The Significant and Profound Impacts of Chou’s “wenxiang” Diagram


In this short review paper, the significant and profound impacts of the Chou’s “wenxiang diagram” have been briefly presented with crystal clear convincingness.

Share and Cite:

Chou, K. (2020) The Significant and Profound Impacts of Chou’s “wenxiang” Diagram. Voice of the Publisher, 6, 102-103. doi: 10.4236/vp.2020.63010.

The Chou’s wenxiang diagram, named after Kuo-Chen Chou [1] [2].

Because the wenxiang diagram is generated by a conical projection of a helix onto a plane, with the start (N-terminus) of the helix at the edge and the end toward the center, the location of each residue in a helix is not only defined by an angle around the diagram’s center, but is also defined by its radius from the center of the diagram in the number of turns, which corresponds to its distance along the helix, in the number of turns. Therefore, in principle, the wenxiang diagram can be used to represent an alpha-helix of any length.

The impacts of the “wenxiang diagram” are significant and profound (see, e.g., [3] - [12]).

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Chou, K.C., Liu, W., Maggiora, G.M. and Zhang, C.T. (1998) Prediction and Classification of Domain Structural Classes. Proteins: Structure, Function, and Bioinformatics, 31, 97-103.<97::AID-PROT8>3.0.CO;2-E
[2] Chou, K.C. and Maggiora, G.M. (1998) Domain Structural Class Prediction. Protein Engineering, 11, 523-538.
[3] Zhou, G.P. (2011) The Disposition of the LZCC Protein Residues in Wenxiang Diagram Provides New Insights into the Protein-Protein Interaction Mechanism. Journal of Theoretical Biology, 284, 142-148.
[4] Zhou, G.P., Chen, D., Liao, S. and Huang, R.B. (2016) Recent Progresses in Studying Helix-Helix Interactions in Proteins by Incorporating the Wenxiang Diagram into the NMR Spectroscopy. Current Topics in Medicinal Chemistry, 16, 581-590.
[5] Cai, Y.D. and Zhou, G.P. (2000) Prediction of Protein Structural Classes by Neural Network. Biochimie, 82, 783-785.
[6] Zhou, G.P. and Assa-Munt, N. (2001) Some Insights into Protein Structural Class Prediction. Proteins: Structure, Function, and Bioinformatics, 44, 57-59.
[7] Cai, Y.D., Zhou, G.P. and Chou, K.C. (2003) Support Vector Machines for Predicting Membrane Protein Types by Using Functional Domain Composition. Biophysical Journal, 84, 3257-3263.
[8] Zhou, G.P. and Doctor, K. (2003) Subcellular Location Prediction of Apoptosis Proteins. Proteins: Structure, Function, and Bioinformatics, 50, 44-48.
[9] Cai, Y.D., Zhou, G.P., Jen, C.H., Lin, S.L. and Chou, K.C. (2004) Identify Catalytic Triads of Serine Hydrolases by Support Vector Machines. Journal of Theoretical Biology, 228, 551-557.
[10] Zhou, G.P. and Cai, Y.D. (2006) Predicting Protease Types by Hybridizing Gene Ontology and Pseudo Amino Acid Composition. Proteins: Structure, Function, and Bioinformatics, 63, 681-684.
[11] Zhou, G.P. and Huang, R.B. (2013) The pH-Triggered Conversion of the PrP(c) to PrP(sc.). Current Topics in Medicinal Chemistry, 13, 1152-1163.
[12] Lu, B., Liu, X.H., Lia, S.M., Lu, L.Z., Chen, D., Troy II, F.A., Huang, R.B. and Zhou, G.P. (2019) A Possible Modulation Mechanism of Intramolecular and Intermolecular Interactions for NCAM Polysialylation and Cell Migration. Current Topics in Mecinal Chemistry, 19.

Copyright © 2021 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.