title: Competitive assessment of protein fold recognition and alignment accuracy.
abstract: The predictions made for fold recognition and modeling accuracy at the 1996 Critical Assessment of Structure Prediction meeting (CASP2) were assessed to discover which groups did best. With 32 groups making a total of 369 predictions, it was necessary to use simple criteria for distinguishing between the entries. By focusing on the predictors' ability to use the sequence of the unknown target structure to recognize the target fold from a database of known folds and also on the quality of the model judged by the accuracy of the predicted alignment, it is easy to determine the best predictions for a given target. Assessing overall performance of the predictors on all the targets is much more difficult and use was made of weighted averages of fold recognition and alignment accuracy with and without normalization for target difficulty. By plotting these results in two dimensions the winning groups stand out, allowing readers to focus their attention on the most promising methods. When the present results are compared with the results of the earlier CASP1 meeting, held in 1994, it is clear that threading predictions have progressed dramatically. For this assessor, the strongest lesson learned is that subjectivity is pervasive and affects us all. It is abundantly clear that the blind predictions made at CASP are essential if progress is to be made in predicting protein structure.
authors.affiliation: Department of Structural Biology, Stanford University School of Medicine, CA 94305, USA. michael.levitt@stanford.edu
authors.forename: M
authors.initials: M
authors.lastname: Levitt
mesh_terms: D008958:Models, Molecular; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry; D015203:Reproducibility of Results; D016415:Sequence Alignment
chemical_list: D011506:Proteins