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

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.