On the critical review of five machine learning-based algorithms for predicting protein stability changes upon mutation
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Abstract A review, recently published in this journal by Fang (2019), showed that methods trained for the prediction of protein stability changes upon mutation have a very critical bias: they neglect that a protein variation (A- > B) and its reverse (B- > A) must have the opposite value of the free energy difference (ΔΔGAB = − ΔΔGBA). In this letter, we complement the Fang’s paper presenting a more general view of the problem. In particular, a machine learning-based method, published in 2015 (INPS), addressed the bias issue directly. We include the analysis of the missing method, showing that INPS is nearly insensitive to the addressed problem.
2009 ◽
Vol 16
(1)
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pp. 61-71
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1976 ◽
pp. 278-279
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2000 ◽
Vol 12
(8A)
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pp. A327-A332
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1975 ◽
Vol 97
(11)
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pp. 3244-3246
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