Letter pubs.acs.org/JPCL
Mutual Exclusion of Urea and Trimethylamine N‑Oxide from Amino Acids in Mixed Solvent Environment Pritam Ganguly,†,‡,§ Timir Hajari,§ Joan-Emma Shea,†,‡ and Nico F. A. van der Vegt*,§ †
Department of Chemistry and Biochemistry and ‡Department of Physics, University of California at Santa Barbara, Santa Barbara, California 93106, United States § Eduard-Zintl-Institut für Anorganische und Physikalische Chemie and Center of Smart Interfaces, Technische Universität Darmstadt, Alarich-Weiss-Straße 10, Darmstadt 64287, Germany S Supporting Information *
ABSTRACT: We study the solvation of amino acids in pure-osmolyte and mixed-osmolyte urea and trimethylamine N-oxide (TMAO) solutions using molecular dynamics simulations. Analysis of Kirkwood−Buff integrals between the solution components provides evidence that in the mixed osmolytic solution, both urea and TMAO are mutually excluded from the amino acid surface, accompanied by an increase in osmolyte−osmolyte aggregation. Similar observations are made in simulations of a model protein backbone, represented by triglycine, and suggest that TMAO stabilizes proteins under urea denaturation conditions by effectively removing urea from the protein surface. The effects of the mixed osmolytes on the solvation of the amino acids and the backbone are found to be highly nonlinear in terms of the effects of the individual osmolytes and independent of differences in the strength of the TMAO−water interactions, as observed with different TMAO force fields.
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favorable vdW component, whereas TMAO is excluded from protein surfaces due to an unfavorable electrostatic interaction.16 Effects of urea and TMAO on proteins in a mixed solvent environment have been shown to be independent of each other and additive in nature. 3,17−19 Preferential interactions of urea with proteins have been reported to be unaffected by the presence of TMAO.17 From later experiments it has been found that the unfolding transition of proteins in the presence of urea is independent of the presence of TMAO18 and the individual m-value (derivative of the free-energy change with cosolvent concentration) of proteins for each osmolyte in a urea-TMAO solution is independent of the other osmolyte present in the solution.18,19 On the other hand, from neutron scattering experiments Meersman et al. have proposed that TMAO counteracts the effects of urea by interacting with urea through hydrogen-bonds, without involving any direct protein− TMAO interactions.20 Another indirect mechanism for the osmolyte-induced conformational changes in proteins has been discussed in terms of the modification of the protein−water interactions by the osmolytes.21 The long-range effects of TMAO on water structure have been confirmed by experiments and theoretical studies.21−26 TMAO binds strongly with water and urea, and hence reduces the number of solvent molecules involved in solvating the protein,27,28 consequently reducing the number of the peptide−solvent hydrogen-bonds, which in
rotein-denaturing effects of urea can be counteracted by the naturally occurring osmolyte trimethylamine N-oxide (TMAO).1 TMAO protects cellular proteins of many marine organisms such as cartilaginous fishes from urea-induced denaturation, where urea and other osmolytes are accumulated at a high concentration in order to maintain the osmotic pressure with the environment.2 Urea-driven denaturation of proteins has been found to be caused by the preferential interaction of urea with the protein backbone and the sidechain, which promotes accumulation of urea near the protein surface.3−12 However, the molecular mechanism behind the effect of TMAO on proteins and its ability to inhibit urea’s effect is not well understood. In the last two decades there have been many experimental and theoretical studies on proteins and other macromolecules in single- or mixed-component osmolyte solutions involving TMAO, but these studies have proposed many different mechanisms and sometimes have also led to contradictory conclusions. Several questions remain open on the issues of TMAO’s direct/indirect effects on protein conformations, preferential interactions of TMAO with proteins, impact of TMAO on the protein backbone or the side-chains, and the influence of TMAO on the water structure or hydrogen-bond network of the solution. It has been argued that unfavorable interaction of TMAO with the protein backbone helps proteins maintain their native folded structures.3,6,13−15 Kokubo et al. quantified the interaction of urea and TMAO with proteins in terms of its electrostatic and van der Waals (vdW) components, and it has been found that urea−protein interaction is dominated by a © XXXX American Chemical Society
