Dataset Information

Voršilák2020 - Bayesian estimation of synthetic accessibility of organic compounds

ABSTRACT: SYBA uses a fragment-based approach to classify whether a molecule is easy or hard to synthesize, and it can also be used to analyze the contribution of individual fragments to the total synthetic accessibility. The easy-to-synthesize dataset is an extract of the ZINC purchasable compounds, and the hard-to-synthesize dataset is generated using a Nonpher approach (introducing small molecular perturbations to transform molecules into more complex compounds). The fragments are calculated with ECFP8 descriptors, and independence between fragments is assumed. Model Type: Predictive machine learning model. Model Relevance: Prediction of synthetic accessibility 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/eos7pw8

SUBMITTER: Zainab Ashimiyu-Abdusalam