Proteome-level assessment of origin, prevalence and function of Leucine-Aspartic Acid (LD) motifs.
Type
ArticleAuthors
Alam, Tanvir
Alazmi, Meshari

Naser, Rayan Mohammad Mahmoud

Huser, Franceline
Momin, Afaque Ahmad Imtiyaz

Astro, Veronica
Hong, Seungbeom
Walkiewicz, Katarzyna Wiktoria
Canlas, Christian G
Huser, Raphaël

Ali, Amal J.

Merzaban, Jasmeen

Adamo, Antonio

Jaremko, Mariusz

Jaremko, Lukasz

Bajic, Vladimir B.

Gao, Xin

Arold, Stefan T.

KAUST Department
Applied Mathematics and Computational Science ProgramBiological and Environmental Sciences and Engineering (BESE) Division
Bioscience Program
Computational Bioscience Research Center (CBRC)
Computer Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Statistics Program
Structural Biology and Engineering
Structural and Functional Bioinformatics Group
KAUST Grant Number
URF/1/1976-04URF/1/3007-01
URF/1/1976-02
BAS/1/1606-01-01
OSR-2015- CRG4-2602
Date
2019-10-04Preprint Posting Date
2018-03-11Permanent link to this record
http://hdl.handle.net/10754/658612
Metadata
Show full item recordAbstract
MOTIVATION:Leucine-aspartic acid (LD) motifs are short linear interaction motifs (SLiMs) that link paxillin family proteins to factors controlling cell adhesion, motility and survival. The existence and importance of LD motifs beyond the paxillin family is poorly understood. RESULTS:To enable a proteome-wide assessment of LD motifs, we developed an active-learning based framework (LDmotif finder; LDMF) that iteratively integrates computational predictions with experimental validation. Our analysis of the human proteome revealed a dozen new proteins containing LD motifs. We found that LD motif signalling evolved in unicellular eukaryotes more than 800 Myr ago, with paxillin and vinculin as core constituents, and nuclear export signal (NES) as a likely source of de novo LD motifs. We show that LD motif proteins form a functionally homogenous group, all being involved in cell morphogenesis and adhesion. This functional focus is recapitulated in cells by GFP-fused LD motifs, suggesting that it is intrinsic to the LD motif sequence, possibly through their effect on binding partners. Our approach elucidated the origin and dynamic adaptations of an ancestral SLiM, and can serve as a guide for the identification of other SLiMs for which only few representatives are known. AVAILABILITY:LDMF is freely available online at www.cbrc.kaust.edu.sa/ldmf; Source code is available at https://github.com/tanviralambd/LD/. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.Citation
Alam, T., Alazmi, M., Naser, R., Huser, F., Momin, A. A., Astro, V., … Arold, S. T. (2019). Proteome-level assessment of origin, prevalence and function of Leucine-Aspartic Acid (LD) motifs. Bioinformatics. doi:10.1093/bioinformatics/btz703Sponsors
We acknowledge SOLEIL for provision of synchrotron radiation facilities for testing of FAT:LD motif peptide crystals. We thank M. Savko, W. Shepard, S. Sirigu, L. Chavas and P. Legrand for assistance in using beamlines PX1 and PX2A. We thank R. Höhndorf for advice with the GO analysis, J. Hanks, C. Kapfer and A. Hungler for help with computing at KAUST. We acknowledge support from the KAUST Imaging and Characterization Core Lab, the Bioscience Core Lab and Research Computing Core lab.This research used the resources of the Supercomputing Laboratory at KAUST, and was supported by KAUST through the baseline fund and the Award No. URF/1/1976-04, URF/1/1976-06, URF/1/3007-01, URF/1/1976-02, BAS/1/1606-01-01 and #OSR-2015- CRG4-2602 from the Office of Sponsored Research (OSR).
Publisher
Oxford University Press (OUP)Journal
BioinformaticsAdditional Links
https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btz703/5581347Relations
Is Supplemented By:- [Software]
Title: tanviralambd/LD: Source code for LD motif detection. Publication Date: 2019-06-28. github: tanviralambd/LD Handle: 10754/666977
ae974a485f413a2113503eed53cd6c53
10.1093/bioinformatics/btz703
Scopus Count
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Articles; Biological and Environmental Science and Engineering (BESE) Division; Bioscience Program; Applied Mathematics and Computational Science Program; Structural and Functional Bioinformatics Group; Computer Science Program; Computational Bioscience Research Center (CBRC); Statistics Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
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