Protein Structure Prediction Center
Success Stories From Recent CASPs
ab initio
help structural
refinement data-assisted
template-based modeling
Models based on templates identified by sequence similarity remain the most accurate. Over the course of the CASP experiments there have been enormous improvements in this area. However, the overall accuracy improvements that we have seen in the first 10 years of CASP remained unmatched until CASP12, when a new burst of progress happened (see the plot). In two years from CASP11 to CASP12 the backbone accuracy of the submitted models improved more than in the preceeding 10 years. Several factors contributed to this, including more accurate alignment of the target sequence to that of available templates, combining multiple templates, improved accuracy of regions not covered by templates, successful refinement of models, and better selection of models from decoy sets due to improved methods for estimation of model accuracy.

target: T0868-D1 (CASP12, 116 res.)
best template: 2cw6 ( 4.2%)
model: T0868TS330_2 (gdt_ts: 86.6)

Welcome to the Protein Structure Prediction Center!

Our goal is to help advance the methods of identifying protein structure from sequence. The Center has been organized to provide the means of objective testing of these methods via the process of blind prediction. The Critical Assessment of protein Structure Prediction (CASP) experiments aim at establishing the current state of the art in protein structure prediction, identifying what progress has been made, and highlighting where future effort may be most productively focused.

There have been twelve previous CASP experiments. The thirteenth experiment is planned to start in May 2018. Description of these experiments and the full data (targets, predictions, interactive tables with numerical evaluation results, dynamic graphs and prediction visualization tools) can be accessed following the links:

CASP1 (1994) | CASP2 (1996) | CASP3 (1998) | CASP4 (2000) | CASP5 (2002) | CASP6 (2004) | CASP7 (2006) | CASP8 (2008) | CASP9 (2010) | CASP10 (2012) | CASP11 (2014) | CASP12 (2016) | CASP13 (2018)

Raw data for the experiments held so far are archived and stored in our data archive.

Details of the experiments have been published in a scientific journal Proteins: Structure, Function and Bioinformatics. CASP proceedings include papers describing the structure and conduct of the experiments, the numerical evaluation measures, reports from the assessment teams highlighting state of the art in different prediction categories, methods from some of the most successful prediction teams, and progress in various aspects of the modeling.
Prediction methods are assessed on the basis of the analysis of a large number of blind predictions of protein structure. Summary of numerical evaluation of the tertiary structure prediction methods tested in the latest CASP experiment can be found on this web page. The main numerical measures used in evaluations are described in the papers [1] , [2] . The latter paper also contains explanations of data handling procedures and guidelines for navigating the data presented on this website.

Some of the best performing methods are implemented as fully automated servers and therefore can be used by public for protein structure modeling.

To proceed to the pages related to the latest CASP experiments click on the logo below:

CASP13 Home   FORCASP Forum

Discussion Forum

of docking interactions
Continuous Automated Model EvaluatiOn
CASP_Commons is now open for business: 30 research groups are awaiting results of our modeling (listed below). Prediction Center Team -- Alan Rein (NI ...
Community Nominated Targets, Data-assisted Prediction in CASP13, and CASP_Commons
Background Together with Dr. Gaetano Montelione (Rutgers), John Tainer (MD Anderson), and Emily Tai (NIH), CASP has launched an initiative to provide structure information for some proteins with hi ...
Opportunity to obtain the structure of a protein of interest in your research
We are happy to announce an opportunity to obtain the three-dimensional structure of proteins you are working on. Dr. Gaetano Montelione and colleagues ( will determine ...
Protein Structure Prediction Center
Sponsored by the US National Institute of General Medical Sciences (NIH/NIGMS)
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