{"database":"biostudies-other","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["1"],"submitter":["Jumoke Adeyemi"],"journal":["Journal of cheminformatics"],"pagination":["8"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/MODEL2407180004"],"repository":["biostudies-other"],"additional_accession":["20298526"],"pubmed_authors":["Zainab Ashimiyu-Abdusalam","Jumoke Adeyemi"]},"is_claimable":false,"name":"Ertl2009 - Synthetic accessibility score estimation","description":"<p>Estimation of synthetic accessibility score (SAScore) of drug-like molecules based on molecular complexity and fragment contributions. The fragment contributions are based on a 1M sample from PubChem and the molecular complexity is based on the presence/absence of non-standard structural features. It has been validated comparing the SAScore and the estimates of medicinal chemist experts for 40 molecules (r2 = 0.89).</p><p><normal>Model Type:</normal> Predictive machine learning model.<br><normal>Model Relevance:</normal> Estimation of synthetic accessibility score (SAScore)<br><normal>Model Encoded by:</normal>  Miquel Duran-Frigola (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/eos9ei3\">https://github.com/ersilia-os/eos9ei3</a></p><img src=\"https://www.ebi.ac.uk/biomodels/static-assets/images/ersilia-logo.png\" alt=\"Ersilia Logo\" width=\"150\">","dates":{"release":"2024-07-18T00:00:00Z","modification":"2025-07-14T17:00:45.527Z","creation":"2025-03-31T13:27:21.001Z"},"accession":"MODEL2407180004","cross_references":{"stato":["STATO:0000142","STATO:0000237"],"bao":["0002305"],"pubmed":["20298526"],"ncit":["NCIT:C53237","NCIT:C54563","NCIT:C16309","C61408","C45329","C154407","NCIT:C71568"],"edam":["topic_3336","topic_0154","topic_3474"],"cheminf":["CHEMINF:000431","CHEMINF:000316","CHEMINF:000018"],"unknown":["eos9ei3","SA_Score"]}}