Received: December 12, 2014 Accepted: January 23, 2015
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The Journal of Physical Chemistry Letters turn helps the protein to fold back to its native structure.29 However, in the simulation study by Kokubo et al., no significant indication on the modification of the hydrogen-bond network of water by the osmolytes has been found.16 Another simulation study by Cho et al. has shown that TMAO can potentially form hydrogen bonds with exposed dipeptide backbones, but it is preferentially excluded from the backbones of the longer peptides, which leads to an entropy-driven TMAO-induced stabilization mechanism for proteins.30 Along with the entropic contribution arising from the crowding-effect of TMAO, it is also shown to have an enthalpic contribution resulting from the decrease in the hydrogen-bond network of water, which combinedly contribute to the stabilization of the proteins in TMAO solutions.31 In order to shed light on the interactions between proteins and a mixed-osmolyte environment, we herein report the preferential solvation of, first, several individual amino acids, and, then, the protein backbone modeled by a short glycine chain in mixed urea and TMAO solution. By isolating the amino acid and backbone components, we obtain insights into the relative contributions of osmolyte/amino acid and osmolyte/backbone interactions in determining protein conformations in mixed solvents. The preferential solvation is discussed in terms of Kirkwood−Buff integrals (KBIs)32,33 obtained from molecular dynamics (MD) simulations. Details on how to calculate the KBIs from the simulated MD trajectories are explained in the Supporting Information (SI) and elsewhere.34 The experimentally most relevant quantity is the preferential binding coefficient (Γ23), which is related to the solute(2)−water(1) KBI, G21, and solute(2)−cosolvent(3) KBI, G23, according to Γ23 = ρ3(G23 − G21) with ρ3 denoting the cosolvent number density. Γ23 > 0 implies preferential binding, Γ23 < 0 implies preferential exclusion. We report KBIs for 12 amino acids: alanine (A), aspartic acid (D), cysteine (C), glutamine (Q), glycine (G), isoleucine (I), leucine (L), proline (P), serine (S), tryptophan (W), tyrosine (Y), and valine (V) in pure water, 8 M urea, 4 M TMAO and in mixed 8 M urea and 4 M TMAO solutions. A 2:1 molar ratio of urea to TMAO is biologically relevant; although, in general, the concentrations of urea and TMAO accumulated in the cells of the marine animals are lower than the concentrations chosen in our study.2 Our choice of amino acids consists of different types of side-chains, ranging from uncharged to charged (D), polar to hydrophobic, and aliphatic to aromatic. Neutral NH2 and COOH amino acid end-groups were considered. The preferential solvation of the amino acids is compared with preferential solvation of a triglycine chain (G3), which mimics the protein backbone. We used the GROMOS54a7 force field35 for the amino acids, KB-developed force field for urea,36 rigid SPC/E parameters for water molecules,37 and three different force fields for TMAO: (a) Kast model,38 (b) Netz model,39 and (c) Shea model.40 Details of the force fields and other technical specifications for the simulations are provided in the SI. For all amino acids studied in this paper, we find that, in mixed urea−TMAO solution, urea and TMAO molecules mutually exclude each other from the amino acids’ first solvation shells, hence providing a new angle on the stabilizing role of TMAO through an indirect mechanism. Figure 1 shows the spatial density distribution of urea and TMAO around an alanine molecule in pure osmolyte and mixed osmolyte solutions. Comparison of panels a and b in Figure 1, and of panels c and d of Figure 1, shows that TMAO causes a significant reduction in the local urea density. Comparison of
Figure 1. Spatial density maps of urea (black) and TMAO (blue) around alanine. (a,c): alanine in 8 M urea; (e,g) alanine in 4 M TMAO; (b,d,f,h): alanine in mixed 8 M urea and 4 M TMAO. Panels a and b show urea densities 2 or more times higher than the bulk densities; c and d show urea densities 3 or more times higher than the bulk densities; e and f plot TMAO densities 4 or more times higher than the bulk; g and h show TMAO densities 5 or more times higher than the bulk. The TMAO model of Kast38 has been used.
