Covalent Inhibitors of S100A4 Block the Formation of a Pro-Metastasis Non-Muscle Myosin 2A Complex
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The S100 protein family functions as protein–protein interaction adaptors regulated by Ca 2+ binding. Formation of various S100 complexes plays a central role in cell functions, from calcium homeostasis to cell signaling, and is implicated in cell growth, migration, and tumorigenesis. We established a suite of biochemical and cellular assays for small molecule screening based on known S100 protein–protein interactions. From 25 human S100 proteins, we focused our attention on S100A4 because of its well-established role in cancer progression and metastasizes by interacting with nonmuscle myosin II (NMII). We identified several potent and selective inhibitors of this interaction and established the covalent nature of binding, confirmed by mass spectrometry and crystal structures. 5b showed on-target activity in cells and inhibition of cancer cell migration. The identified S100A4 inhibitors can serve as a basis for the discovery of new cancer drugs operating via a novel mode of action.
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".