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Fig. 4 | Algorithms for Molecular Biology

Fig. 4

From: Bayesian optimization with evolutionary and structure-based regularization for directed protein evolution

Fig. 4

Regularization leads to better designs. Shown are the cumulative per batch scores for each protein averaged (± 1 SEM) over 100 trials. GP models were initialized with 20 randomly chosen sequences, and each batch consisted of 19 selected variants. Left: GP + UCB + TPLM selected the GB1 variant with highest average fitness (7.76), Middle: GP + EI + FoldX selected the BRCA1 variant with highest average E3 ubiquitin ligase activity (2.65), and Right: GP + UCB + FoldX selected the Spike variant with highest average ACE2 binding affinity (0.98)

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