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Accurate and rigorous prediction of the changes in protein free energies in a large-scale mutation scan.

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Gapsys,  V.
Research Group of Computational Biomolecular Dynamics, MPI for biophysical chemistry, Max Planck Society;

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Michielssens,  S.
Research Group of Computational Biomolecular Dynamics, MPI for biophysical chemistry, Max Planck Society;

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Seeliger,  D.
Research Group of Computational Biomolecular Dynamics, MPI for biophysical chemistry, Max Planck Society;

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de Groot,  B. L.
Research Group of Computational Biomolecular Dynamics, MPI for biophysical chemistry, Max Planck Society;

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2307451.pdf
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Supplementary Material (public)

2307451_Suppl.pdf
(Supplementary material), 9MB

Citation

Gapsys, V., Michielssens, S., Seeliger, D., & de Groot, B. L. (2016). Accurate and rigorous prediction of the changes in protein free energies in a large-scale mutation scan. Angewandte Chemie-International Edition, 55(26), 7364-7368. doi:10.1002/anie.201510054.


Cite as: https://hdl.handle.net/11858/00-001M-0000-002A-EF25-F
Abstract
The prediction of mutation-induced free-energy changes in protein thermostability or protein–protein binding is of particular interest in the fields of protein design, biotechnology, and bioengineering. Herein, we achieve remarkable accuracy in a scan of 762 mutations estimating changes in protein thermostability based on the first principles of statistical mechanics. The remaining error in the free-energy estimates appears to be due to three sources in approximately equal parts, namely sampling, force-field inaccuracies, and experimental uncertainty. We propose a consensus force-field approach, which, together with an increased sampling time, leads to a free-energy prediction accuracy that matches those reached in experiments. This versatile approach enables accurate free-energy estimates for diverse proteins, including the prediction of changes in the melting temperature of the membrane protein neurotensin receptor 1.