Experimental and computational interaction studies of terbium (III) and lanthanide (III) complexes containing 2,2′-bipyridine with bovine serum albumin and their <i>in vitro</i> anticancer and antimicrobial activities
Bibliographic record
Abstract
To investigate the chemotherapeutic and pharmacokinetic aspects of two lanthanide complexes (Tb(III) and La(III) containing 2,2′-bipyridine ligand), in vitro binding studies were carried out with BSA by employing multiple biophysical methods and molecular modeling study. There are different techniques containing fluorescence, absorption spectroscopy and competitive experiments to determine the interaction mode between BSA and these complexes. These complexes efficiently quenched the BSA emission through a static procedure. The results showed that the terbium and lanthanum complexes exhibited a high propensity for BSA interaction via van der Waals force. Further, competitive examination and docking study showed that the interaction site of these complexes on BSA is site III. The results of docking calculations were in good agreement with experimental examinations. Also, the energy transfer from BSA to these complexes has happened with high possibility. Moreover, antimicrobial studies of different bacterial and fungi indicated its promising antibacterial activity. In vitro cytotoxicity of the Tb complex and La complex was carried out in MCF-7 and A-549 cell lines, which revealed significantly good activity.Communicated by Ramaswamy H. Sarma
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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 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".