Many efforts were spent in the last years in bridging the gap between the huge number of sequenced proteins and the relatively few solved structures. Relative Solvent Accessibility (RSA) prediction of residues in protein complexes is a key step towards secondary structure and protein-protein interaction sites prediction. With very different approaches, a number of software tools for RSA prediction have been produced throughout the last twenty years. Here, we present a binary classifier which implements a new method mainly based on sequence homology and implemented by means of look-up tables. The tool exploits residue similarity in solvent exposure pattern of neighboring context in similar protein chains, using BLAST search and DSSP structure. A two-state classification with 89.5% accuracy and 0.79 correlation coefficient against the real data is achieved on a widely used dataset.

A High Performing Tool for Residue Solvent Accessibility Prediction / Palmieri, Lorenzo; Federico, Maria; Leoncini, Mauro; Montangero, Manuela. - STAMPA. - 6865:(2011), pp. 138-152. ((Intervento presentato al convegno 2nd International Conference on Information Technology in Bio- and Medical Informatics, ITBAM 2011 tenutosi a Toulouse, fra nel 29 august-2 september 2011 [10.1007/978-3-642-23208-4_13].

A High Performing Tool for Residue Solvent Accessibility Prediction

PALMIERI, LORENZO;FEDERICO, Maria;LEONCINI, Mauro;MONTANGERO, Manuela
2011

Abstract

Many efforts were spent in the last years in bridging the gap between the huge number of sequenced proteins and the relatively few solved structures. Relative Solvent Accessibility (RSA) prediction of residues in protein complexes is a key step towards secondary structure and protein-protein interaction sites prediction. With very different approaches, a number of software tools for RSA prediction have been produced throughout the last twenty years. Here, we present a binary classifier which implements a new method mainly based on sequence homology and implemented by means of look-up tables. The tool exploits residue similarity in solvent exposure pattern of neighboring context in similar protein chains, using BLAST search and DSSP structure. A two-state classification with 89.5% accuracy and 0.79 correlation coefficient against the real data is achieved on a widely used dataset.
2nd International Conference on Information Technology in Bio- and Medical Informatics, ITBAM 2011
Toulouse, fra
29 august-2 september 2011
6865
138
152
Palmieri, Lorenzo; Federico, Maria; Leoncini, Mauro; Montangero, Manuela
A High Performing Tool for Residue Solvent Accessibility Prediction / Palmieri, Lorenzo; Federico, Maria; Leoncini, Mauro; Montangero, Manuela. - STAMPA. - 6865:(2011), pp. 138-152. ((Intervento presentato al convegno 2nd International Conference on Information Technology in Bio- and Medical Informatics, ITBAM 2011 tenutosi a Toulouse, fra nel 29 august-2 september 2011 [10.1007/978-3-642-23208-4_13].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/684651
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