Fig. 5: Model feature explanation and finding. | Nature Communications

Fig. 5: Model feature explanation and finding.

From: AGILE platform: a deep learning powered approach to accelerate LNP development for mRNA delivery

Fig. 5: Model feature explanation and finding.The alternative text for this image may have been generated using AI.

a, b This model has identified the top 20 most important molecular descriptors, which have been fine-tuned for HeLa and RAW 264.7. c, d Three-dimensional visualizations of the H9 and R6 structures, with the important regions highlighted for easy identification. e, f The top 15 lipid candidates in HeLa and RAW 264.7 cells have been organized into similarity networks, with each candidate being connected to its four closest neighbors. g The violin plot shows how the predicted potencies are distributed among Tail 1 with varied carbons for the RAW 264.7 cells, using lipids with the most effective headgroup A5 (n = 9, 18, 27, 45, 54, 53, 35, 39, 45, 36, 27, 27, 40, 21, and 27, respectively). h A similar violin plot as in (g) but focusing on lipids of the entire candidate set (n = 198, 396, 594, 990, 1188, 1226, 830, 948, 990, 792, 594, 594, 910, 552, and 594, respectively). i A similar violin plot as in (h) but focusing on the length of Tail 2 (n = 1364, 1188, 1364, 1188, 1364, 1188, 2552, and 1188, respectively). j A similar violin plot as in (h) but focusing on the lipids of the entire candidate set for the HeLa cell (n = 198, 196, 594, 990, 1188, 1226, 830, 948, 990, 792, 594, 594, 910, 552, and 594, respectively). The box denotes the interquartile range of predicted potency change. The mean is marked by the central dot within each box. The error bars represent the 95% confidence interval in (gj). k, l Top two most important molecular descriptors identified by this model fine-tuned for HeLa and RAW 264.7 cells, respectively, for each headgroup. Source data are provided as a Source Data file.

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