Literature DB >> 9619589

Prediction of beta-turns.

Y D Cai1, H Yu, K C Chou.   

Abstract

Kohonen's self-organization model, a neural network model, is applied to predict the beta-turns in proteins. There are 455 beta-turn tetrapeptides and 3807 non-beta-turn tetrapeptides in the training database. The rates of correct prediction for the 110 beta-turn tetrapeptides and 30,229 non-beta-turn tetrapeptides in the testing database are 81.8% and 90.7%, respectively. The high quality of prediction of neural network model implies that the residue-coupled effect along a polypeptide chain is important for the formation of reversal turns, such as beta-turns, during the process of protein folding.

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Year:  1998        PMID: 9619589     DOI: 10.1023/a:1022559300504

Source DB:  PubMed          Journal:  J Protein Chem        ISSN: 0277-8033


  2 in total

1.  Insight into a molecular interaction force supporting peptide backbones and its implication to protein loops and folding.

Authors:  Qi-Shi Du; Dong Chen; Neng-Zhong Xie; Ri-Bo Huang; Kuo-Chen Chou
Journal:  J Biomol Struct Dyn       Date:  2014-12-22

2.  A method for WD40 repeat detection and secondary structure prediction.

Authors:  Yang Wang; Fan Jiang; Zhu Zhuo; Xian-Hui Wu; Yun-Dong Wu
Journal:  PLoS One       Date:  2013-06-11       Impact factor: 3.240

  2 in total

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