Laurel M. Pegram

Thermodynamic origin of hofmeister ion effects.

Quantitative interpretation and prediction of Hofmeister ion effects on protein processes, including folding and crystallization, have been elusive goals of a century of research. Here, a quantitative thermodynamic analysis, developed to treat noncoulombic interactions of solutes with biopolymer surface and recently extended to analyze the effects of Hofmeister salts on the surface tension of water, is applied to literature solubility data for small hydrocarbons and model peptides. This analysis allows us to obtain a minimum estimate of the hydration b1 (H2O A(-2)), of hydrocarbon surface and partition coefficients Kp, characterizing the distribution of salts and salt ions between this hydration water and bulk water. Assuming that Na+ and SO4(2-) ions of Na2SO4 (the salt giving the largest reduction in hydrocarbon solubility as well as the largest increase in surface tension) are fully excluded from the hydration water at hydrocarbon surface, we obtain the same b1 as for air-water surface (approximately 0.18 H2O A(-2)). Rank orders of cation and anion partition coefficients for nonpolar surface follow the Hofmeister series for protein processes, but are strongly offset for cations in the direction of exclusion (preferential hydration). By applying a coarse-grained decomposition of water accessible surface area (ASA) into nonpolar, polar amide, and other polar surface and the same hydration b1 to interpret peptide solubility increments, we determine salt partition coefficients for amide surface. These partition coefficients are separated into single-ion contributions based on the observation that both Cl- and Na+ (also K+) occupy neutral positions in the middle of the anion and cation Hofmeister series for protein folding. Independent of this assignment, we find that all cations investigated are strongly accumulated at amide surface while most anions are excluded. Cation and anion effects are independent and additive, allowing successful prediction of Hofmeister salt effects on micelle formation and other processes from structural information (ASA).

Quantifying why urea is a protein denaturant, whereas glycine betaine is a protein stabilizer

To explain the large, opposite effects of urea and glycine betaine (GB) on stability of folded proteins and protein complexes, we quantify and interpret preferential interactions of urea with 45 model compounds displaying protein functional groups and compare with a previous analysis of GB. This information is needed to use urea as a probe of coupled folding in protein processes and to tune molecular dynamics force fields. Preferential interactions between urea and model compounds relative to their interactions with water are determined by osmometry or solubility and dissected using a unique coarse-grained analysis to obtain interaction potentials quantifying the interaction of urea with each significant type of protein surface (aliphatic, aromatic hydrocarbon (C); polar and charged N and O). Microscopic local-bulk partition coefficients Kp for the accumulation or exclusion of urea in the water of hydration of these surfaces relative to bulk water are obtained. Kp values reveal that urea accumulates moderately at amide O and weakly at aliphatic C, whereas GB is excluded from both. These results provide both thermodynamic and molecular explanations for the opposite effects of urea and glycine betaine on protein stability, as well as deductions about strengths of amide NH—amide O and amide NH—amide N hydrogen bonds relative to hydrogen bonds to water. Interestingly, urea, like GB, is moderately accumulated at aromatic C surface. Urea m-values for protein folding and other protein processes are quantitatively interpreted and predicted using these urea interaction potentials or Kp values.

Partitioning of atmospherically relevant ions between bulk water and the water/vapor interface

Recently, surface-sensitive spectroscopy data and molecular dynamics simulations have generated intense interest in the distribution of electrolyte ions between bulk water and the air/water interface. A partitioning model for cations and anions developed for biopolymer surface is extended here to interpret the effects of selected acids, bases, and salts on the surface tension of water. Data for electrolytes were analyzed by using a lower-bound value for the number of water molecules in the surface region [0.2 H2O Å−2 (approximately two layers of water)], obtained by assuming that both Na+ and SO42− (i.e., Na2SO4) are fully excluded from this region. Surface–bulk partition coefficients of atmospherically relevant anions and the proton are determined. Notably, we find that H+ is most strongly surface-accumulated, I− is modestly accumulated, NO3− is evenly distributed, and OH− is weakly excluded.

Why Hofmeister effects of many salts favor protein folding but not DNA helix formation

The majority (∼70%) of surface buried in protein folding is hydrocarbon, whereas in DNA helix formation, the majority (∼65%) of surface buried is relatively polar nitrogen and oxygen. Our previous quantification of salt exclusion from hydrocarbon (C) accessible surface area (ASA) and accumulation at amide nitrogen (N) and oxygen (O) ASA leads to a prediction of very different Hofmeister effects on processes that bury mostly polar (N, O) surface compared to the range of effects commonly observed for processes that bury mainly nonpolar (C) surface, e.g., micelle formation and protein folding. Here we quantify the effects of salts on folding of the monomeric DNA binding domain (DBD) of lac repressor (lac DBD) and on formation of an oligomeric DNA duplex. In accord with this prediction, no salt investigated has a stabilizing Hofmeister effect on DNA helix formation. Our ASA-based analyses of model compound data and estimates of the surface area buried in protein folding and DNA helix formation allow us to predict Hofmeister effects on these processes. We observe semiquantitative to quantitative agreement between these predictions and the experimental values, obtained from a novel separation of coulombic and Hofmeister effects. Possible explanations of deviations, including salt-dependent unfolded ensembles and interactions with other types of surface, are discussed.

