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Integration of Evolutionary Features for the Identification of Functionally Important Residues in Major Facilitator Superfamily Transporters SCIE SCOPUS

Title
Integration of Evolutionary Features for the Identification of Functionally Important Residues in Major Facilitator Superfamily Transporters
Authors
Jeon, JYang, JSKim, S
Date Issued
2009-10
Publisher
PUBLIC LIBRARY SCIENCE
Abstract
The identification of functionally important residues is an important challenge for understanding the molecular mechanisms of proteins. Membrane protein transporters operate two-state allosteric conformational changes using functionally important cooperative residues that mediate long-range communication from the substrate binding site to the translocation pathway. In this study, we identified functionally important cooperative residues of membrane protein transporters by integrating sequence conservation and co-evolutionary information. A newly derived evolutionary feature, the co-evolutionary coupling number, was introduced to measure the connectivity of co-evolving residue pairs and was integrated with the sequence conservation score. We tested this method on three Major Facilitator Superfamily (MFS) transporters, LacY, GlpT, and EmrD. MFS transporters are an important family of membrane protein transporters, which utilize diverse substrates, catalyze different modes of transport using unique combinations of functional residues, and have enough characterized functional residues to validate the performance of our method. We found that the conserved cores of evolutionarily coupled residues are involved in specific substrate recognition and translocation of MFS transporters. Furthermore, a subset of the residues forms an interaction network connecting functional sites in the protein structure. We also confirmed that our method is effective on other membrane protein transporters. Our results provide insight into the location of functional residues important for the molecular mechanisms of membrane protein transporters.
URI
https://oasis.postech.ac.kr/handle/2014.oak/12633
DOI
10.1371/JOURNAL.PCBI.1000522
ISSN
1553-734X
Article Type
Article
Citation
PLOS COMPUTATIONAL BIOLOGY, vol. 5, no. 10, page. E1000522 - E1000522, 2009-10
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김상욱KIM, SANGUK
Dept of Life Sciences
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