FlexSLiM: a Novel Approach for Short Linear Motif Discovery in Protein Sequences

被引:0
|
作者
Li, Xiaoman [1 ]
Ge, Ping [2 ]
Hu, Haiyan [2 ]
机构
[1] Univ Cent Florida, Burnett Sch Biomed Sci, Orlando, FL 32816 USA
[2] Univ Cent Florida, Dept Comp Sci, Orlando, FL 32816 USA
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
Short linear motif; protein sequences; frequent pattern mining; deterministic finite automaton; WEB SERVER; PREDICTION; REGIONS; DOMAIN; ELM;
D O I
10.1145/3194480.3194501
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Short linear motifs are 3 to 11 amino acid long peptide patterns that play important regulatory roles in modulating protein activities. Although they are abundant in proteins, it is often difficult to discover them by experiments, because of the low affinity binding and transient interaction of short linear motifs with their partners. Moreover, available computational methods cannot effectively predict short linear motifs, due to their short and degenerate nature. Here we developed a novel approach, FlexSLiM, for reliable discovery of short linear motifs in protein sequences. By testing on simulated data and benchmark experimental data, we demonstrated that FlexSLiM more effectively identifies short linear motifs than existing methods. We provide a general tool that will advance the understanding of short linear motifs, which will facilitate the research on protein targeting signals, protein post-translational modifications, and many others.
引用
收藏
页码:32 / 39
页数:8
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