Solvent accessible surface area-assessed molecular basis of osmolyte-induced protein stability

Abstract

In solvent-modulated protein folding, under certain physiological conditions, an equilibrium exists between the unfolded and folded states of the protein without any need to break or make a covalent bond. In this process, interactions between various protein groups (peptides) and solvent molecules are known to play a major role in determining the directionality of the chemical reaction. However, an understanding of the mechanism of action of the co(solvent) by a generic theoretical underpinning is lacking. In this study, a generic solvation model is developed based on statistical mechanics and the thermodynamic transfer free energy model by considering the microenvironment polarity of the interacting co(solvent)-protein system. According to this model, polarity and the fractional solvent-accessible surface areas contribute to the interaction energies. The present model includes various orientations of participating interactant solvent surfaces of suitable areas. As model systems, besides the backbone we consider naturally occurring amino acid residues solvated in ten different osmolytes, small organic compounds known to modulate protein stability. The present model is able to predict the correct trend of the osmolyte-peptide interactions ranging from stabilizing to destabilizing not only for the backbone but also for side chains. Our model predicts Asn, Gln, Asp, Glu, Arg and Pro to be highly stable in most of the protecting osmolytes while Ala, Val, Ile, Leu, Thr, Met, Lys, Phe, Trp and Tyr are predicted to be moderately stable, and Ser, Cys and Histidine are predicted to be least stable. However, in denaturing solvents, both backbone and side chain models show similar stabilities in urea and guanidine. One of the important aspects of this model is that it is essentially parameter-free and consistent with the electrostatics of the interaction partners that make this model suitable for estimating any solute-solvent interaction energies.

Fig. 1. Schematic view of an interaction. (a) A 3-site backbone model (N⁺O⁻O⁻) and solvent accessible surface areas with partially positive (SA₊), negative (SA₋), and neutral (SA₀) charges as was originally proposed. (b) A 3-site model with solute atoms O, N, and C and solvent accessible surface areas with partially positive (SA₊), negative (SA₋), and neutral (SA₀) charges as proposed in the current work. Consequently, a 3-site model will have now 7 sub-sets. See ESI, Fig. S1 for more on microstate counting.

Fig. 2. Molecular structures of various osmolytes, shown in space-filling representations and color-coded by atom type. Oxygen (red), nitrogen (blue), and carbon (grey); protecting osmolytes are TMAO, sarcosine, betaine, proline, sucrose, trehalose, glycerol, sorbitol, and denaturants are urea and guanidine.

Fig. 3. Molecular electrostatics of amino acid side chains and backbone (bb). Atomic partial charges assigned in the CHARMM force field to 21 amino acids (Gly was excluded, and three protonated states of histidine, Hsd, Hse and Hsp were included). n-Number of atomic charges define the n-site model. For example, amino acids Ala and Phe use 1-site and 6-site models, respectively. For Leu, the γ-carbon which is buried, was not included as a charge site.

Fig. 4. Transfer free energies of various 3-site models. The N⁺O⁻O⁻ configuration is highlighted by blue triangles. Red circles represent all possible 3³ = 27 arrangements between the solute’s three charge sites (+1, 0, −1) and the solvent’s polarity-specific surfaces (SA₊,SA₀,SA₋).

Fig. 5. Local osmolyte concentration vs. measured transfer free energies, ΔG_tr of the 3-site backbone model. ΔG_tr values are given for all seven conformations of all ten osmolytes. Values for the lone N⁺O⁻O⁻ configuration which was originally proposed are shown in maroon open pentagons for all ten osmolytes. In all cases, 1 M osmolyte solution was taken. Local concentration is plotted as scaled deviation between average occupancy of osmolyte on an interaction site (〈O_pref〉) and in the bulk (〈O_bulk〉).

Fig. 6. Calculated ΔG_tr values for the backbone model as osmolyte concentration is increased from >1 M. Available experimental data are plotted using blue circles (sarcosine), magenta triangles (urea), and green inverted triangles (guanidine). Solid lines represent values calculated in this study.

Fig. 7. Computed ΔG_tr values for peptide backbone (a single unit) utilizing (a) CHARMM and (b) OPLS partial charges. For partial charges of 3-site, 4-site and 5-site models, see ESI, Fig. S3.

Fig. 8. Transfer free energies (ΔG_tr) of side chain models calculated using explicit charges, and considering all k-combinations in all ten osmolytes. The color bar runs from red (−0.13) to blue (0.15) representing ΔG_tr values in kcal mol⁻¹. The red color represents better solubility of amino acids in osmolyte than those in blue color. The size of the square displays counting of occurrence of the value. For example, Arg has the greatest solubility in guanidine, and the corresponding ΔG_tr value has lower distribution indicated by the smallest red square. Arg has the lowest solubility in trehalose, and corresponding ΔG_tr value has higher distribution indicated by a large, dark blue square.

Fig. 9. Transfer free energies (ΔG_tr) of aliphatic C and cationic N groups of Arg. They are calculated using explicit charges, and considering all k-combinations in all ten osmolytes.

Fig. 10. Wordcloud representation of stabilities of side chain models in all ten osmolytes. In each sub-set, the larger the size of the word the higher the ΔG_tr value.