Finding a Leucine in a Haystack: Searching the Proteome for ambigous Leucine-Aspartic Acid motifs

Abstract
Leucine-aspartic acid (LD) motifs are short helical protein-protein interaction motifs involved in cell motility, survival and communication. LD motif interactions are also implicated in cancer metastasis and are targeted by several viruses. LD motifs are notoriously difficult to detect because sequence pattern searches lead to an excessively high number of false positives. Hence, despite 20 years of research, only six LD motif–containing proteins are known in humans, three of which are close homologues of the paxillin family. To enable the proteome-wide discovery of LD motifs, we developed LD Motif Finder (LDMF), a web tool based on machine learning that combines sequence information with structural predictions to detect LD motifs with high accuracy. LDMF predicted 13 new LD motifs in humans. Using biophysical assays, we experimentally confirmed in vitro interactions for four novel LD motif proteins. Thus, LDMF allows proteome-wide discovery of LD motifs, despite a highly ambiguous sequence pattern. Functional implications will be discussed.

Conference/Event Name
KAUST Research Conference on Computational and Experimental Interfaces of Big Data and Biotechnology

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