biostudies-otherUnknown626Zainab Ashimiyu-AbdusalamNature177-185Staphylococcus aureushttps://www.ebi.ac.uk/biostudies/studies/MODEL2405080002biostudies-other38123686Zainab Ashimiyu-AbdusalamfalseWong2024 - Discovery of a structural class of antibiotics with explainable deep learning<p>The authors use a large dataset (>30k) to train an explainable graph-based model to identify potential antibiotics with low cytotoxicity. The model uses a substructure-based approach to explore the chemical space. Using this method, they were able to screen 283 compounds and identify a candidate active against methicillin-resistant S. aureus (MRSA) and vancomycin-resistant enterococci.</p><p><normal>Model Type:</normal> Predictive machine learning model.<br><normal>Model Relevance:</normal> The model predicts the probability of growth inhibition.<br><normal>Model Encoded by:</normal> Sarima Chiorlu (Ersilia)<br><normal>Metadata Submitted in BioModels by:</normal> Zainab Ashimiyu-Abdusalam</p><p>Implementation of this model code by <a href="https://ersilia.io/">Ersilia</a> is available here: <br><a href="https://github.com/ersilia-os/eos18ie">https://github.com/ersilia-os/eos18ie</a></p><img src="https://www.ebi.ac.uk/biomodels/static-assets/images/ersilia-logo.png" alt="Ersilia Logo" width="150">2024-05-08T00:00:00Z2025-07-14T17:02:37.81Z2025-03-31T13:25:42.975ZMODEL2405080002MCRO:0000026000009400003480002305STATO:0000274STATO:0000549STATO:000003138123686NCIT:C173515C2890NCIT:C16309NCIT:C176258NCIT:C17429C154407NCIT:C47824NCIT:C19148C45329C258topic_3336topic_0154topic_3474OBI_0200032CHEMINF:000018960612800005741antibioticsaieos18iechemprop