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Prediction of zinc-binding sites in proteins from sequence
Stockholm University, Faculty of Science, Department of Physical, Inorganic and Structural Chemistry, Structural Chemistry. (Sven Hovmöller)
Stockholm University, Faculty of Science, Department of Physical, Inorganic and Structural Chemistry. (Sven Hovmöller)
Stockholm University, Faculty of Science, Department of Physical, Inorganic and Structural Chemistry. (Sven Hovmöller)
2008 (English)In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 24, no 6, 775-782 p.Article in journal (Refereed) Published
Abstract [en]

MOTIVATION: Motivated by the abundance, importance and unique functionality of zinc, both biologically and physiologically, we have developed an improved method for the prediction of zinc-binding sites in proteins from their amino acid sequences. RESULTS: By combining support vector machine (SVM) and homology-based predictions, our method predicts zinc-binding Cys, His, Asp and Glu with 75% precision (86% for Cys and His only) at 50% recall according to a 5-fold cross-validation on a non-redundant set of protein chains from the Protein Data Bank (PDB) (2727 chains, 235 of which bind zinc). Consequently, our method predicts zinc-binding Cys and His with 10% higher precision at different recall levels compared to a recently published method when tested on the same dataset. AVAILABILITY: The program is available for download at www.fos.su.se/~nanjiang/zincpred/download/

Place, publisher, year, edition, pages
2008. Vol. 24, no 6, 775-782 p.
Keyword [en]
zinc-binding, Support Vector Machine, Profile
National Category
Bioinformatics and Systems Biology Mathematics
Research subject
Biochemistry; Molecular Biology
Identifiers
URN: urn:nbn:se:su:diva-32774DOI: 10.1093/bioinformatics/btm618ISI: 000254010400006OAI: oai:DiVA.org:su-32774DiVA: diva2:281508
Projects
protein structure prediction
Available from: 2009-12-16 Created: 2009-12-16 Last updated: 2017-12-12Bibliographically approved
In thesis
1. Protein structure prediction: Zinc-binding sites, one-dimensional structure and remote homology
Open this publication in new window or tab >>Protein structure prediction: Zinc-binding sites, one-dimensional structure and remote homology
2010 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Predicting the three-dimensional (3D) structure of proteins is a central problem in biology. These computationally predicted 3D protein structures have been successfully applied in many fields of biomedicine, e.g. family assignments and drug discovery. The accurate detection of remotely homologous templates is critical for the successful prediction of the 3D structure of proteins. Also, the prediction of one-dimensional (1D) protein structures such as secondary structures and shape strings are useful for predicting the 3D structure of proteins and important for understanding the sequence-structure relationship. In addition, the prediction of the functional sites of proteins, such as metal-binding sites, can not only reveal the important function of proteins (even in the absence of the 3D structure) but also facilitate the prediction of the 3D structure.

Here, three novel methods in the field of protein structure prediction are presented: PREDZINC, a method for predicting zinc-binding sites in proteins; Frag1D, a method for predicting the 1D structure of proteins; and FragMatch, a method for detecting remotely homologous proteins. These methods compete satisfactorily with the best methods previously published and contribute to the task of protein structure prediction.

Place, publisher, year, edition, pages
Stockholm: Department of Materials and Environmental Chemistry (MMK), Stockholm University, 2010. 81 p.
Keyword
protein structure prediction, zinc-binding, profile, homology detection, shape string
National Category
Bioinformatics and Systems Biology Biochemistry and Molecular Biology Biochemistry and Molecular Biology
Research subject
Structural Chemistry
Identifiers
urn:nbn:se:su:diva-34094 (URN)978-91-7155-984-5 (ISBN)
Public defence
2010-02-09, Magnélisalen, Kemiska övningslaboratoriet, Svante Arrhenius väg 16 B, Magnélisalen, 10:00 (English)
Opponent
Supervisors
Projects
Protein structure prediction
Note
At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 3: Manuscript.Available from: 2010-01-18 Created: 2010-01-05 Last updated: 2010-12-29Bibliographically approved

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Publisher's full texthttp://bioinformatics.oxfordjournals.org/cgi/content/abstract/24/6/775

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