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Liu2023 - Acinetobacter baumannii growth inhibition prediction with Deep Learning


ABSTRACT: This model is a Chemprop neural network trained with a growth inhibition dataset. Authors screened ~7,500 molecules for those that inhibited the growth of A. baumannii in vitro. They discovered abaucin, an antibacterial compound with narrow-spectrum activity against A. baumannii. Model Type: Predictive machine learning model. Model Relevance: The model predicts the probability of growth inhibition of the bacteria A. Baumannii. 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/eos3804

SUBMITTER: Zainab Ashimiyu-Abdusalam  

PROVIDER: MODEL2405080001 | BioModels | 2024-05-28

REPOSITORIES: BioModels

Dataset's files

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MODEL2405080001?filename=eos3804%20-%20BioModels%20Metadata%20file.csv Csv
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Publications


Acinetobacter baumannii is a nosocomial Gram-negative pathogen that often displays multidrug resistance. Discovering new antibiotics against A. baumannii has proven challenging through conventional screening approaches. Fortunately, machine learning methods allow for the rapid exploration of chemical space, increasing the probability of discovering new antibacterial molecules. Here we screened ~7,500 molecules for those that inhibited the growth of A. baumannii in vitro. We trained a neural netw  ...[more]

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