Literature DB >> 20544377

An analysis of reentrant loops.

Changhui Yan1, Jingru Luo.   

Abstract

Reentrant loops are an important structural motif in alpha-helical transmembrane proteins. A reentrant loop is a structural motif that goes only halfway through the membrane and then turns back to the side from which it originates. The question of what causes the reentrant loops to form such a unique topology is still unanswered. In this study, we try to answer this question by analyzing the hydrophobicity distribution on the amino acid sequences of the reentrant loops. Our results show that reentrant loops have very low hydrophobicity around the deepest point buried in the membrane and relative high hydrophobicity close to the membrane surfaces. We speculate that this hydrophobicity distribution is a major force that stabilizes the unique reentrant loop structure. Our results also show that this hydrophobicity distribution results in special patterns on protein sequences, which can be captured using profile hidden Markov models (HMMs). The resulting profile HMMs can detect reentrant loops on protein sequences with high sensitivity and perfect specificity.

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Substances:

Year:  2010        PMID: 20544377     DOI: 10.1007/s10930-010-9259-z

Source DB:  PubMed          Journal:  Protein J        ISSN: 1572-3887            Impact factor:   2.371


  19 in total

1.  Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes.

Authors:  A Krogh; B Larsson; G von Heijne; E L Sonnhammer
Journal:  J Mol Biol       Date:  2001-01-19       Impact factor: 5.469

2.  BPROMPT: A consensus server for membrane protein prediction.

Authors:  Paul D Taylor; Teresa K Attwood; Darren R Flower
Journal:  Nucleic Acids Res       Date:  2003-07-01       Impact factor: 16.971

3.  An ENSEMBLE machine learning approach for the prediction of all-alpha membrane proteins.

Authors:  Pier Luigi Martelli; Piero Fariselli; Rita Casadio
Journal:  Bioinformatics       Date:  2003       Impact factor: 6.937

4.  Transmembrane proteins in the Protein Data Bank: identification and classification.

Authors:  Gábor E Tusnády; Zsuzsanna Dosztányi; István Simon
Journal:  Bioinformatics       Date:  2004-06-04       Impact factor: 6.937

5.  Membrane protein structure prediction. Hydrophobicity analysis and the positive-inside rule.

Authors:  G von Heijne
Journal:  J Mol Biol       Date:  1992-05-20       Impact factor: 5.469

6.  A combinatorial pattern discovery approach for the prediction of membrane dipping (re-entrant) loops.

Authors:  Gorka Lasso; John F Antoniw; Jonathan G L Mullins
Journal:  Bioinformatics       Date:  2006-07-15       Impact factor: 6.937

7.  Structural classification and prediction of reentrant regions in alpha-helical transmembrane proteins: application to complete genomes.

Authors:  Håkan Viklund; Erik Granseth; Arne Elofsson
Journal:  J Mol Biol       Date:  2006-07-05       Impact factor: 5.469

8.  Hidden Markov models in computational biology. Applications to protein modeling.

Authors:  A Krogh; M Brown; I S Mian; K Sjölander; D Haussler
Journal:  J Mol Biol       Date:  1994-02-04       Impact factor: 5.469

9.  A simple method for displaying the hydropathic character of a protein.

Authors:  J Kyte; R F Doolittle
Journal:  J Mol Biol       Date:  1982-05-05       Impact factor: 5.469

10.  PDB_TM: selection and membrane localization of transmembrane proteins in the protein data bank.

Authors:  Gábor E Tusnády; Zsuzsanna Dosztányi; István Simon
Journal:  Nucleic Acids Res       Date:  2005-01-01       Impact factor: 16.971

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  10 in total

Review 1.  Computational studies of membrane proteins: models and predictions for biological understanding.

Authors:  Jie Liang; Hammad Naveed; David Jimenez-Morales; Larisa Adamian; Meishan Lin
Journal:  Biochim Biophys Acta       Date:  2011-10-12

2.  The Regulatory Domain of Squalene Monooxygenase Contains a Re-entrant Loop and Senses Cholesterol via a Conformational Change.

Authors:  Vicky Howe; Ngee Kiat Chua; Julian Stevenson; Andrew J Brown
Journal:  J Biol Chem       Date:  2015-10-03       Impact factor: 5.157

3.  Substituted cysteine accessibility reveals a novel transmembrane 2-3 reentrant loop and functional role for transmembrane domain 2 in the human proton-coupled folate transporter.

Authors:  Mike R Wilson; Zhanjun Hou; Larry H Matherly
Journal:  J Biol Chem       Date:  2014-07-22       Impact factor: 5.157

Review 4.  Life at the border: adaptation of proteins to anisotropic membrane environment.

Authors:  Irina D Pogozheva; Henry I Mosberg; Andrei L Lomize
Journal:  Protein Sci       Date:  2014-07-02       Impact factor: 6.725

Review 5.  Monotopic Membrane Proteins Join the Fold.

Authors:  Karen N Allen; Sonya Entova; Leah C Ray; Barbara Imperiali
Journal:  Trends Biochem Sci       Date:  2018-10-15       Impact factor: 13.807

Review 6.  Regulation of ER-derived membrane dynamics by the DedA domain-containing proteins VMP1 and TMEM41B.

Authors:  Yutaro Hama; Hideaki Morishita; Noboru Mizushima
Journal:  EMBO Rep       Date:  2022-01-19       Impact factor: 8.807

7.  The topology of pen-2, a γ-secretase subunit, revisited: evidence for a reentrant loop and a single pass transmembrane domain.

Authors:  Xulun Zhang; Chunjiang J Yu; Sangram S Sisodia
Journal:  Mol Neurodegener       Date:  2015-08-22       Impact factor: 14.195

8.  In silico prediction of structure and function for a large family of transmembrane proteins that includes human Tmem41b.

Authors:  Shahram Mesdaghi; David L Murphy; Filomeno Sánchez Rodríguez; J Javier Burgos-Mármol; Daniel J Rigden
Journal:  F1000Res       Date:  2020-12-03

9.  ConPlot: web-based application for the visualization of protein contact maps integrated with other data.

Authors:  Filomeno Sánchez Rodríguez; Shahram Mesdaghi; Adam J Simpkin; J Javier Burgos-Mármol; David L Murphy; Ville Uski; Ronan M Keegan; Daniel J Rigden
Journal:  Bioinformatics       Date:  2021-09-09       Impact factor: 6.937

10.  Insights into the key determinants of membrane protein topology enable the identification of new monotopic folds.

Authors:  Sonya Entova; Jean-Marc Billod; Jean-Marie Swiecicki; Sonsoles Martín-Santamaría; Barbara Imperiali
Journal:  Elife       Date:  2018-08-31       Impact factor: 8.140

  10 in total

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