Using Reduced Amino Acid Alphabet and Biological Properties to Analyze and Predict Animal Neurotoxin Protein

(E-pub Ahead of Print)

Author(s): Yao Yu, Shiyuan Wang, Yakun Wang, Yiyin Cao, Chunlu Yu, Yi Pan, Dongqing Su, Qianzi Lu, Yongchun Zuo, Lei Yang*.

Journal Name: Current Drug Metabolism

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Abstract:

The animal neurotoxin proteins are one of the most common functional groups among the animal toxin proteins. Because of the high affinity of these animal neurotoxin proteins in some special target site, they were usually used as pharmacological tools and therapeutic agents in medicine to gain deep insights into the function of the nervous system. Thus, it was very important to characterize and predict the animal neurotoxin proteins. In this study, the differences between the animal neurotoxin proteins and nontoxin proteins were analyzed. Significant differences were found between them. In addition, the support vector machine was proposed to predict the animal neurotoxin proteins. The predictive results of our classifier achieved the overall accuracy of 96.46%. Furthermore, the random forest and k-nearest neighbors were applied to predict the animal neurotoxin proteins. The compared results indicated that the predictive performances of our classifier were better than other two algorithms.

Keywords: neurotoxin protein, reduced amino acid alphabet, biological property, support vector machine.

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Article Details

(E-pub Ahead of Print)
DOI: 10.2174/1389200221666200520090555
Price: $95

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