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Abstract
MotivationLeucine-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.ResultsTo enable a proteome-wide assessment of LD motifs, we developed an active learning based framework (LD motif 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 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 and implementation 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.
Highlights
Cellular signal transduction networks rely on the recognition of short linear motifs (SLiMs) by their cognate ligand binding domains (Gould, et al, 2010)
We produced a bioinformatic tool, named LDMF, that allowed the proteomewide detection of Leucine-aspartic acid (LD) motifs with high accuracy
An additional difficulty was the scarcity of the positive data set, which precluded using deep learning methods
Summary
Cellular signal transduction networks rely on the recognition of short linear motifs (SLiMs) by their cognate ligand binding domains (Gould, et al, 2010). These motifs are contained on a single contiguous amino acid stretch of typically less than 15 residues, and do not require to be embedded in a three-dimensional protein framework to be functional. The resulting sequence motif degeneration and binding promiscuity hamper our capacity to computationally identify SLiMs and their biologically relevant binding partners (Edwards and Palopoli, 2015). This difficulty severely limits our capacity to evaluate the spread, adaptation and possibly origin of SLiMs
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