Abstract
Current projects for the massive characterization of proteomes are generating protein sequences and, to less extent, three dimensional structures with unknown function. Experimentally determining functional features of a protein is expensive, time consuming and difficult to automate. There is therefore a demand for computational methods for predicting protein functional features, which can be coupled to the pipelines of genome sequencing and structure determination. This review focuses on current in-silico methods for predicting regions in proteins with some functional importance (catalytic sites, binding sites, protein interaction regions, etc.) using sequence and/or three-dimensional structure information.
Keywords: Functional site, active site, binding site, protein function, protein interaction
Current Bioinformatics
Title: Computational Prediction of Functionally Important Regions in Proteins
Volume: 1 Issue: 1
Author(s): Florencio Pazos and Jung-Wook Bang
Affiliation:
Keywords: Functional site, active site, binding site, protein function, protein interaction
Abstract: Current projects for the massive characterization of proteomes are generating protein sequences and, to less extent, three dimensional structures with unknown function. Experimentally determining functional features of a protein is expensive, time consuming and difficult to automate. There is therefore a demand for computational methods for predicting protein functional features, which can be coupled to the pipelines of genome sequencing and structure determination. This review focuses on current in-silico methods for predicting regions in proteins with some functional importance (catalytic sites, binding sites, protein interaction regions, etc.) using sequence and/or three-dimensional structure information.
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Cite this article as:
Pazos Florencio and Bang Jung-Wook, Computational Prediction of Functionally Important Regions in Proteins, Current Bioinformatics 2006; 1 (1) . https://dx.doi.org/10.2174/157489306775330633
DOI https://dx.doi.org/10.2174/157489306775330633 |
Print ISSN 1574-8936 |
Publisher Name Bentham Science Publisher |
Online ISSN 2212-392X |
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