Accurate and Rigorous Prediction of the Changes in Protein Free Energies in a Large-Scale Mutation Scan.
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.
Computational Biomolecular Dynamics Group, Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077, Göttingen, Germany. vgapsys@gwdg.de.
Vytautas
V
Gapsys
Computational Biomolecular Dynamics Group, Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077, Göttingen, Germany.
Servaas
S
Michielssens
Lead Identification and Optimization Support, Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorfer Strasse 65, 88397, Biberach, Germany.
Daniel
D
Seeliger
Computational Biomolecular Dynamics Group, Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077, Göttingen, Germany. bgroot@gwdg.de.
Bert L
BL
de Groot
D009154:Mutation; D011485:Protein Binding; D055550:Protein Stability; D018028:Receptors, Neurotensin / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism; D013816:Thermodynamics
D018028:Receptors, Neurotensin; C114036:neurotensin type 1 receptor
force field; free-energy calculations; proteins; thermostability