Conformational Study of Cannabinoid Docking to Cannabinoid Receptor 1 (CB1) via Linear and Nonlinear Circular Dichroism
Bibliographic record
Abstract
The exact mechanism of binding of (-)-trans-Δ9-tetrahydrocannabinol (the main psychoactive component of marijuana) to the cannabinoid receptor, CB1, is unknown. Conformational information of the cannabinoids may give insight to this mechanism and the elicited effects of consumption. Herein, we report on the theoretical conformational study of Δ9-tetrahydrocannabinol (Δ9-THC) and cannabidiol (CBD), the psychoactive and a non-psychoactive compound found in marijuana, respectively, using electronic circular dichroism (ECD) and two-photon circular dichroism (TPCD). The compounds were optimized in vacuo and in the receptor site using DFT and B3LYP with the 6-311G** basis set and spectra were calculated using the same level of theory, but with the 6-311++G** basis set. First, we present and discuss the comparison of experimental and theoretical ECD spectra of (-)-trans-Δ9-THC and CBD in methanol solution in order to corroborate our theoretical approach. Second, we show, theoretically, the enhanced sensitivity of TPCD compared with ECD to conformational changes of cannabinoids upon docking, giving rise to a potential application in vivo. Finally, the comparative analysis of the theoretical TPCD spectra of Δ9-THC and CBD show distinct fingerprints in the far-UV region for two conformers of each molecule, which may help to understand the specific binding mechanisms of these species to the cannabinoid receptors and to describe the difference in psychological effects upon consumption. Our results show the complementarity of these two spectroscopic techniques and the potential of TPCD to determine the conformational changes of cannabinoids upon docking to the CB1 receptor.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".