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Proteins. 2014 Jul;82(7):1503-11. doi: 10.1002/prot.24520. Epub 2014 Feb 18.

PRIMSIPLR: prediction of inner-membrane situated pore-lining residues for alpha-helical transmembrane proteins.

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Center for Bioinformatics, Saarland University, D-66041, Saarbrücken, Germany.


Transmembrane proteins such as transporters and channels mediate the passage of inorganic and organic substances across biological membranes through their central pore. Pore-lining residues (PLRs) that make direct contacts to the substrates have a crucial impact on the function of the protein and, hence, their identification is a key step in mechanistic studies. Here, we established a nonredundant data set containing the three-dimensional (3D) structures of 90 α-helical transmembrane proteins and annotated the PLRs of these proteins by a pore identification software. A support vector machine was then trained to distinguish PLRs from other residues based on the protein sequence alone. Using sixfold cross-validation, our best performing predictor gave a Matthews's correlation coefficient of 0.41 with an accuracy of 0.86, sensitivity of 0.61, and specificity of 0.89, respectively. We provide a novel software tool that will aid biomedical scientists working on transmembrane proteins with unknown 3D structures. Both standalone version and web service are freely available from the URL


amino acid composition; evolutionary conservation; imbalanced data; pore identification; support vector machine; transmembrane protein

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