Data set and fitting dependencies when estimating protein mutant stability: Toward simple, balanced, and interpretable models.

Abstract excerpt

Accurate prediction of protein stability changes upon mutation (ΔΔG) is increasingly important to evolution studies, protein engineering, and screening of disease-causing gene variants but is challenged by biases in training data. We investigated 45 linear regression models trained on data sets that account systematically for destabilization bias and mutation-type bias BM . The models were externally validated on...

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