Documentation of an Imperative To Improve Methods for Predicting Membrane Protein Stability.

Autor:	Kroncke BM; Department of Biochemistry, ‡Center for Structural Biology, §Departments of Chemistry, Pharmacology, and Bioinformatics, and ∥Department of Biostatistics, Vanderbilt University , Nashville, Tennessee 37240, United States., Duran AM; Department of Biochemistry, ‡Center for Structural Biology, §Departments of Chemistry, Pharmacology, and Bioinformatics, and ∥Department of Biostatistics, Vanderbilt University , Nashville, Tennessee 37240, United States., Mendenhall JL; Department of Biochemistry, ‡Center for Structural Biology, §Departments of Chemistry, Pharmacology, and Bioinformatics, and ∥Department of Biostatistics, Vanderbilt University , Nashville, Tennessee 37240, United States., Meiler J; Department of Biochemistry, ‡Center for Structural Biology, §Departments of Chemistry, Pharmacology, and Bioinformatics, and ∥Department of Biostatistics, Vanderbilt University , Nashville, Tennessee 37240, United States., Blume JD; Department of Biochemistry, ‡Center for Structural Biology, §Departments of Chemistry, Pharmacology, and Bioinformatics, and ∥Department of Biostatistics, Vanderbilt University , Nashville, Tennessee 37240, United States., Sanders CR; Department of Biochemistry, ‡Center for Structural Biology, §Departments of Chemistry, Pharmacology, and Bioinformatics, and ∥Department of Biostatistics, Vanderbilt University , Nashville, Tennessee 37240, United States.
Jazyk:	angličtina
Zdroj:	Biochemistry [Biochemistry] 2016 Sep 13; Vol. 55 (36), pp. 5002-9. Date of Electronic Publication: 2016 Aug 30.
DOI:	10.1021/acs.biochem.6b00537
Abstrakt:	There is a compelling and growing need to accurately predict the impact of amino acid mutations on protein stability for problems in personalized medicine and other applications. Here the ability of 10 computational tools to accurately predict mutation-induced perturbation of folding stability (ΔΔG) for membrane proteins of known structure was assessed. All methods for predicting ΔΔG values performed significantly worse when applied to membrane proteins than when applied to soluble proteins, yielding estimated concordance, Pearson, and Spearman correlation coefficients of <0.4 for membrane proteins. Rosetta and PROVEAN showed a modest ability to classify mutations as destabilizing (ΔΔG < -0.5 kcal/mol), with a 7 in 10 chance of correctly discriminating a randomly chosen destabilizing variant from a randomly chosen stabilizing variant. However, even this performance is significantly worse than for soluble proteins. This study highlights the need for further development of reliable and reproducible methods for predicting thermodynamic folding stability in membrane proteins.
Databáze:	MEDLINE
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