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FOLD RECOGNITION USING ProFIT Jaritz M., Domingues F., Floeckner H. and Sippl M. Markus JARITZ Center for Applied Molecular Engineering University of Salzburg Jakob Haringer Strasse 1 5020 SALZBURG AUSTRIA We analyzed the quality of predictions made by ProFIT1 using several target sequences of known structure. The ProFIT user did not know in advance the structure of the targets and was asked to predict a fold similar to the native one out of a database of 1300 structures. In each case the target structure was excluded from this database. Also, the sequence homology between each target and any of the 1300 folds was not higher than 25%. The sequence was threaded over the database for each of 20 different parameter sets. The thread scores were averaged and used to sort the results (model/alignments). The top scoring results were then analyzed case by case. We looked for good models /alignments where insertions and deletions should be in loop regions where they could be modeled without disrupting the overall fold. Here we present four representative cases. Three are successful predictions (beta spectrin, a phosphatase, a nucleoside phosphoryase), the fourth is an unsuccessful case (NFKB P50). The quality of the predictions and of the sequence-structure alignments was assayed by structure-structure comparison using ProSup2. REFERENCES 1. Floeckner,H., Braxenthaler,M., Lackner,P.,Jaritz,M., Ortner,M., Sippl,M.J. Progress in fold recognition. Proteins, 23, 376-386, (1995). 2. Feng,Z.-K. & Sippl, M.J. Optimum superimposition of protein structures, ambiguities and implications. Folding and Design, 1, 123-132, (1996). ## Back to the list of abstracts