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Fig. 3 | BMC Bioinformatics

Fig. 3

From: rstoolbox - a Python library for large-scale analysis of computational protein design data and structural bioinformatics

Fig. 3

Guiding iterative design pipelines. Information retrieved from decoy populations can be used to guide following generations of designs. With the exception of the panel identifiers, the image was directly created with the code presented in Table 2. a Mutant enrichment from comparison of the design on top 5% by score and the overall population. Positions 34, 35, 46 and 47 present a 20% enrichment of certain residue types over the whole population and are selected as positions of interest. b Residue types for the positions of interest in the decoy selected as template of the second generation. c Upon guided mutagenesis, we obtain a total of 16 decoys including the second-generation template. We can observe that the overrepresented residues shown in A are now present in the designed population. Upper x axis shows the original residue types of the template. d Combinatorial targeted mutagenesis yields 16 new designs, three of which showed an improved total score relative to the second-generation template (mutant_count_A is 0). e The three best scoring variants show mutations such as P46G which seem to be clearly favorable for the overall score of the designs. Upper x axis shows the original residue types of the template

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