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. 2023 Jan 7;14:114. doi: 10.1038/s41467-022-35692-6

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 3 — a Number of molecules in the refined virtual chemical library that were predicted as “highly active” as a function of the number of votes (confidence level). b Average structural similarity (Tanimoto similarity index computed on Morgan fingerprints) of each de novo design to the fine-tuning set as a function of the number of votes. The solid line represents the mean value, with the shaded area representing the standard deviation. c Top-ranked designs (99/100 votes) selected with the most distant nearest neighbor, whose similarity is indicated below the structure (“Most similar”) in the fine-tuning set. The atom (“Atom scaffold”) and graph (“Graph scaffold”) scaffold novelty of the structure with respect to the fine-tuning set is indicated below each structure (“Yes”: new, “No”: not new). d Top-ranked designs (99/100 votes) selected with the closest nearest neighbor in the fine-tuning set.