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Prediction of disulfide connectivity in proteins
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Abstract
Motivation: A major problem in protein structure predictionis the correct location of disulfide bridges in cysteine-rich proteins. In protein-folding prediction, the location of disulfide bridges can strongly reduce the search in the conformational space. Therefore the correct prediction of the disulfide connectivity starting from the protein residue sequencemay also help in predicting its 3D structure.
Results: In this paper we equate the problem of predicting the disulfide connectivity in proteins to a problem of finding the graph matching with the maximum weight. The graph vertices are the residues of cysteine-forming disulfide bridges, and the weight edges are contact potentials. In order to solve this problem we develop and test different residue contact potentials. The best performing one, based on the Edmonds–Gabow algorithm and Monte-Carlo simulated annealing reaches an accuracy significantly higher than that obtained with a general mean force contact potential. Significantly, in the case of proteins with four disulfide bonds in the structure, the accuracy is 17 times higher than that of a random predictor. The method presented here can be used to locate putative disulfide bridges in protein-folding.
Availability: The program is available upon request from the authors.
Contact: Casadio@alma.unibo.it; Piero@biocomp.unibo.it
Title: Prediction of disulfide connectivity in proteins
Description:
Abstract
Motivation: A major problem in protein structure predictionis the correct location of disulfide bridges in cysteine-rich proteins.
In protein-folding prediction, the location of disulfide bridges can strongly reduce the search in the conformational space.
Therefore the correct prediction of the disulfide connectivity starting from the protein residue sequencemay also help in predicting its 3D structure.
Results: In this paper we equate the problem of predicting the disulfide connectivity in proteins to a problem of finding the graph matching with the maximum weight.
The graph vertices are the residues of cysteine-forming disulfide bridges, and the weight edges are contact potentials.
In order to solve this problem we develop and test different residue contact potentials.
The best performing one, based on the Edmonds–Gabow algorithm and Monte-Carlo simulated annealing reaches an accuracy significantly higher than that obtained with a general mean force contact potential.
Significantly, in the case of proteins with four disulfide bonds in the structure, the accuracy is 17 times higher than that of a random predictor.
The method presented here can be used to locate putative disulfide bridges in protein-folding.
Availability: The program is available upon request from the authors.
Contact: Casadio@alma.
unibo.
it; Piero@biocomp.
unibo.
it.
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