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Record W4413812373 · doi:10.1038/s41598-025-17314-5

GC-MS profiling, in vitro and in silico antibacterial and antioxidant potential of crude secondary metabolites of an endophytic bacterium isolated from Enhydra fluctuans lour

2025· article· en· W4413812373 on OpenAlexaff
Mourad A. M. Aboul‐Soud, Md. Nazim Uddin, Kishor Mazumder, A. U. Akash, Reem M. Aljowaie, John P. Giesy, Mohit Agrawal, Shariful Haque

Bibliographic record

VenueScientific Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsUniversity of Saskatchewan
FundersKing Saud University
KeywordsIn silicoIn vitroTraditional medicineBiologyBacteriaAntioxidantMicrobiologyProfiling (computer programming)ChemistryBiochemistryMedicineComputer scienceGenetics

Abstract

fetched live from OpenAlex

This study investigates the bioactive potential of secondary metabolites produced by endophytic bacteria isolated from Enhydra fluctuans Lour., a medicinal plant known for its antioxidant and antimicrobial properties. Fresh leaves were collected, surface-sterilized, and used to isolate bacterial endophytes. The isolates were identified morphologically and confirmed by 16S rRNA gene sequencing. Metabolites were extracted using ethyl acetate and assessed for antibacterial activity via the disc diffusion method and antioxidant capacity by DPPH radical scavenging assay. GC-MS was used to identify volatile bioactive substances. The isolate showed 91.75% similarity with Pseudomonas campi (NR_181172.1), indicating a distant relationship and suggesting it may represent a novel or uncharacterized taxon. The isolate was mostly sensitive to Ciprofloxacin (5 µg). Its ethyl acetate crude extract showed moderate antibacterial activity against Staphylococcus aureus with a 13.4 ± 0.21 mm inhibition zone at 500 µg/disc, compared to kanamycin (30 µg/disc). Antioxidant activity showed an IC 50 of 61.66 ± 0.33 µg/mL, versus 17.38 ± 0.63 µg/mL for ascorbic acid. GC-MS identified 19 bioactive compounds, with Phenol, 3,5-bis(1,1-dimethylethyl)-, 1,9-Diazaspiro (4,4 )nonane-2,8-dione, and Octacosanol as major constituents. In silico analyses showed that 9,10-anthracenedione, 2-[(tert-butylamino)methylcarbamoyl] exhibited strong antibacterial and antioxidant potential, with high binding affinities to MurD ligase (-9.8 kcal/mol) and myeloperoxidase (-9.6 kcal/mol), respectively. Molecular dynamics (MD) simulations over 100 ns confirmed the stability of these complexes, supported by analyses of RMSD, RMSF, hydrogen bonds, and MMGBSA free energy. Most molecules were predicted to be non-toxic. These findings suggest that 9,10-Anthracenedione exhibits promising binding characteristics, driven by non-covalent interactions, making it a potential candidate for further drug development studies. Our results provide preliminary evidence that endophytic bacteria harbor chemically diverse secondary metabolites, reinforcing their role in natural product-based drug discovery pipelines. While initial findings are promising, Pure compound isolation comprehensive in vivo studies, compound purification, and pharmacokinetic profiling are essential.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.001

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.225
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2025
Admission routes1
Has abstractyes

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