Open AccessLocal Bilayer Hydrophobicity Modulates Membrane Protein Stability
Author(s) -
Dagan C. Marx,
Karen G. Fleming
Publication year - 2021
Publication title -
journal of the american chemical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.115
H-Index - 612
eISSN - 1520-5126
pISSN - 0002-7863
DOI - 10.1021/jacs.0c09412
Subject(s) - bilayer , chemistry , translocon , membrane , lipid bilayer , chemical physics , folding (dsp implementation) , lipid bilayer mechanics , side chain , crystallography , lipid bilayer phase behavior , biophysics , molecular dynamics , membrane protein , computational chemistry , biochemistry , organic chemistry , polymer , electrical engineering , biology , engineering
Through the insertion of nonpolar side chains into the bilayer, the hydrophobic effect has long been accepted as a driving force for membrane protein folding. However, how the changing chemical composition of the bilayer affects the magnitude of the side-chain transfer free energies ( Δ G s c ° ) has historically not been well understood. A particularly challenging region for experimental interrogation is the bilayer interfacial region that is characterized by a steep polarity gradient. In this study, we have determined the Δ G s c ° for nonpolar side chains as a function of bilayer position using a combination of experiment and simulation. We discovered an empirical correlation between the surface area of the nonpolar side chain, the transfer free energies, and the local water concentration in the membrane that allows for Δ G s c ° to be accurately estimated at any location in the bilayer. Using these water-to-bilayer Δ G s c ° values, we calculated the interface-to-bilayer transfer free energy ( Δ G i , b ° ). We find that the Δ G i , b ° are similar to the "biological", translocon-based transfer free energies, indicating that the translocon energetically mimics the bilayer interface. Together these findings can be applied to increase the accuracy of computational workflows used to identify and design membrane proteins as well as bring greater insight into our understanding of how disease-causing mutations affect membrane protein folding and function.