{"database":"biostudies-other","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["18"],"submitter":["Zainab Ashimiyu-Abdusalam"],"journal":["PLoS computational biology"],"pagination":["e1010613"],"species":["Burkholderia cenocepacia"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/MODEL2404080002"],"repository":["biostudies-other"],"additional_accession":["36228001"],"pubmed_authors":["Zainab Ashimiyu-Abdusalam"]},"is_claimable":false,"name":"Rahman2022 - High throughput antibacterial screening with machine learning.","description":"<p>Prediction of antimicrobial potential using a dataset of 29537 compounds screened against the antibiotic resistant pathogen Burkholderia cenocepacia. The model uses the Chemprop Direct Message Passing Neural Network (D-MPNN) and has an AUC score of 0.823 for the test set. It has been used to virtually screen the FDA approved drugs as well as a collection of natural product list (>200k compounds) with hit rates of 26% and 12% respectively.</p><p><normal>Model Type:</normal> Predictive machine learning model.<br><normal>Model Relevance:</normal> Probability that a compound inhibits bacterial pathogens with a focus on ESKAPE.<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/eos5xng\">https://github.com/ersilia-os/eos5xng</a></p><img src=\"https://www.ebi.ac.uk/biomodels/static-assets/images/ersilia-logo.png\" alt=\"Ersilia Logo\" width=\"150\">","dates":{"release":"2024-04-08T00:00:00Z","modification":"2025-07-14T17:03:06.872Z","creation":"2025-03-31T13:25:14.382Z"},"accession":"MODEL2404080002","cross_references":{"mcro":["MCRO:0000009","MCRO:0000026"],"stato":["STATO:0000274","STATO:0000415","STATO:0000524","STATO:0000031"],"bao":["0000094","0002305"],"pubmed":["36228001"],"ncit":["NCIT:C52588","C14187","NCIT:C16309","NCIT:C176258","NCIT:C19146","C154407","C45329"],"edam":["topic_3336","topic_0154","topic_3474"],"cheminf":["CHEMINF:000800","CHEMINF:000018"],"taxonomy":["1869227","95486"],"unknown":["eos5xng","Prediction-of-ATB-Activity","chemprop","Raw%20data%20used%20in%20ML"],"efo":["0005741"]}}