BAIT
SIC1
SDB25, cyclin-dependent protein serine/threonine kinase inhibiting protein SIC1, L000001886, L000001822, YLR079W
Cyclin-dependent kinase inhibitor (CKI); inhibitor of Cdc28-Clb kinase complexes that controls G1/S phase transition, preventing premature S phase and ensuring genomic integrity; phosphorylated by Clb5/6-Cdk1 and Cln1/2-Cdk1 kinase which regulate timing of Sic1p degradation; phosphorylation targets Sic1p for SCF(CDC4)-dependent turnover; functional homolog of mammalian Kip1
GO Process (3)
GO Function (1)
GO Component (2)
Gene Ontology Biological Process
Gene Ontology Molecular Function
Saccharomyces cerevisiae (S288c)
PREY
UBA4
YHR1, YHR111W
E1-like protein that activates Urm1p before urmylation; also acts in thiolation of the wobble base of cytoplasmic tRNAs by adenylating and then thiolating Urm1p; receives sulfur from Tum1p
GO Process (7)
GO Function (4)
GO Component (1)
Gene Ontology Biological Process
Gene Ontology Molecular Function
Saccharomyces cerevisiae (S288c)
Negative Genetic
Mutations/deletions in separate genes, each of which alone causes a minimal phenotype, but when combined in the same cell results in a more severe fitness defect or lethality under a given condition. This term is reserved for high or low throughput studies with scores.
Publication
A Network of Conserved Synthetic Lethal Interactions for Exploration of Precision Cancer Therapy.
An emerging therapeutic strategy for cancer is to induce selective lethality in a tumor by exploiting interactions between its driving mutations and specific drug targets. Here we use a multi-species approach to develop a resource of synthetic lethal interactions relevant to cancer therapy. First, we screen in yeast ∼169,000 potential interactions among orthologs of human tumor suppressor genes (TSG) and ... [more]
Mol. Cell Aug. 04, 2016; 63(3);514-25 [Pubmed: 27453043]
Quantitative Score
- -13.07 [Confidence Score]
Throughput
- High Throughput
Ontology Terms
- phenotype: colony size (APO:0000063)
Additional Notes
- Untreated conditions. SGA was used to score genetic interactions based on the colony size of double versus single mutants. Genetic interactions were considered significant if they had an S score >= 2.0 for positive interactions (epistatic or suppressor interactions) and S score <= -2.5 for negative interactions (synthetic sick/lethal interactions).
Curated By
- BioGRID