Fig. 2: Sequence-based developability parameters show higher redundancies compared to structure-based parameters. | Communications Biology

Fig. 2: Sequence-based developability parameters show higher redundancies compared to structure-based parameters.

From: Biophysical cartography of the native and human-engineered antibody landscapes quantifies the plasticity of antibody developability

Fig. 2

a Absolute pairwise Pearson correlation of sequence and structure developability parameters within the native antibody dataset. Numerical values on the figure represent the median of Pearson correlation for the corresponding subset. Differences were assessed using pairwise Mann-Whitney test with p-value adjustment (Benjamini-Hochberg method). ****p < 0.0001 (Human; IgD: 2.09e-112, IgM: 6.54e-104, IgG: 5.21e-100, IgA: 8.94e-101, IgE: 1.04e-94, IgK: 4.61e-74, IgL: 7.46e-80, Mouse; IgM: 1.276e-98, IgG: 4.76e-101, IgK: 6.9e-88, IgL: 6.68e-71). n = 785 sequence and 1035 structure biologically independent pairwise correlation experiments for each isotype and species combination. b Hierarchical clustering of 40 sequence and 46 structure developability parameters based on pairwise Pearson correlation for 170,473 IgG human antibodies (median of absolute Pearson correlation: 0.02 + /-0.003 SEM). As explained in the inset (top right), each cell within the heatmap reflects the value of Pearson correlation for a pair of DPs. Developability parameters are color-annotated with their corresponding level (sequence or structure), physicochemical property (as detailed in Supplementary Data 1), and dominance status from the ABC-EDA algorithm output at Pearson correlation coefficient threshold of 0.6 (see Methods). Black boxes highlight correlation clusters that contain more than three DPs and exhibit pairwise Pearson correlation coefficient > 0.6. Supplementary Figs. 6–10A.

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