Role of Water in the Selection of Stable Proteins at Ambient and Extreme Thermodynamic Conditions

Proteins that are functional at ambient conditions do not necessarily work at extreme conditions of temperature $T$ and pressure $P$. Furthermore, there are limits of $T$ and $P$ above which no protein has a stable functional state. Here, we show that these limits and the selection mechanisms for working proteins depend on how the properties of the surrounding water change with $T$ and $P$. We find that proteins selected at high $T$ are superstable and are characterized by a nonextreme segregation of a hydrophilic surface and a hydrophobic core. Surprisingly, a larger segregation reduces the stability range in $T$ and $P$. Our computer simulations, based on a new protein design protocol, explain the hydropathy profile of proteins as a consequence of a selection process influenced by water. Our results, potentially useful for engineering proteins and drugs working far from ambient conditions, offer an alternative rationale to the evolutionary action exerted by the environment in extreme conditions.

Popular Summary

Proteins are large, complex molecules that perform many critical functions in living cells. Different proteins have a range of temperatures and pressures for which they are stable. Many life forms thrive under extreme temperatures and pressures, implying that their proteins are naturally selected for their environments. How protein selection responds to drastic changes in an aqueous environment is not understood. We present the first computational study that mimics the natural selection of proteins in water under distinct environmental conditions, with the goal of designing amino acid sequences able to express their functions at specific temperatures and pressures.

Our simulations are based on a novel model for how proteins adapt to a range of thermodynamic conditions. We find that the protein selection process depends strongly on the molecular properties of the surrounding water. Proteins selected at high temperatures are also stable over a wider range of temperatures and pressures than those selected at low temperatures. We also show that high-temperature proteins exhibit a segregation between hydrophilic surface and hydrophobic core that is higher than proteins selected at lower temperature. The sequence segregation of a designed protein therefore depends on the selection temperature and pressure, which is consistent with what is observed in natural proteins working at different environmental conditions.

Our results are significant for understanding protein evolution on Earth, explaining why proteins that evolved in early high-temperature environments are able to work at current ambient conditions.

We also substantiate the tantalizing hypothesis that many features observed in proteins arise naturally when the selection process explicitly takes into account the thermodynamic properties of the solvent.

Figure 1

$T–P$ stability regions of designed and experimental proteins. (a) Average stability regions (closed curves) within which the protein sequences designed with the MIN ENTHALPY protocol at different $T_d$ and $P_d$ fold into the native state. The regions for proteins designed at $P_d=0$ (red, green, and blue curves), close to ambient pressure, are enclosed one into another with an extension that is proportional to $T_d$. All of these regions enclose the stability region of proteins designed at higher $P_d$ (pink curve). The dotted line shows the stability region for a sequence calculated with the IMPLICIT SOLVENT protocol. The “glass-transition” (solid black) line defines the temperatures below which the system does not equilibrate. The long-dashed line represents the limit of stability (spinodal) of the liquid with respect to the gas phase. Pressure and temperature are expressed in internal units (IU). (b) Experimental stability region for different proteins indicated in the legend (adapted from Refs. [40, 41, 42, 43, 44, 45, 46, 47, 48, 49]). The long-dashed line is the liquid-gas transition line. The data show a clear positive correlation between the $T$ range and $P$ range of stability. Pressure denaturation is observed in a range of $-0.1\lesssim P/\mathrm{GPa}\lesssim 0.6$, while stability at higher $P$ is reached by introducing artificial covalent bridges between the amino acids, as in the case of Zn cytochrome $c$ [43]. In both panels, the shaded region corresponds to ambient conditions.

Figure 2

Hydropathy profile of the designed protein surface and core. The color-coded contour plots of the fraction ${\mathcal{P}}_{\mathrm{surf}}^{\mathrm{PHI}}(T_d,P_d)$ of surface hydrophilic amino acid [panels (a) and (b)] and the fraction ${\mathcal{Q}}_{\mathrm{core}}^{\mathrm{PHO}}(T_d,P_d)$ of core hydrophobic amino acid [panels (c) and (d)] as a function of the design temperature $T_d$ and pressure $P_d$, calculated with both design protocols, MIN ENTHALPY [panels (a) and (c)] and MAX GAP [panels (b) and (d)], show a stronger segregation between the hydrophilic surface and the hydrophobic core for proteins designed at high $T_d$ and low or intermediate $P_d$. The straight (green) line in the lower-right corner of each panel marks the liquid-gas spinodal line of the solvent. $T_d$ and $P_d$ are expressed in internal units.

