Summary
This laboratory study identified blaOXA-carrying Bacillus cereus from soil and used artificial intelligence-driven molecular docking to screen natural phytochemicals as potential inhibitors of the blaOXA β-lactamase enzyme. Piperine and AI-optimised derivatives showed favourable in silico binding affinities and pharmacokinetic properties compared to standard antibiotics; however, the authors acknowledge that findings remain computationally validated and require in vitro and in vivo experimental confirmation.
Regional applicability
The study does not specify geographic origin of samples and is based entirely on computational modelling. Applicability to United Kingdom foodborne illness surveillance or clinical practice would depend on future experimental validation and assessment of whether the identified strain and resistance mechanisms are relevant to UK Bacillus cereus epidemiology.
Key measures
Antibiotic susceptibility (disc diffusion); blaOXA gene amplification and sequencing; molecular docking scores (kcal/mol); AlphaFold3 protein modelling validation (Ramachandran plot, ERRAT score); ADMET properties; toxicity predictions; molecular dynamics simulations; density functional theory energy gap; pharmacophore analysis
Outcomes reported
The study identified blaOXA-positive B. cereus from soil samples and screened 30 phytochemicals via molecular docking against the blaOXA enzyme. AI-optimised piperine derivatives were evaluated for binding affinity, pharmacokinetics, and toxicity through computational methods including molecular dynamics simulations and density functional theory analysis.
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