Homodimer Interface Mutations of Human Galectin-7 alter Its Biological Activity
Bibliographic record
Abstract
Human galectins are beta-galactoside binding proteins subdivided into three groups in accordance \nwith their structural organization: tandem repeat, chimera, and prototype. Among these galectins, \nprototype galectin-7 (GAL-7), characterized by a homodimeric molecular organization of its carbohydrate recognition domain (CRD), is involved in different types of cancer, including carcinomas, lymphomas and melanomas. Its overexpression in tumor cells not only confers resistance to cell death \nstimuli, but extracellular GAL-7 also induces apoptosis of lymphocytes, abrogating immune system \nresponse against tumor antigens. Consequently, GAL-7 is a promising target for cancer therapy. To this \nday, the development of GAL-7 modulators has almost exclusively focused on small-molecule Glycan Binding Site (GBS) inhibitors aimed at perturbation of glycoreceptor interactions. However, due to high GBS \nsimilarity among different galectin homologs, this remains a high risk strategy because of unwanted offtarget effects on other beneficial anti-tumor galectins. Furthermore, GBS inhibitors are ineffective at targeting glycan-independent function of GAL-7. New approaches are thus required to develop effective and \nhighly specific GAL-7 inhibitors. Prior structural investigations of ancestral galectins have suggested that \nstabilization of their oligomeric state through evolutionary pressure improves ligand affinity and biological \nfunction. Since destabilization of GAL-7 architecture could potentially alter its affinity towards glycoproteins \nand biological function, our main research objective is to dissect the molecular importance of GAL-7 homodimer formation in celullar function. In this study, we will present the impact of homodimer interface mutations on protein stability and induction of Jurkat T-cell apoptosis.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".