five

Stokes2020 - Antibiotics discovery using deep learning approach (Antiviral implementation)

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NIAID Data Ecosystem2026-05-02 收录
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https://www.omicsdi.org/dataset/biomodels/MODEL2405080006
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This model was developed to support the early efforts in the identification of novel drugs against SARS-CoV2. It predicts the probability that a small molecule inhibits SARS-3CLpro-mediated peptide cleavage. It was developed using a high-throughput screening against the 3CL protease of SARS-CoV1, as no data was yet available for the new virus (SARS-CoV2) causing the COVID-19 pandemic. It uses the ChemProp model. Model Type: Predictive machine learning model. Model Relevance: Probability of 3CL protease inhibition. 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/eos9f6t
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2024-05-08
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