Molecular docking and in silico analysis of the pharmacokinetics, toxicological profile and differential gene expression of bioactive compounds from Cyrtopodium glutiniferum
Bibliographic record
Abstract
The genus Cyrtopodium , from the Orchidaceae family, is widely used for its therapeutic properties in the treatment of tuberculosis, abscesses, urinary infection, and colds. C. glutiniferum , one of the species of this genus, is endemic in Brazil and largely used in herbal medicine. Thus, it is of great interest to recognize its composition, the properties of the molecules found in it. This study aimed to perform the in silico analysis of the main compounds from C. glutiniferum , on the platforms pKCSM, SwissADME, LAZAR, CLC-pred, ToxTree, DIGEPred, STRING, and Cytoscape. Further than this, the molecular docking was performed. The compounds present in the aqueous extract of C. glutiniferum were identified by UHPLC-MS/MS, finding Arbutin, Caffeic acid 4-O-glucoside, and Dihydroformononetin as the three most abundant molecules. The evaluation of the gastrointestinal absorption of Dihydroformononetin is given as high, also managing to cross the blood-brain barrier, while Arbutin can only be absorbed by the gastrointestinal tract and Caffeic acid 4-O-glucoside had very low absorption. Further analysis showed that Arbutin and Dihydroformononetin are possible leading molecules for drug synthesis, according to the prediction. Toxicological aspects were analysed, and no adverse effects were noted, but there were divergences in the mutagenic prediction of Arbutin and Dihydroformononetin, having different results in the used platforms, demonstrating that a cautious analysis and data insertion is needed in these tools to optimize them. The analysis of the differentially expressed genes predicted that the compounds can regulate several genes, including some genes associated with carcinogenesis and inflammation. The Molecular docking analysis showed high binding affinities of the molecules with different proteins. Therefore, C. glutiniferum demonstrates the potential to be used as a phytotherapeutic. The same was given through the in silico analysis of the three compounds found in the orchid, that show good individual potential. • The analysis shows potential of compounds as anti-inflammatory and anticancer agents. • Molecular docking shows strong binding affinities with target proteins. • Arbutin and Caffeic Acid 4-O-glucoside may exhibit synergistic therapeutic effects. • Dihydroformononetin downregulates proinflammatory genes. • Dihydroformononetin upregulates AURKB and AURKA.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.001 |
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".