prediction must be applied (e.g. Rosetta), which is much less reliable but can sometimes yield models with the correct fold (usually, for proteins less than 100-150 amino acids). Truly new folds are becoming quite rare among the targets, making that category smaller than desirable.