LNX functions as a RING type E3 ubiquitin ligase that targets the cell fate determinant Numb for ubiquitin-dependent degradation

LNX is a RING finger and PDZ domain containing protein that interacts with the cell fate determinant Numb. To investigate the function of LNX, we tested its RING finger domain for ubiquitin ligase activity. The isolated RING finger domain was able to function as an E2-dependent, E3 ubiquitin ligase in vitro and mutation of a conserved cysteine residue within the RING domain abolished its activity, indicating that LNX is the first described PDZ domain-containing member of the E3 ubiquitin ligase family. We have identified Numb as a substrate of LNX E3 activity in vitro and in vivo. In addition to the RING finger, a region of LNX, including the Numb PTB domain-binding site and the first PDZ domain, is required for Numb ubiquitylation. Expression of wild-type but not mutant LNX causes proteasome-dependent degradation of Numb and can enhance Notch signalling. These results suggest that the levels of mammalian Numb protein and therefore, by extension, the processes of asymmetric cell division and cell fate determination may be regulated by ubiquitin-dependent proteolysis

Biochemical and Computational Analysis Of LNX1 Interacting Proteins

PDZ (Post-synaptic density, 95 kDa, Discs large, Zona Occludens-1) domains are protein interaction domains that bind to the carboxy-terminal amino acids of binding partners, heterodimerize with other PDZ domains, and also bind phosphoinositides. PDZ domain containing proteins are frequently involved in the assembly of multi-protein complexes and clustering of transmembrane proteins. LNX1 (Ligand of Numb, protein X 1) is a RING (Really Interesting New Gene) domain-containing E3 ubiquitin ligase that also includes four PDZ domains suggesting it functions as a scaffold for a multiprotein complex. Here we use a human protein array to identify direct LNX1 PDZ domain binding partners. Screening of 8,000 human proteins with isolated PDZ domains identified 53 potential LNX1 binding partners. We combined this set with LNX1 interacting proteins identified by other methods to assemble a list of 220 LNX1 interacting proteins. Bioinformatic analysis of this protein list was used to select interactions of interest for future studies. Using this approach we identify and confirm six novel LNX1 binding partners: KCNA4, PAK6, PLEKHG5, PKC-alpha1, TYK2 and PBK, and suggest that LNX

PreBIND and Textomy – mining the biomedical literature for protein-protein interactions using a support vector machine

<p>Abstract</p> <p>Background</p> <p>The majority of experimentally verified molecular interaction and biological pathway data are present in the unstructured text of biomedical journal articles where they are inaccessible to computational methods. The Biomolecular interaction network database (BIND) seeks to capture these data in a machine-readable format. We hypothesized that the formidable task-size of backfilling the database could be reduced by using Support Vector Machine technology to first locate interaction information in the literature. We present an information extraction system that was designed to locate protein-protein interaction data in the literature and present these data to curators and the public for review and entry into BIND.</p> <p>Results</p> <p>Cross-validation estimated the support vector machine's test-set precision, accuracy and recall for classifying abstracts describing interaction information was 92%, 90% and 92% respectively. We estimated that the system would be able to recall up to 60% of all non-high throughput interactions present in another yeast-protein interaction database. Finally, this system was applied to a real-world curation problem and its use was found to reduce the task duration by 70% thus saving 176 days.</p> <p>Conclusions</p> <p>Machine learning methods are useful as tools to direct interaction and pathway database back-filling; however, this potential can only be realized if these techniques are coupled with human review and entry into a factual database such as BIND. The PreBIND system described here is available to the public at <url>http://bind.ca</url>. Current capabilities allow searching for human, mouse and yeast protein-interaction information.</p