Characterization of PABP-interacting proteins 1 and 2
Bibliographic record
Abstract
The 3' poly(A) tail of eukaryotic mRNAs and the poly(A) binding protein (PABP) play key roles in the regulation of translation. Recently, our group identified two human PABP-interacting proteins (Paip), Paip1 and Paip2, which stimulate and repress translation, respectively. Paip2 also inhibits the binding of PABP to the poly(A) tail and competes with Paip1 for binding to PABP. My research project was divided into two parts to allow me to gain a greater understanding of the roles of these two PABP-interacting proteins. First, in order to study the mechanism of interaction of Paip1 and PABP, their binding sites were mapped by Far Western and GST pull-downs experiments. The Paip1-PABP interaction involves two distinct binding regions in each protein. The PABP interacting motif-1 (PAM1) of Paip1 is rich in acidic amino acids and is located in the C-terminus (a.a. 440--479). PAM1 interacts with the RNA recognition motifs (RRMs) 1 and 2 of PABP. PAM2 consists of a 15 amino acid stretch residing in the N-terminus of Paip1 (a.a. 123--137) and interacts with the C-terminal domain of PABP. In addition, the stoichiometry and the kinetic and thermodynamic constants for the Paip1-PABP interaction were determined using a Surface Plasmon Resonance (SPR)-biosensor. Paip1 interacts with PABP with an apparent KD of 1.9 nM and with a 1:1 stoichiometry. In the second part of my thesis research, the Drosophila Paip2 (dPaip2) was isolated and characterized in order to ascertain a biological role for Paip2. dPaip2 was found to be the bona fide homologue of human Paip2 since it interacts with the Drosophila PABP (dPABP) via two independent binding sites, interferes with the ability of dPABP to bind to poly(A), and represses translation. Ectopic overexpression of dPaip2 in wings resulted in a size reduction phenotype, which was due to a decrease in the cell number but not to a difference in cell size. Clones of cells overexpressing dPaip2 in wing discs also contai
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".