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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).
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