Computational Study of the Binding Modes of Caffeine to the Adenosine A<sub>2A</sub>Receptor
Bibliographic record
Abstract
Using the recently solved crystal structure of the human adenosine A(2A) receptor, we applied MM/PBSA to compare the binding modes of caffeine with those of the high-affinity selective antagonist ZM241385. MD simulations were performed in the environment of the lipid membrane bilayer. Four low-energy binding modes of caffeine-A(2A) were found, all of which had similar energies. Assuming an equal contribution of each binding mode of caffeine, the computed binding free energy difference between caffeine and ZM241385 is -2.4 kcal/mol, which compares favorably with the experimental value, -3.6 kcal/mol. The configurational entropy contribution of -0.9 kcal/mol from multiple binding modes of caffeine helps explain how a small molecule like caffeine can compete with a significantly larger molecule, ZM241385, which can form many more interactions with the receptor. We also performed residue-wise energy decomposition and found that Phe168, Leu249, and Ile274 contribute most significantly to the binding modes of caffeine and ZM241385.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".