Additional file 1 of Leveraging structural and 2D-QSAR to investigate the role of functional group substitutions, conserved surface residues and desolvation in triggering the small molecule-induced dimerization of hPD-L1
Bibliographic record
Abstract
Additional file 1: Figure S1. The 3D structure of a small molecule free PD-L1 dimer (a) and the comparison of backbone RMSD fluctuations in small molecule-bound and unbound systems during 75 ns long MD simulation (b). (a) In the 3D structure of the PD-L1 dimer shown as a cartoon representation, the chain A is shown in blue and chain B in Red. The region corresponding to the residues 33-42 and 93-105 in both the chains, where a physical restraint of 0.5 kcal/mol were applied, are shown in black color. (b) Analyses based on the evolution of backbone RMSDs of the bound (orange line) and unbound (blue line) systems indicated that the systems stabilized during the course of MD simulations. Figure S2. The 3D structures of small molecule-free PD-L1 dimers (in cartoon representation) showing the residues (stick representation) forming key H-bond interactions. The small molecule binding site (based on the small molecule bound PD-L1 dimer complex) is shown as a surface in white.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.816 | 0.121 |
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".