Flexslim: A Novel Approach For Short Linear Motif Discovery In Protein Sequences

Keywords

Deterministic finite automaton; Frequent pattern mining; Protein sequences; Short linear motif

Abstract

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.

Publication Date

3-12-2018

Publication Title

ACM International Conference Proceeding Series

Number of Pages

32-39

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1145/3194480.3194501

Socpus ID

85047134283 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85047134283

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