panels e and f in Figure 1, and of panels g and h of Figure 1, shows that urea, in turn, affects the local TMAO densities even stronger. In the mixed cosolvent solutions, the urea and TMAO densities near the methyl group of the alanine molecule are lower than in the solutions with a single cosolvent component. For all other amino acids, the density maps of urea and TMAO around the amino acids are found to be qualitatively similar. As an example, the density maps of urea and TMAO around proline are shown in the SI (Figure S1). Figure 2 quantifies the above picture in terms of the KBIs between the amino acids and the cosolvents (upper panel) and the KBIs among the cosolvent molecules (lower panel). Addition of TMAO to urea−water solution reduces the amino acid−urea KBIs while causing an enhancement of the urea−urea KBIs, reflecting larger urea−urea aggregation in the bulk and weaker urea interaction with the amino acids. Interestingly, a very similar observation can be made when urea is added to TMAO−water solutions: TMAO molecules are depleted from the amino acids, while the TMAO−TMAO KBIs increase. From the data in Figure 2 it can further be inferred that the preferential urea binding coefficient Γ23 is smaller in the system with TMAO. We note that the TMAO− TMAO KBIs are significantly smaller than urea−urea KBIs for all systems. We further note that for most of the amino acids, the observed decrease in the amino acid−TMAO KBIs induced by addition of urea is 2−3 times larger than the decrease in the amino acid−urea KBIs induced by the addition of TMAO. From these results it can be concluded that both osmolytes are depleted from the vicinity of the amino acid molecules when the other osmolyte is added to the solution, a process that is accompanied by an increase in nonlocal self-aggregation of the osmolytes. The same observations are made for the triglycine backbone (see data for G3 in Figure 2). The data clearly point at an amino acid-independent mechanism, also applicable to the model peptide backbone studied here. In agreement with the above data, previous simulations have shown that TMAO interacts with several dipeptides in aqueous solution while being depleted from the surfaces of polypeptides.30 Urea, however, does not show such length scale dependence and interacts with amino acids, 582
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competition among the cosolvent species to bind water is expected in the TMAO−urea aqueous mixtures, provoking urea and TMAO self-aggregation. The results discussed above have all been obtained with the Kast model for TMAO.38 In order to examine the extent to which the observed effects depend on the TMAO force field, we calculated all KBIs with two additional models for TMAO, referred to in this paper as the Netz model39 and the Shea model.40 The force field parameters of the TMAO models are provided in the SI. Figure 3 shows several of the resulting KBIs.
Figure 2. Upper panel: Kirkwood−Buff integrals between amino acids and urea (Gau), amino acids and TMAO (Gat), and amino acids and water (Gaw) for amino acids in 8 M urea, 4 M TMAO, and mixed 8 M urea and 4 M TMAO solutions. Lower panel: urea−urea (Guu) and TMAO−TMAO (Gtt) Kirkwood−Buff integrals for amino acids in 8 M urea, 4 M TMAO, and mixed 8 M urea and 4 M TMAO solutions. The TMAO model of Kast38 was used.
polypeptides, and proteins.3−12 Thus, while urea and TMAO are mutually excluded from amino acids, we expect that TMAO removes urea from the protein surface. All remaining KBIs for the systems studied in this work are reported in the SI. Interestingly, the TMAO−water KBIs are significantly larger in the mixed-osmolyte system (8 M urea + 4 M TMAO) as compared to the pure-osmolyte (4 M TMAO) system (Figure S2). The same effect, albeit smaller, is also seen for the urea−water KBI, while the water−water KBI decreases (Figure S2). This observation sheds some light on what drives the above stabilization mechanism. TMAO binds water strongly.28 In recently reported dielectric spectroscopy experiments by Hunger et al., it has been shown that TMAO tightly binds with three water molecules, forming TMAO·3H2O complexes in solution, which remain unperturbed upon addition of urea.41 The TMAO−water KBIs (Figure S2) are qualitatively consistent with this observation, as a lower bulk density of water, resulting from its replacement by urea molecules, can only lead to significantly higher TMAO−water KBIs if TMAO retains its hydration water in the system with urea. This is further supported by the observation that the addition of urea to pure water solutions increases the water− water KBI, but further addition of TMAO again reduces it (Figure S2). Compared with TMAO−water interactions, urea− water interactions are weaker. Urea−water mixtures display little or no urea self-aggregation owing to nearly identical averaged strengths of urea−water and water−water interactions combined with a weaker urea−urea interaction.36 Hence, a
Figure 3. Comparison of KBIs with different TMAO force fields: Kast model,38 Netz model,39 and Shea model.40 Upper panel: amino acid− urea (Gau) and amino acid−water (Gaw) Kirkwood−Buff integrals for amino acids in 8 M urea, and in the mixture of 8 M urea and 4 M TMAO solutions. Lower panel: urea−urea (Guu) and urea−water (Guw) Kirkwood−Buff integrals for amino acids in pure water, 8 M urea and in mixed 8 M urea and 4 M TMAO solutions. Netz model shows a very high urea−urea aggregation and eventually a lower urea− water KBI.
