ersilia-os / eos3nn9

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Predict bioactivity against Main Protease of SARS-CoV-2

MProPred predicts the efficacy of compounds against the main protease of SARS-CoV-2, which is a promising drug target since it processes polyproteins of SARS-CoV-2. This model uses PaDEL-Descriptor to calculate molecular descriptors of compounds. It is based on a dataset of 758 compounds that have inhibition efficacy against the Main Protease, as published in peer-reviewed journals between January, 2020 and August, 2021. Input compounds are compared to compounds in the dataset to measure molecular similarity with MACCS.

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If you use this model, please cite the original authors of the model and the Ersilia Model Hub.

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This package is licensed under a GPL-3.0 license. The model contained within this package is licensed under a MIT license.

Notice: Ersilia grants access to these models 'as is' provided by the original authors, please refer to the original code repository and/or publication if you use the model in your research.

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The Ersilia Open Source Initiative is a Non Profit Organization (1192266) with the mission is to equip labs, universities and clinics in LMIC with AI/ML tools for infectious disease research.

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