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Fig. 5 | Algorithms for Molecular Biology

Fig. 5

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

Fig. 5

Evolution and structure-based regularization biases variant selections towards those that score favorably under multiple criteria. Shown are the regularization scores for variants selected for GB1 (Left), BRCA1 (Middle), and Spike (Right) under each selection criterion. As expected, variants selected by TPLM-regularized methods have higher log-odds under the TPLM than those selected from non-TPLM regularized methods (Top). Similarly, variants selected by FoldX regularized methods have lower \(\Delta \Delta G\) values than those selected by non-FoldX methods (Bottom). The figures also show that TPLM-regularized methods tend to improve FoldX scores, and that FoldX-regularized methods tend to improve log-odds, indicating that there is some correlation between log-odds and thermodynamic stability

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