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Articles

Amino acid composition analysis of secondary transport proteins from Escherichia coli with relation to functional classification, ligand specificity and structure

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Pages 2205-2220 | Received 05 Oct 2014, Accepted 10 Dec 2014, Published online: 14 Jan 2015
 

Abstract

We have performed an amino acid composition (AAC) analysis of the complete sequences for 235 secondary transport proteins from Escherichia coli, which have functions in the uptake and export of organic and inorganic metabolites, efflux of drugs and in controlling membrane potential. This revealed the trends in content for specific amino acid types and for combinations of amino acids with similar physicochemical properties. In certain proteins or groups of proteins, the so-called spikes of high content for a specific amino acid type or combination of amino acids were identified and confirmed statistically, which in some cases could be directly related to function and ligand specificity. This was prevalent in proteins with a function of multidrug or metal ion efflux. Any tool that can help in identifying bacterial multidrug efflux proteins is important for a better understanding of this mechanism of antibiotic resistance. Phylogenetic analysis based on sequence alignments and comparison of sequences at the N- and C-terminal ends confirmed transporter Family classification. Locations of specific amino acid types in some of the proteins that have crystal structures (EmrE, LacY, AcrB) were also considered to help link amino acid content with protein function. Though there are limitations, this work has demonstrated that a basic analysis of AAC is a useful tool to use in combination with other computational and experimental methods for classifying and investigating function and ligand specificity in a large group of transport or other membrane proteins, including those that are molecular targets for development of new drugs.

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Acknowledgements

MS thanks the deputy of research and technology, Hamadan University of Medical Sciences, Hamadan, Iran, for financial support.

Additional information

Funding

This work was supported by the EU EDICT consortium (contract 201924).

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