Project description:According to our study, Chrysanthemum lavandulifolum extract showed excellent antibiotic effects on Escherichia coli O157:H7. A notable point is that the antibiotic efficacy of the herb extract is on the all three proven targets for main antibiotic drugs that are bacterial cell wall biosynthesis, bacterial protein synthesis and bacterial DNA replication and repair. This multi-target efficacy of the herbal antibiotics may be used as more effective and safe drugs that substitute existing antibiotics.
Project description:To advance our understanding of the regional molecular effects of non-antibiotic drugs on the gut ecosystem, we performed multi-omics analysis of different mice intestinal regions after oral administration of 33 commonly used drugs (n=8, one drug for each animal, (n=10 for the control group)),
Project description:Based on a simple E.coli growth inhibition assay, the authors trained a model capable of identifying antibiotic potential in compounds structurally divergent from conventional antibiotic drugs. One of the predicted active molecules, Halicin (SU3327), was experimentally validated in vitro and in vivo.
Model Type: Predictive machine learning model.
Model Relevance: Probability that a compound inhibits E.coli growth.
Model Encoded by: Miquel Duran-Frigola(Ersilia)
Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam
Implementation of this model code by Ersilia is available here:
https://github.com/ersilia-os/eos4e40