Integrating In Vitro and In Silico Approaches to Assess Monotheca buxifolia Plant Extract against Rhipicephalus (Boophilus) microplus and Sarcoptes scabiei
Bibliographic record
Abstract
Tick and mite infestations pose significant challenges to animal health, agriculture, and public health worldwide. The search for effective and environmentally friendly acaricidal agents has led researchers to explore natural alternatives. In this study, we investigated the acaricidal potential of the Monotheca buxifolia plant extract against Rhipicephalus microplus ticks and Sarcoptes scabiei mites. Additionally, we employed a computational approach to identify phytochemicals from the extract that could serve as drug candidates against these ectoparasites. The contact bioassay results demonstrated that the M. buxifolia plant extract exhibited significant efficacy against R. microplus and S. scabiei, with higher concentrations outperforming the positive control acaricide permethrin in terms of mite mortality. Time exposure to the extract also showed a positive correlation with better lethal concentration (LC50 and LC90) values. Similarly, the adult immersion test revealed a notable inhibition of tick oviposition via the plant extract, especially at higher concentrations. The two-protein primary structure, secondary structure and stability were predicted using the Expasy’s ProtParam server, SOPMA and SUSUI server, respectively. Using Homology modeling, the 3D structure of the protein was obtained and validated through the ERRAT server, and active sites were determined through the CASTp server. The docking analysis revealed that Alpha-Amyrenyl acetate and alpha-Tocopherol exhibited the highest docking scores for S. scabiei and R. microplus aspartic protease proteins, respectively. These phytochemicals demonstrated strong binding interactions, suggesting their potential as acaricidal drug candidates. In conclusion, the M. buxifolia plant extract displayed significant acaricidal activity against R. microplus and S. scabiei. Moreover, the computational approach identified promising phytochemicals that could serve as potential drug candidates for controlling these ectoparasites.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 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".