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Predicting Protein Metal Binding Sites with RBF Networks based on PSSM Profiles and Additional Properties

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Background: Metal atoms are involved in many biological mechanisms, such as protein structure stability, apoptosis and aging. Therefore, identifying metal-binding sites in proteins is an important issue in helping biologists better understand the workings of these mechanisms.

Methods: We propose a method based on Position Specific Scoring Matrix (PSSM) profiles and additional information (conservation score and solvent accessible surface area (ASA)) to identify the metal-binding residues in proteins.

Results: We have selected a non-redundant set of 262 metal-binding proteins and 617 disulfide proteins as the independent test set. The proposed method can predict metal-binding sites at 51.0% recall and 73.4% precision. Comparing with the previous work of A. Passerini et al., the proposed method can improve over 7% of precision with the same level of recall on the independent dataset.

Conclusions: We have developed a novel approach based on PSSM profiles and additional properties for identifying metal-binding sites from proteins. The proposed approach achieved a significant improvement with newly discovered metal-binding proteins and disulfide proteins.
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Keywords: Metal-binding proteins; MetalDetector; PSI-BLAST; PSSM; RBF networks; accessible surface area; frequency; metal-binding sites; non-redundant; β-barrel proteins

Document Type: Research Article

Affiliations: Department of Computer Science and Engineering, Yuan Ze University, Chung-Li, Taiwan.

Publication date: 01 June 2012

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  • Current Bioinformatics aims to publish all the latest and outstanding developments in bioinformatics. Each issue contains a series of timely, in-depth reviews written by leaders in the field, covering a wide range of the integration of biology with computer and information science.

    The journal focuses on reviews on advances in computational molecular/structural biology, encompassing areas such as computing in biomedicine and genomics, computational proteomics and systems biology, and metabolic pathway engineering. Developments in these fields have direct implications on key issues related to health care, medicine, genetic disorders, development of agricultural products, renewable energy, environmental protection, etc.

    Current Bioinformatics is an essential journal for all academic and industrial researchers who want expert knowledge on all major advances in bioinformatics.
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