Figure 3

Hydrophilic profile of a protein surface designed at ambient pressure. The fraction ${\mathcal{P}}_{\mathrm{surf}}^{\mathrm{PHI}}(T_d,P_d)$ of surface hydrophilic amino acid decreases with the design temperature $T_d$, for both the design protocols MIN ENTHALPY (black circles) and MAX GAP (diamonds). Data are from Figs. 2 and 2 at $P=0$. Our results qualitatively follow the trend observed for the average hydropathy of real thermophilic [58] (large red circle), mesophilic [58] (large green circle), and ice-binding proteins [59] (large blue circle), plotted at high $T$ ($T=0.45$ IU), intermediate $T$ ($T=0.3$ IU), and low $T$ ($T=0.15$ IU), respectively, to ease the comparison. Such values of $T$ resemble the average working temperature of real thermophilic, mesophilic, and ice-binding proteins. The hydropathy profile (independent of $T_d$) of sequences designed with implicit solvent (dashed line) is unable to reproduce the observed trend.

Figure 4

Isothermal free energy, enthalpy, and entropy variation. Inset: Color-coded (in IU) maximum value of $⟨\mathrm{\Delta }{H}_{\text{R}}^{(h)}⟩$ found for the sequences designed with the MAX GAP protocol. Main panel: The variations of the denaturation free-energy gain $⟨{\mathrm{\Delta }}_G(P)-{\mathrm{\Delta }}_G(0)⟩$, of the denaturation enthalpy gain $⟨{\mathrm{\Delta }}_H(P)-{\mathrm{\Delta }}_H(0)⟩$, and of the folding entropy surplus $⟨{\mathrm{\Delta }}_{TS}(P)-{\mathrm{\Delta }}_{TS}(0)⟩$ increase with $P$ along the isotherm $T=0.15$ IU for a protein designed at $P_d=0.8$ IU and $T_d=0.2$ IU. We calculate $⟨{\mathrm{\Delta }}_H⟩$ as thermodynamic average over equilibrium configurations, $⟨{\mathrm{\Delta }}_G(P)-{\mathrm{\Delta }}_G(0)⟩={\int }_0^P⟨V^f(P)-V^u(0)⟩dP$ and $⟨{\mathrm{\Delta }}_{TS}(P)-{\mathrm{\Delta }}_{TS}(0)⟩=⟨{\mathrm{\Delta }}_H(P)-{\mathrm{\Delta }}_H(0)⟩-⟨{\mathrm{\Delta }}_G(P)-{\mathrm{\Delta }}_G(0)⟩$.

Figure 5

Average stability regions for proteins designed at constant pressure according to the MIN ENTHALPY protocol. The proteins are designed along the isobar $P_d=0.2$ IU. We observe how designed sequences at high $T_d$ are more resistant to thermal fluctuations.

Figure 6

Average compactness of the designed proteins. The compactness is calculated as the average number of residue-residue contact points, regardless of if they correspond to the native contacts, as a function of $T$ and $P$. It is expressed as a (color-coded) percentage over the maximum possible number of contacts and averaged over proteins designed at different values of $P_d$ and $T_d$. The straight (green) line on the bottom represents the liquid-gas spinodal line.

Figure 7

Hydropathy of the protein surface and the protein core of the ice-binding proteins.

Figure 8

Hydropathy profile of proteins designed at ambient pressure for different values of ${\epsilon }_p$. Here, we report how the hydrophilic profile of the protein surface and the hydrophobic profile of the protein core, respectively shown in panels (a) and (b), changes as a function of $T_d$, at ambient pressure, according to the parameter ${\epsilon }_p$, appearing in Eq. (b1). The data are calculated following the protocol MIN ENTHALPY. In all cases, the segregation between the hydrophilic surface and the hydrophobic core decreases with $T$.

Figure 9

Average stability regions for proteins designed according to the MAX GAP protocol. Average stability regions for proteins designed along the isobar $P_d=0$ and the isotherm $T_d=0.2$ IU, respectively, shown in panels (a) and (b). Arrows point at the design pressure $P_d=0$ IU and to the design temperature $T_d=0.2$ IU.

Figure 10

Schematic representation of the water-protein model. The position of the water molecules is coarse-grained, assigning a cell to each water molecule. The cell size coincides with the average distance between first-neighbor molecules and fluctuates according to the Boltzmann weight of isobaric-isothermal ensemble. The conformational state of water molecule $i$ is described via four bonding indices ${\sigma }_{ij}$, each one accounting for the bonding conformation of molecule $i$ with respect to the neighbor in the direction $j$. Water molecules around the protein form the hydration shell (dark blue cells). Protein is modeled as a self-avoiding lattice chain, composed of 20 different amino acids. Each amino acid can be hydrophobic or hydrophilic, according to the Kyte-Doolittle hydropathy scale [82]. Red and green amino acids in the figure refer to core and surface elements, respectively.