The Netz model, which has a significantly higher affinity for water (Figure S3), increases the urea aggregation by reducing the number of water molecules available for solvating the urea molecules. Interestingly, the Netz model does not show significant differences in the amino acid−water KBIs compared to the Kast model. In general, the Shea and Kast models show similar trends. The effect of TMAO on the amino acid−urea KBIs is model independent, with the exception of isoleucine and proline, which do not show any significant difference in the amino acid−urea KBI when the Netz force field for TMAO is used. Along with different force fields for TMAO, we also examined the effects of choosing a different force field combination for alanine and water. The all-atom OPLS model42−44 for alanine was combined with the TIP3P water model45 and the Kast TMAO model for 4 M TMAO, 8 M urea, and mixed 8 M urea + 4 M TMAO solutions. The resulting 583
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CURIE based in France at Très Grand Centre de Calcul (TGCC). We acknowledge support from the Center for Scientific Computing from the CNSI, MRL: an NSF MRSEC (DMR-1121053) and NSF CNS-0960316. J.E.S. acknowledges support of the NSF Grant No. MCB-1158577 and the David and Lucile Packard Foundation.
KBIs are qualitatively very similar to the data obtained with the GROMOS54a7 model for alanine and the SPC/E water model. Comparison between these two combinations of the amino acid and the water models can be found in the SI (Figure S4). These results further reconfirm that the TMAO stabilization mechanism proposed above is force field independent, at least for the different combinations of the force fields studied in this work. It is interesting to point out another TMAO force field by MacKerell and co-workers, which has been used to study TMAO (pKa = 4.7) protonation in the presence of RNA.46 To conclude, we have analyzed the preferential solvation of a wide range of amino acid monomers and a short peptide backbone in mixed osmolytic solutions of urea and TMAO using computer simulations. The data uncover a general, amino acid independent mechanism of mutual depletion of each of the two osmolytes from the amino acid and backbone surface by the other osmolyte. While direct TMAO−peptide interactions are length scale dependent,30 direct urea−peptide interactions do not depend on the peptide dimension. The observed ureadepletion mechanism therefore provides a new angle on TMAO-induced stabilization of proteins under urea denaturation conditions. Comparison of simulation data for 8 M urea and 8 M urea + 4 M TMAO solution systems indicates that the observed mechanism is indirectly caused by strong TMAO− water binding. TMAO−water binding drives urea selfaggregation in bulk and decreases the preferential urea− amino acid and urea−backbone binding coefficients in the solutions containing 4 M TMAO.
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ASSOCIATED CONTENT
S Supporting Information *
The Supporting Information file contains simulation details including the parameters of the TMAO force fields, relevant KBI data and preferential binding coefficients for all systems studied, comparison of TMAO−water KBIs for different TMAO force-fields, comparison of KBIs obtained with GROMOS54a7 alanine + SPC/E water and with OPLS-AA alanine + TIP3P water, density maps of urea and TMAO around proline molecules and liquid phase transfer free energies of alanine and neopentane (a model hydrophobe) between water and 1 M TMAO−water solution obtained from free energy calculations. This material is available free of charge via the Internet at http://pubs.acs.org
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REFERENCES
AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS This research was supported by the German Research Foundation (DFG) within the Cluster of Excellence 259 “Smart Interfaces: Understanding and Designing Fluid Boundaries”. This work used computational resources of the Lichtenberg High Performance Computer at the Technische Universität Darmstadt, Germany. This work also used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation (NSF) Grant Numbers ACI-1053575 and TG-MCA05S027. We acknowledge PRACE for awarding us access to resource 584
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