Abstract
The rapid growth of the Protein Data Bank (PDB) highlights a great challenge for researchers to predict the binding sites of protein for specific metal ion(s). Experimental determination of functional features of a protein is expensive, time consuming and difficult to automate. Therefore, there is a great demand of computational methods for predicting functional features of protein. This review sheds light on currently available in-silico methods including different tools and databases which are based on various information of metal ion and their binding sites (protein residue length, amino acid composition, geometrical and molecular information etc.) and determines the efficiency, speed and accuracy by using diverse algorithms which make the tools beneficial.
Keywords: Computational method, Metal binding site, Motif, PDB, Metalloprotein, Stand alone tools, Metal binding Site Predictor, GRID, CHED, MSDsite
Current Bioinformatics
Title: Tools for Predicting Metal Binding Sites in Protein: A Review
Volume: 6 Issue: 4
Author(s): Medhavi Mallick, Ambarish Sharan Vidyarthi and Shankaracharya
Affiliation:
Keywords: Computational method, Metal binding site, Motif, PDB, Metalloprotein, Stand alone tools, Metal binding Site Predictor, GRID, CHED, MSDsite
Abstract: The rapid growth of the Protein Data Bank (PDB) highlights a great challenge for researchers to predict the binding sites of protein for specific metal ion(s). Experimental determination of functional features of a protein is expensive, time consuming and difficult to automate. Therefore, there is a great demand of computational methods for predicting functional features of protein. This review sheds light on currently available in-silico methods including different tools and databases which are based on various information of metal ion and their binding sites (protein residue length, amino acid composition, geometrical and molecular information etc.) and determines the efficiency, speed and accuracy by using diverse algorithms which make the tools beneficial.
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Cite this article as:
Mallick Medhavi, Sharan Vidyarthi Ambarish and Shankaracharya , Tools for Predicting Metal Binding Sites in Protein: A Review, Current Bioinformatics 2011; 6 (4) . https://dx.doi.org/10.2174/157489311798072990
DOI https://dx.doi.org/10.2174/157489311798072990 |
Print ISSN 1574-8936 |
Publisher Name Bentham Science Publisher |
Online ISSN 2212-392X |
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