Literature DB >> 15987894

The effect of long-range interactions on the secondary structure formation of proteins.

Daisuke Kihara1.   

Abstract

The influence of long-range residue interactions on defining secondary structure in a protein has long been discussed and is often cited as the current limitation to accurate secondary structure prediction. There are several experimental examples where a local sequence alone is not sufficient to determine its secondary structure, but a comprehensive survey on a large data set has not yet been done. Interestingly, some earlier studies denied the negative effect of long-range interactions on secondary structure prediction accuracy. Here, we have introduced the residue contact order (RCO), which directly indicates the separation of contacting residues in terms of the position in the sequence, and examined the relationship between the RCO and the prediction accuracy. A large data set of 2777 nonhomologous proteins was used in our analysis. Unlike previous studies, we do find that prediction accuracy drops as residues have contacts with more distant residues. Moreover, this negative correlation between the RCO and the prediction accuracy was found not only for beta-strands, but also for alpha-helices. The prediction accuracy of beta-strands is lower if residues have a high RCO or a low RCO, which corresponds to the situation that a beta-sheet is formed by beta-strands from different chains in a protein complex. The reason why the current study draws the opposite conclusion from the previous studies is examined. The implication for protein folding is also discussed.

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Year:  2005        PMID: 15987894      PMCID: PMC2279307          DOI: 10.1110/ps.051479505

Source DB:  PubMed          Journal:  Protein Sci        ISSN: 0961-8368            Impact factor:   6.725


  52 in total

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Journal:  Nature       Date:  1996-04-25       Impact factor: 49.962

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Journal:  Biopolymers       Date:  1983-12       Impact factor: 2.505

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Journal:  Proteins       Date:  1994-05

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10.  Benchmarking secondary structure prediction for fold recognition.

Authors:  Liam J McGuffin; David T Jones
Journal:  Proteins       Date:  2003-08-01
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  37 in total

1.  Building native protein conformation from highly approximate backbone torsion angles.

Authors:  Haipeng Gong; Patrick J Fleming; George D Rose
Journal:  Proc Natl Acad Sci U S A       Date:  2005-10-26       Impact factor: 11.205

2.  The implications of higher (or lower) success in secondary structure prediction of chain fragments.

Authors:  Chung-Jung Tsai; Ruth Nussinov
Journal:  Protein Sci       Date:  2005-08       Impact factor: 6.725

3.  Secondary structure determines protein topology.

Authors:  Patrick J Fleming; Haipeng Gong; George D Rose
Journal:  Protein Sci       Date:  2006-07-05       Impact factor: 6.725

4.  A Consensus Data Mining secondary structure prediction by combining GOR V and Fragment Database Mining.

Authors:  Taner Z Sen; Haitao Cheng; Andrzej Kloczkowski; Robert L Jernigan
Journal:  Protein Sci       Date:  2006-09-25       Impact factor: 6.725

5.  Consensus Data Mining (CDM) Protein Secondary Structure Prediction Server: combining GOR V and Fragment Database Mining (FDM).

Authors:  Haitao Cheng; Taner Z Sen; Robert L Jernigan; Andrzej Kloczkowski
Journal:  Bioinformatics       Date:  2007-07-27       Impact factor: 6.937

6.  Mimicking the folding pathway to improve homology-free protein structure prediction.

Authors:  Joe DeBartolo; Andrés Colubri; Abhishek K Jha; James E Fitzgerald; Karl F Freed; Tobin R Sosnick
Journal:  Proc Natl Acad Sci U S A       Date:  2009-02-23       Impact factor: 11.205

Review 7.  The loop hypothesis: contribution of early formed specific non-local interactions to the determination of protein folding pathways.

Authors:  Tomer Orevi; Gil Rahamim; Gershon Hazan; Dan Amir; Elisha Haas
Journal:  Biophys Rev       Date:  2013-04-12

Review 8.  From local structure to a global framework: recognition of protein folds.

Authors:  Agnel Praveen Joseph; Alexandre G de Brevern
Journal:  J R Soc Interface       Date:  2014-04-16       Impact factor: 4.118

9.  Effect of using suboptimal alignments in template-based protein structure prediction.

Authors:  Hao Chen; Daisuke Kihara
Journal:  Proteins       Date:  2011-01

10.  SPINE X: improving protein secondary structure prediction by multistep learning coupled with prediction of solvent accessible surface area and backbone torsion angles.

Authors:  Eshel Faraggi; Tuo Zhang; Yuedong Yang; Lukasz Kurgan; Yaoqi Zhou
Journal:  J Comput Chem       Date:  2011-11-02       Impact factor: 3.376

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