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. 2022 Dec 14;13:7747. doi: 10.1038/s41467-022-35422-y

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© The Author(s) 2022

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. 4 — Comparison of predicted output scores (probabilities) from the synthetic chemistry and enzymatic template prioritizers illustrate their balance for different chemical spaces. The likelihood that at least one synthetic chemistry template (black) or enzymatic template (blue) will rank among the top templates when templates from both sets are combined and sorted by their probabilities for a small organic molecules from the MOSES dataset and for b biogenic molecules from ZINC. Means for the top ten probability scores using the enzymatic (blue square) and organic (black triangle) template prioritizers on c the MOSES subset and on d the ZINC subset. Distribution of top-1 probability scores using the enzymatic (blue) and organic (gray) template prioritizers when the scores are computed for e the MOSES subset and for the f ZINC subset.