Binding of solvated peptide (EPLQLKM) with a graphene sheet via simulated coarse-grained approach
Bibliographic record
Abstract
Binding of a solvated peptide A1 ((1)E (2)P (3)L (4)Q (5)L (6)K (7)M) with a graphene sheet is studied by a coarse-grained computer simulation involving input from three independent simulated interaction potentials in hierarchy. A number of local and global physical quantities such as energy, mobility, and binding profiles and radius of gyration of peptides are examined as a function of temperature (T). Quantitative differences (e.g., the extent of binding within a temperature range) and qualitative similarities are observed in results from three simulated potentials. Differences in variations of both local and global physical quantities suggest a need for such analysis with multiple inputs in assessing the reliability of both quantitative and qualitative observations. While all three potentials indicate binding at low T and unbinding at high T, the extent of binding of peptide with the temperature differs. Unlike un-solvated peptides (with little variation in binding among residues), solvation accentuates the differences in residue binding. As a result the binding of solvated peptide at low temperatures is found to be anchored by three residues, (1)E, (4)Q, and (6)K (different from that with the un-solvated peptide). Binding to unbinding transition can be described by the variation of the transverse (with respect to graphene sheet) component of the radius of gyration of the peptide (a potential order parameter) as a function of temperature.
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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 | 0.001 | 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 | 0.000 |
| 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 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".