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.
KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): URF/1/1976-04, URF/1/3007-01, URF/1/1976-02, BAS/1/1606-01-01, OSR-2015- CRG4-2602
Acknowledgements: 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.