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

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-pi). 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.

Preferential interactions between small solutes and the protein backbone: A computational analysis

To improve our understanding of the effects of small solutes on protein stability, we conducted atomistic simulations to quantitatively characterize the interactions between two broadly used small solutes, urea and glycine betaine (GB), and a triglycine peptide, which is a good model for a protein backbone. Multiple solute concentrations were analyzed, and each solute-peptide-water ternary system was studied with approximately 200-300 ns of molecular dynamics simulations with the CHARMM force field. The comparison between calculated preferential interaction coefficients (Gamma(23)) and experimentally measured values suggests that semiquantitative agreement with experiments can be obtained if care is exercised to balance interactions among the solute, protein, and water. On the other hand, qualitatively incorrect (i.e., wrong sign in Gamma(23)) results can be obtained if a solute model is constructed by directly taking parameters for chemically similar groups from an existing force field. Such sensitivity suggests that small solute thermodynamic data can be valuable in the development of accurate force field models of biomolecules. Further decomposition of Gamma(23) into group contributions leads to additional insights regarding the effects of small solutes on protein stability. For example, use of the CHARMM force field predicts that urea preferentially interacts with not only amide groups in the peptide backbone but also aliphatic groups, suggesting a role for these interactions in urea-induced protein denaturation; quantitatively, however, it is likely that the CHARMM force field overestimates the interaction between urea and aliphatic groups. The results with GB support a simple thermodynamic model that assumes additivity of preferential interaction between GB and various biomolecular surfaces.

Quantifying the Roles of Water and Solutes (Denaturants, Osmolytes, and Hofmeister Salts) in Protein and Model Processes Using the Solute Partitioning Model

Salts and uncharged solutes in aqueous solution exert effects on a wide range of processes in which large amounts ofbiopolymer surface are buried or exposed (folding/unfolding, complexation/dissociation, or precipitation/dissolution). A simple two-state solute partitioning model (SPM, where the solute is partitioned between the bulk and surface water) allows the interpretation and prediction of the thermodynamic effects of various uncharged solutes (e.g., urea, glycine betaine) on protein and nucleic acid processes in terms of structural information. The correlation of solute effects with various coarse-grained types of biopolymer surface exposed or buried in a process provides a novel probe for investigation of large-scale conformational changes. Solutes that are fully excluded from one or more types of biopolymer surface are useful to quantify changes in water of hydration of these surfaces in biopolymer processes. Additionally, application of the SPM to the analysis of non-Coulombic salt effects on various model processes provides an estimate for the hydration layer at surfaces and shows that ion effects are additive and independent of the nature of the counterion.

Prediction of Hofmeister ion effects on biopolymer processes

At moderate to high concentrations, salt ions exert a wide range of effects on protein folding and other protein processes, from extremely destabilizing (GuH+, SCN-) to very stabilizing (SO42-). The Hofmeister series is a qualitative ranking of these effects, originally based on the effectiveness of salts as protein precipitants and subsequently observed for other processes including creating air-water surface and dissolving hydrocarbons in water. Recently surface spectroscopy, molecular dynamics simulations and molecular thermodynamic analysis of surface tension and model compound solubility data have all provided evidence that local accumulation or exclusion of individual salt ions, relative to bulk concentrations, is responsible for their Hofmeister effects. In particular, application of a novel two-domain salt ion partitioning model (SPM) to analyze effects of Hofmeister salts on the surface tension of water and on hydrocarbon and peptide solubility (Pegram & Record, J. Phys. Chem. B 112, 9428 (2008); 111, 5411 (2007)) provides a quantitative molecular thermodynamic description of the individual partitioning of salt cations and anions at uncharged interfaces, with predictive capability. This analysis shows that the Hofmeister rank order of ions arises from their interactions with nonpolar surface. Surface-bulk partition coefficients of ions obtained from hydrocarbon and amide model compound solubility data, together with a coarse-grained description of functional groups that make up molecular surfaces, allow the quantitative prediction of Hofmeister (noncoulombic) salt effects on micelle formation, protein folding, protein crystallization and DNA helix formation.This work is supported by NIH GM47022.