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Predicting DNA-binding proteins: approached from Chou’s pseudo amino acid composition and other specific sequence features

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Summary.

DNA-binding proteins play a pivotal role in gene regulation. It is vitally important to develop an automated and efficient method for timely identification of novel DNA-binding proteins. In this study, we proposed a method based on alone the primary sequences of proteins to predict the DNA-binding proteins. DNA-binding proteins were encoded by autocross-covariance transform, pseudo-amino acid composition, dipeptide composition, respectively and also the different combinations of the three encoded methods; further, these feature matrices were applied to support vector machine classifiers to predict the DNA-binding proteins. All modules were trained and validated by the jackknife cross-validation test. Through comparing the performance of these substituted modules, the best result was obtained from pseudo-amino acid composition with the overall accuracy of 96.6% and the sensitivity of 90.7%. The results suggest that it can efficiently predict the novel DNA-binding proteins only using the primary sequences.

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  1. College of Chemistry, Sichuan University, Chengdu, China

    Y. Fang, Y. Guo, Y. Feng & M. Li

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  1. Y. Fang
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  2. Y. Guo
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Correspondence to M. Li.

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Authors’ address: Menglong Li, College of Chemistry, Sichuan University, Chengdu, Sichuan 610064, P.R. China

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Fang, Y., Guo, Y., Feng, Y. et al. Predicting DNA-binding proteins: approached from Chou’s pseudo amino acid composition and other specific sequence features. Amino Acids 34, 103–109 (2008). https://doi.org/10.1007/s00726-007-0568-2

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