iSP-RAAC: Identify Secretory Proteins of Malaria Parasite Using Reduced Amino Acid Composition
| Autor: | Qilemuge Xi, Yongchun Zuo, Lei Zheng, Shenghui Huang, Haoyue Zhang, Wuritu Yang |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Plasmodium falciparum
Computational biology Tripeptide Plasmodium 03 medical and health sciences 0302 clinical medicine Sequence Analysis Protein Drug Discovery medicine Animals Parasite hosting Amino Acid Sequence Amino Acids Databases Protein Pathogen 030304 developmental biology chemistry.chemical_classification 0303 health sciences biology Organic Chemistry Prostatic Secretory Proteins General Medicine biology.organism_classification medicine.disease Computer Science Applications Amino acid Secretory protein Amino acid composition chemistry 030220 oncology & carcinogenesis Algorithms Malaria |
| Zdroj: | Combinatorial Chemistry & High Throughput Screening. 23:536-545 |
| ISSN: | 1386-2073 |
| Popis: | Background: As the pathogen of malaria, malaria parasite secretes a variety of proteins for its growth and reproduction. Objective: The identification of the secretory proteins of malaria parasite has crucial reference significance for the development of anti-malaria vaccines as well as medicine. Methods: In this study, a computational classification method was developed to identify the secreted proteins of Plasmodium. Amino acid composition, dipeptide composition, and tripeptide composition as well as reduced amino acids alphabets were proposed to illuminate protein sequences. We further used SVM to train and predict respectively and optimized the features. Results: 74 types of reduced amino acids alphabets were employed to predict secretory proteins. The results showed that the accuracy improved to 91.67% with 0.84 Mathew’s correlation coefficient (MCC) by dipeptide composition, and the highest prediction accuracy reached 92.26% after feature selection, which demonstrated that our method is prominent and reliable in the field of malaria parasite secreted proteins prediction. Conclusion: A intuitive web server iSP-RAAC (http://bioinfor.imu.edu.cn/isppseraac) was established for the convenience of most experimental scientists. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|