Literature DB >> 17333485

2DCSi: identification of protein secondary structure and redox state using 2D cluster analysis of NMR chemical shifts.

Ching-Cheng Wang1, Jui-Hung Chen, Wen-Chung Lai, Woei-Jer Chuang.   

Abstract

Chemical shifts of amino acids in proteins are the most sensitive and easily obtainable NMR parameters that reflect the primary, secondary, and tertiary structures of the protein. In recent years, chemical shifts have been used to identify secondary structure in peptides and proteins, and it has been confirmed that (1)H(alpha), (13)C(alpha), (13)C(beta), and (13)C' NMR chemical shifts for all 20 amino acids are sensitive to their secondary structure. Currently, most of the methods are purely based on one-dimensional statistical analyses of various chemical shifts for each residue to identify protein secondary structure. However, it is possible to achieve an increased accuracy from the two-dimensional analyses of these chemical shifts. The 2DCSi approach performs two-dimension cluster analyses of (1)H(alpha), (1)H(N), (13)C(alpha), (13)C(beta), (13)C', and (15)N(H) chemical shifts to identify protein secondary structure and the redox state of cysteine residue. For the analysis of paired chemical shifts of 6 data sets, each of the 20 amino acids has its own 15 two-dimension cluster scattering diagrams. Accordingly, the probabilities for identifying helix and extended structure were calculated by using our scoring matrix. Compared with existing the chemical shift-based methods, it appears to improve the prediction accuracy of secondary structure identification, particularly in the extended structure. In addition, the probability of the given residue to be helix or extended structure is displayed, allows the users to make decisions by themselves.

Entities:  

Mesh:

Substances:

Year:  2007        PMID: 17333485     DOI: 10.1007/s10858-007-9146-x

Source DB:  PubMed          Journal:  J Biomol NMR        ISSN: 0925-2738            Impact factor:   2.582


  17 in total

Review 1.  Review: protein secondary structure prediction continues to rise.

Authors:  B Rost
Journal:  J Struct Biol       Date:  2001 May-Jun       Impact factor: 2.867

2.  An empirical correlation between secondary structure content and averaged chemical shifts in proteins.

Authors:  Anaika B Sibley; Monique Cosman; V V Krishnan
Journal:  Biophys J       Date:  2003-02       Impact factor: 4.033

3.  Bioverse: Functional, structural and contextual annotation of proteins and proteomes.

Authors:  Jason McDermott; Ram Samudrala
Journal:  Nucleic Acids Res       Date:  2003-07-01       Impact factor: 16.971

4.  Simple consensus procedures are effective and sufficient in secondary structure prediction.

Authors:  Mario Albrecht; Silvio C E Tosatto; Thomas Lengauer; Giorgio Valle
Journal:  Protein Eng       Date:  2003-07

5.  Protein energetic conformational analysis from NMR chemical shifts (PECAN) and its use in determining secondary structural elements.

Authors:  Hamid R Eghbalnia; Liya Wang; Arash Bahrami; Amir Assadi; John L Markley
Journal:  J Biomol NMR       Date:  2005-05       Impact factor: 2.835

6.  The chemical shift index: a fast and simple method for the assignment of protein secondary structure through NMR spectroscopy.

Authors:  D S Wishart; B D Sykes; F M Richards
Journal:  Biochemistry       Date:  1992-02-18       Impact factor: 3.162

7.  Knowledge-based protein secondary structure assignment.

Authors:  D Frishman; P Argos
Journal:  Proteins       Date:  1995-12

8.  C alpha and C beta carbon-13 chemical shifts in proteins from an empirical database.

Authors:  M Iwadate; T Asakura; M P Williamson
Journal:  J Biomol NMR       Date:  1999-03       Impact factor: 2.835

9.  Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features.

Authors:  W Kabsch; C Sander
Journal:  Biopolymers       Date:  1983-12       Impact factor: 2.505

Review 10.  Protein chemical shift analysis: a practical guide.

Authors:  D S Wishart; A M Nip
Journal:  Biochem Cell Biol       Date:  1998       Impact factor: 3.626

View more
  9 in total

1.  Uncovering symmetry-breaking vector and reliability order for assigning secondary structures of proteins from atomic NMR chemical shifts in amino acids.

Authors:  Wookyung Yu; Woonghee Lee; Weontae Lee; Suhkmann Kim; Iksoo Chang
Journal:  J Biomol NMR       Date:  2011-10-30       Impact factor: 2.835

2.  Identification of helix capping and b-turn motifs from NMR chemical shifts.

Authors:  Yang Shen; Ad Bax
Journal:  J Biomol NMR       Date:  2012-03       Impact factor: 2.835

3.  CSI 2.0: a significantly improved version of the Chemical Shift Index.

Authors:  Noor E Hafsa; David S Wishart
Journal:  J Biomol NMR       Date:  2014-10-02       Impact factor: 2.835

4.  Application of data mining tools for classification of protein structural class from residue based averaged NMR chemical shifts.

Authors:  Arun V Kumar; Rehana F M Ali; Yu Cao; V V Krishnan
Journal:  Biochim Biophys Acta       Date:  2015-03-07

5.  Characterization of protein secondary structure from NMR chemical shifts.

Authors:  Steven P Mielke; V V Krishnan
Journal:  Prog Nucl Magn Reson Spectrosc       Date:  2009-04-05       Impact factor: 9.795

6.  Predicting the redox state and secondary structure of cysteine residues using multi-dimensional classification analysis of NMR chemical shifts.

Authors:  Ching-Cheng Wang; Wen-Chung Lai; Woei-Jer Chuang
Journal:  J Biomol NMR       Date:  2016-09-09       Impact factor: 2.835

7.  Type I and II β-turns prediction using NMR chemical shifts.

Authors:  Ching-Cheng Wang; Wen-Chung Lai; Woei-Jer Chuang
Journal:  J Biomol NMR       Date:  2014-05-17       Impact factor: 2.835

8.  CSI 3.0: a web server for identifying secondary and super-secondary structure in proteins using NMR chemical shifts.

Authors:  Noor E Hafsa; David Arndt; David S Wishart
Journal:  Nucleic Acids Res       Date:  2015-05-15       Impact factor: 16.971

9.  NMRDSP: an accurate prediction of protein shape strings from NMR chemical shifts and sequence data.

Authors:  Wusong Mao; Peisheng Cong; Zhiheng Wang; Longjian Lu; Zhongliang Zhu; Tonghua Li
Journal:  PLoS One       Date:  2013-12-23       Impact factor: 3.240

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.