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KMID : 0381120110330050565
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Genes and Genomics
2011 Volume.33 No. 5 p.565 ~ p.565
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Comparative study of ammonium transporters in different organisms by study of a large number of structural protein features via data mining algorithms
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Tahrokh Ehsan
Ebrahimi Mansour
Ebrahimi Mahdi
Zamansani Fatemeh
Sarvestani Narjes Rahpeyma
Mohammadi-Dehcheshmeh Manijeh
Ghaemi Mohammad Reza
Ebrahimie Esmaeil
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Abstract
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Ammonium is an excellent nitrogen source, and ammonium transfer is a fundamental process in most organisms. Membrane transport of ammonium is the key component of nitrogen metabolism mediated by Ammonium Transporter/Methylamine Permease/Rhesus (AMT/MEP/Rh) protein family. Ammonium transporters play different physiological roles in various organisms. Here, we looked at the protein characteristics of ammonium transporters in different organisms to create a link between protein characteristics and the organism. In order to increase the accuracy and precision of the employed models, for the first time, an attempt was made to cover all structural aspects of ammonium transporters in animals, bacteria, fungi, plants, and human by extracting and calculating 874 protein attributes of primary, secondary, and tertiary structures for each ammonium transporter. Then, various weighting and modeling algorithms were applied to determine how structural protein features change between organisms. Considering a large number of protein attributes made it possible to detect key protein characteristics in the structure of ammonium transporters. The results, for the first time, indicated that His-based features including count/frequency of His and frequency/count of Ile-His were the most significant features generating different types of ammonium transporters within organisms. Within different tested models, the C5.0 model was the most efficient and precise model for discrimination of organism type, based on ammonium transporter sequence, with the precision of 94.85%. The determination of protein characteristics of ammonium transporters in different organisms provides a new vista for understanding the evolution of transporters based on the modulation of protein characteristics and facilitates engineering of new transporters. In our point of view, dissecting a large number of structural protein characteristics through data mining algorithms provides a novel functional strategy for studying evolution and phylogeny. This research will serve as a basis for future studies on engineering novel ammonium transporters.
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KEYWORD
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Bioinformatics, Evolution, Modeling, Protein, Ammonium transporters
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