LDmotif

LDmotif identifies and characterizes Leucine-Aspartic Acid (LD) short linear interaction motifs (SLiMs) across proteomes to enable functional and evolutionary analysis of LD-mediated interactions, including those linking paxillin family proteins to regulators of cell adhesion, motility, and survival.

Key Features:

• Active Learning Framework: The LD motif finder (LDMF) employs an active learning-based framework that iteratively combines computational predictions with experimental validation to improve motif detection accuracy.
• Proteome-Wide Analysis: Applied to the human proteome, LDmotif identified a dozen new proteins containing LD motifs and characterized their prevalence.
• Evolutionary Insights: Analyses indicate LD motif signaling evolved over 800 million years ago in unicellular eukaryotes and identify paxillin, vinculin, and nuclear export signals as core constituents and potential sources for de novo LD motifs.
• Functional Homogeneity: Proteins containing LD motifs form a functionally homogenous group involved in cell morphogenesis and adhesion, with functional specificity intrinsic to the LD motif sequence influencing binding partners.

Scientific Applications:

• Cell adhesion and motility studies: Identification and characterization of LD motifs supports investigation of mechanisms underlying cell adhesion, motility, and survival.
• Evolutionary analysis of SLiMs: Enables investigation of the origins, evolutionary history, and adaptations of ancestral SLiMs.
• Discovery of novel LD motif-containing proteins: Supports proteome-scale discovery of previously unrecognized LD motifs in proteins.
• Functional annotation of LD-mediated interactions: Assists in linking LD motifs to binding partners and functional roles in morphogenesis and adhesion.

Methodology:

LDmotif uses an active learning-based framework (LD motif finder, LDMF) that integrates computational predictions with experimental validation and employs amino acid index calculations via external jars and files.