In continuation of the established SAMPL challenges, the first euroSAMPL blind prediction challenge investigates the ability of computational methods to predict acidity constants (pKa) of 35 drug-like small molecules. An additional goal is the development of suitable domain-specific metadata standards. Participants are asked to submit both, predictions for the given compounds, and bibliographic as well as methodical metadata. Furthermore, to improve the reproducibility of the obtained results, we ask for raw data and, if available, evaluation scripts that produce the predictions from the uploaded raw data. Detailed information on the challenge, tasks and submission templates will be found on TU Dortmund University's GitLab as soon as the challenge is launched.

All uploaded metadata, submissions and submitted raw data will be uploaded to TU Dortmund University's GitLab instance and made publicly available after the challenge has concluded. Metadata and submission data are published under CC-BY 4.0, software code will be published under the MIT license or a more permissive license.

Challenge GitLab repository

The challenge started on 2024-02-19 and is now closed. Results are provided in the challenge Gitlab repository. Please stay tuned for publication of the overview paper and individual contributions.

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This challenge has been partly funded by the NFDI4Chem consortium.

Logo of the EeuroSAMPL pK_a blind prediction challenge