Interactions of the Osmolyte Glycine Betaine with Molecular Surfaces in Water: Thermodynamics, Structural Interpretation, and Prediction of m-Values

• Published in: Biochemistry (Easton) 2009-11, Vol.48 (43), p.10372-10379
• Main Authors: Capp, Michael W, Pegram, Laurel M, Saecker, Ruth M, Kratz, Megan, Riccardi, Demian, Wendorff, Timothy, Cannon, Jonathan G, Record, M. Thomas
• Format: Article
• Language: English
• Subjects: Amides - chemistry; Betaine - chemistry; Biopolymers - chemistry; Escherichia coli; Hydrocarbons, Aromatic - chemistry; Models, Chemical; Thermodynamics; Water - chemistry
• ISSN: 0006-2960; 1520-4995
• DOI: 10.1021/bi901273r

Noncovalent self-assembly of biopolymers is driven by molecular interactions between functional groups on complementary biopolymer surfaces, replacing interactions with water. Since individually these interactions are comparable in strength to interactions with water, they have been difficult to quantify. Solutes (osmolytes, denaturants) exert often large effects on these self-assembly interactions, determined in sign and magnitude by how well the solute competes with water to interact with the relevant biopolymer surfaces. Here, an osmometric method and a water-accessible surface area (ASA) analysis are developed to quantify and interpret the interactions of the remarkable osmolyte glycine betaine (GB) with molecular surfaces in water. We find that GB, lacking hydrogen bond donors, is unable to compete with water to interact with anionic and amide oxygens; this explains its effectiveness as an osmolyte in the Escherichia coli cytoplasm. GB competes effectively with water to interact with amide and cationic nitrogens (hydrogen bonding) and especially with aromatic hydrocarbon (cation−π). The large stabilizing effect of GB on lac repressor−lac operator binding is predicted quantitatively from ASA information and shown to result largely from dehydration of anionic DNA phosphate oxygens in the protein−DNA interface. The incorporation of these results into theoretical and computational analyses will likely improve the ability to accurately model intra- and interprotein interactions. Additionally, these results pave the way for development of solutes as kinetic/mechanistic and thermodynamic probes of conformational changes and formation/disruption of molecular interfaces that occur in the steps of biomolecular self-assembly processes.