期刊
JOURNAL OF THEORETICAL BIOLOGY
卷 462, 期 -, 页码 221-229出版社
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jtbi.2018.11.010
关键词
Toxin; Reduced amino acid; Biological property; Prediction performance; Classifiers
资金
- National Natural Science Foundation of China [31501078, 61561036, 61602135]
- Heilongjiang Postdoctoral Research Foundation [LBH-Z15153]
- China Postdoctoral Science Foundation [2016M590290]
The animal toxin proteins are one of the disulfide rich small peptides that detected in venomous species. They are used as pharmacological tools and therapeutic agents in medicine for the high specificity of their targets. The successful analysis and prediction of toxin proteins may have important signification for the pharmacological and therapeutic researches of toxins. In this study, significant differences were found between the toxins and the non-toxins in amino acid compositions and several important biological properties. The random forest was firstly proposed to predict the animal toxin proteins by selecting 400 pseudo amino acid compositions and the dipeptide compositions of reduced amino acid alphabet as the input parameters. Based on dipeptide composition of reduced amino acid alphabet with 13 reduced amino acids, the best overall accuracy of 85.71% was obtained. These results indicated that our algorithm was an efficient tool for the animal toxin prediction. (C) 2018 Elsevier Ltd. All rights reserved.
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