ESI-MS and FTIR studies of the interaction between the second PDZ domain of hPTP1E and target peptides
Bibliographic record
Abstract
The specificity of interaction between the second PDZ domain of human protein tyrosine phosphatase1E (PDZ2) and a C-terminal peptide, ENEQVSAV, from the guanine nucleotide exchange factor RA-GEF-2 was investigated using Fourier transform infrared (FTIR) spectroscopy and electrospray ionization mass spectrometry (ESI-MS). Specificity of the binding interaction and the importance of Ser in the -2 position of the target peptide were demonstrated using alternate peptides ENEQVCAV and KDDEVYYV. FTIR-monitored thermal denaturation in the amide I region showed a 10 degrees C increase in melting temperature (Tm) for the PDZ2-ENEQVSAV complex compared with that of free PDZ2, and the spectra revealed increased absorption in the beta-sheet region (1628 cm(-1)) of PDZ2 on peptide binding. Neither of these results were observed with peptides containing either Cys or Tyr in the -2 position. Complex formation with the Ser-containing peptide was further demonstrated by direct measurement of a 1:1 PDZ-peptide complex by ESI-MS in 100% aqueous solutions without the need for organic co-solvents. Our results demonstrate that even a single atom (O --> S) substitution from Ser to Cys in the -2 position disrupts C-terminal peptide binding to PDZ2.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".