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Turon2023 - H3D virtual screening models


ABSTRACT: The H3D virtual screening cascade contains models for Mycobacterium tuberculosis and Plasmodium falciparum IC50 predictions, as well as ADME, cytotoxicity, and solubility assays. Model Type: Predictive machine learning model. Model Relevance: This panel of models provides predictions for the H3D virtual screening cascade. 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/eos7kpb

SUBMITTER: Zainab Ashimiyu-Abdusalam  

PROVIDER: MODEL2403270001 | BioModels | 2024-05-13

REPOSITORIES: BioModels

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Publications

First fully-automated AI/ML virtual screening cascade implemented at a drug discovery centre in Africa.

Turon Gemma G   Hlozek Jason J   Woodland John G JG   Kumar Ankur A   Chibale Kelly K   Duran-Frigola Miquel M  

Nature communications 20230915 1


Streamlined data-driven drug discovery remains challenging, especially in resource-limited settings. We present ZairaChem, an artificial intelligence (AI)- and machine learning (ML)-based tool for quantitative structure-activity/property relationship (QSAR/QSPR) modelling. ZairaChem is fully automated, requires low computational resources and works across a broad spectrum of datasets. We describe an end-to-end implementation at the H3D Centre, the leading integrated drug discovery unit in Africa  ...[more]

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