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. 2020 Jan 2;11:68. doi: 10.1038/s41467-019-13867-y

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© The Author(s) 2020

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 — a Eight product-specific iCHO2048s models were constructed for biotherapeutics commonly produced in CHO cells. The protein structures^60–67 shown were downloaded from the Protein Data Bank (www.rcsb.org) with IDs (in clockwise order starting from the top): 1au1, 5brr, 1hzh, 3alq, 1m4u, 2h64, 4bdv, and 1eer. b Pareto optimality frontiers of growth-productivity trade-off curves were computed for the eight iCHO2048s models using the same constraints and experimental data from Supplementary Data 3. The shaded region corresponds to range of maximum productivity at commonly observed growth rates in CHO cell cultures. The molecular weight (in Daltons) of each biotherapeutic is shown in the legend. c All protein features (PTMs, transmembrane domains, and amino acid compositions) were used to fit a multivariate linear regression to predict specific productivity. The model coefficients (β) quantify their contribution to the explained variation in specific productivity. Error bars represent the standard error of the fitted coefficients. Source data are provided as a Source Data file.