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Ertl2009 - Synthetic accessibility score estimation

ABSTRACT: 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). Model Type: Predictive machine learning model. Model Relevance: Estimation of synthetic accessibility score (SAScore) 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/eos9ei3

SUBMITTER: Zainab Ashimiyu-Abdusalam

PROVIDER: MODEL2407180004 | BioModels | 2024-07-18

REPOSITORIES: BioModels

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Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions.

Ertl Peter P Schuffenhauer Ansgar A

Journal of cheminformatics 20090610 1

<h4>Background</h4>A method to estimate ease of synthesis (synthetic accessibility) of drug-like molecules is needed in many areas of the drug discovery process. The development and validation of such a method that is able to characterize molecule synthetic accessibility as a score between 1 (easy to make) and 10 (very difficult to make) is described in this article.<h4>Results</h4>The method for estimation of the synthetic accessibility score (SAscore) described here is based on a combination o ...[more]

PMID: 20298526

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