Homology and Molecular Dynamics Models of Toll‐Like Receptor 7 Protein and Its Dimerization
Why this work is in the frame
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Bibliographic record
Abstract
Toll-like receptor protein 7 is a transmembrane protein playing a crucial role in the signaling pathways involved in innate immunity. Its crystal structure is not yet available, but there are several proteins possessing domains of sufficiently high homology, which enabled us to build a model of the toll-like receptor protein 7 monomer and gain insights into dimer formation. To obtain a reliable structure prediction, we subjected this model to equilibration using molecular dynamics simulations. Furthermore, the equilibrated monomer structure was used to construct models of dimerization and to predict binding sites for small ligands. Docking studies were performed for some of the known toll-like receptor protein 7 ligands. We determined that a new homology model generated by the LOOPP server provides a good alternative to a previously reported model. Our docking results indicate that the addition of either imiquimod or 1V209 to a toll-like receptor protein 7 dimer changes an unfavorable interaction into a favorable one. We found that eight small molecules docked to two pockets in toll-like receptor protein 7 bind to both pockets at pH 7 and at pH 5.5. This work provides a realistic model that could be used for drug discovery aimed at finding toll-like receptor protein 7 dimerization activators, with potential clinical applications to a host of diseases, including cancer.
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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 | 0.000 |
| 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) | 0.000 | 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 it