Predicting Secretory Proteins of Malaria Parasite by Incorporating Sequence Evolution Information into Pseudo Amino Acid Composition via Grey System Model

被引:62
|
作者
Lin, Wei-Zhong [1 ,2 ]
Fang, Jian-An [2 ]
Xiao, Xuan [1 ,3 ]
Chou, Kuo-Chen [3 ]
机构
[1] Jing De Zhen Ceram Inst, Dept Comp, Jing De Zhen, Peoples R China
[2] Donghua Univ, Informat Sci & Technol Sch, Shanghai, Peoples R China
[3] Gordon Life Sci Inst, San Diego, CA USA
来源
PLOS ONE | 2012年 / 7卷 / 11期
基金
中国国家自然科学基金;
关键词
DNA-BINDING PROTEINS; FUSING FUNCTIONAL DOMAIN; WEB SERVER; SUBCELLULAR-LOCALIZATION; MEMBRANE-PROTEINS; STRUCTURAL CLASS; GENE ONTOLOGY; IDENTIFICATION; DATABASE; CLASSIFIER;
D O I
10.1371/journal.pone.0049040
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The malaria disease has become a cause of poverty and a major hindrance to economic development. The culprit of the disease is the parasite, which secretes an array of proteins within the host erythrocyte to facilitate its own survival. Accordingly, the secretory proteins of malaria parasite have become a logical target for drug design against malaria. Unfortunately, with the increasing resistance to the drugs thus developed, the situation has become more complicated. To cope with the drug resistance problem, one strategy is to timely identify the secreted proteins by malaria parasite, which can serve as potential drug targets. However, it is both expensive and time-consuming to identify the secretory proteins of malaria parasite by experiments alone. To expedite the process for developing effective drugs against malaria, a computational predictor called "iSMP-Grey" was developed that can be used to identify the secretory proteins of malaria parasite based on the protein sequence information alone. During the prediction process a protein sample was formulated with a 60D (dimensional) feature vector formed by incorporating the sequence evolution information into the general form of PseAAC (pseudo amino acid composition) via a grey system model, which is particularly useful for solving complicated problems that are lack of sufficient information or need to process uncertain information. It was observed by the jackknife test that iSMP-Grey achieved an overall success rate of 94.8%, remarkably higher than those by the existing predictors in this area. As a user-friendly web-server, iSMP-Grey is freely accessible to the public at http://www.jci-bioinfo.cn/iSMP-Grey. Moreover, for the convenience of most experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results without the need to follow the complicated mathematical equations involved in this paper.
引用
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页数:7
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