Cumulative Millisecond-Long Sampling for a Comprehensive Energetic Evaluation of Aqueous Ionic Liquid Effects on Amino Acid Interactions

The interactions of amino acid side-chains confer diverse energetic contributions and physical properties to a protein’s stability and function. Various computational tools estimate the effect of changing a given amino acid on the protein’s stability based on parametrized (free) energy functions. When parametrized for the prediction of protein stability in water, such energy functions can lead to suboptimal results for other solvents, such as ionic liquids (IL), aqueous ionic liquids (aIL), or salt solutions. However, to our knowledge, no comprehensive data are available describing the energetic effects of aIL on intramolecular protein interactions. Here, we present the most comprehensive set of potential of mean force (PMF) profiles of pairwise protein–residue interactions to date, covering 50 relevant interactions in water, the two biotechnologically relevant aIL [BMIM/Cl] and [BMIM/TfO], and [Na/Cl]. These results are based on a cumulated simulation time of >1 ms. aIL and salt ions can weaken, but also strengthen, specific residue interactions by more than 3 kcal mol–1, depending on the residue pair, residue–residue configuration, participating ions, and concentration, necessitating considering such interactions specifically. These changes originate from a complex interplay of competitive or cooperative noncovalent ion–residue interactions, changes in solvent structural dynamics, or unspecific charge screening effects and occur at the contact distance but also at larger, solvent-separated distances. This data provide explanations at the atomistic and energetic levels for complex IL effects on protein stability and should help improve the prediction accuracies of computational tools that estimate protein stability based on (free) energy functions

Atomic fluctuations calculated from MD simulations.

<p>A, B: Mean (± SEM) atomic fluctuations (RMSF) on a per nucleotide level for Gsw^apt (A) and Gsw^loop (B) over the three simulations for each system setup. Secondary structure regions are depicted above the plots and colored according to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0179271#pone.0179271.g001" target="_blank">Fig 1A</a>. Red: simulations in the absence of Mg²⁺ ions; green: simulations with 12 Mg²⁺ ions per RNA molecule; blue: simulations with 20 Mg²⁺ ions per RNA molecule. C, D, E: Differences in atomic fluctuations projected onto the RNA structure. Larger differences are colored red, smaller differences blue. Nucleotides responsible for ligand binding are shown as sticks. C: Difference in atomic fluctuations for Gsw^apt of 0 Mg²⁺—20 Mg²⁺ ions per RNA molecule. D: Difference in atomic fluctuations in the absence of Mg²⁺ for Gsw^loop—Gsw^apt. E: Difference in atomic fluctuations for Gsw^loop of 0 Mg²⁺—20 Mg²⁺ ions per RNA molecule.</p

Cumulative Millisecond-Long Sampling for a Comprehensive Energetic Evaluation of Aqueous Ionic Liquid Effects on Amino Acid Interactions

The interactions of amino acid side-chains confer diverse energetic contributions and physical properties to a protein’s stability and function. Various computational tools estimate the effect of changing a given amino acid on the protein’s stability based on parametrized (free) energy functions. When parametrized for the prediction of protein stability in water, such energy functions can lead to suboptimal results for other solvents, such as ionic liquids (IL), aqueous ionic liquids (aIL), or salt solutions. However, to our knowledge, no comprehensive data are available describing the energetic effects of aIL on intramolecular protein interactions. Here, we present the most comprehensive set of potential of mean force (PMF) profiles of pairwise protein–residue interactions to date, covering 50 relevant interactions in water, the two biotechnologically relevant aIL [BMIM/Cl] and [BMIM/TfO], and [Na/Cl]. These results are based on a cumulated simulation time of >1 ms. aIL and salt ions can weaken, but also strengthen, specific residue interactions by more than 3 kcal mol–1, depending on the residue pair, residue–residue configuration, participating ions, and concentration, necessitating considering such interactions specifically. These changes originate from a complex interplay of competitive or cooperative noncovalent ion–residue interactions, changes in solvent structural dynamics, or unspecific charge screening effects and occur at the contact distance but also at larger, solvent-separated distances. This data provide explanations at the atomistic and energetic levels for complex IL effects on protein stability and should help improve the prediction accuracies of computational tools that estimate protein stability based on (free) energy functions

Rigidity analyses.

<p>A: Nucleotides involved in binding guanine in the binding site of the aptamer domain of Gsw (PDB ID 1Y27 [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0179271#pone.0179271.ref026" target="_blank">26</a>]). Black dashed lines indicate hydrogen bonds. B: Constraints (black lines) added to conformations of the <i>apo</i> aptamer domain of Gsw to model the presence of guanine in the binding site for rigidity analyses. C, D, E, F: Nucleotide-wise differences in the probability to be in the largest rigid cluster (Δ<i><b>p</b></i>_{<i><b>lrc</b></i>}(<i><b>i</b></i>), <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0179271#pone.0179271.e002" target="_blank">Eq 1</a>, <i><b>E</b></i>_{<i><b>HB</b></i>} = <b>−0.6 kcal/mol</b> for the rigidity analyses) between the ligand being present or absent in the aptamer domain, projected onto the aptamer domain of Gsw^apt (C, E) and Gsw^loop (D, F) in the absence of Mg²⁺ ions (C, D) and in the presence of 20 Mg²⁺ ions (E, F).</p

Cooperative influence on the P1 region.

<p>A: <i>Coop</i>(<i>i</i>) values mapped onto the aptamer. The values were calculated according to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0179271#pone.0179271.e008" target="_blank">Eq 2</a> for the systems in the presence of 20 Mg²⁺ ions (see also <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0179271#pone.0179271.t004" target="_blank">Table 4</a>). Grey nucleotides show <i>Coop</i>(<i>i</i>) values that are not significantly different from zero (<i>p</i> > 0.05). B, C: Model for the influence of tertiary interactions and ligand binding on the stability of the P1 region. The tweezer represents the aptamer domain of the guanine-sensing riboswitch. The secondary structure elements are indicated by colors as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0179271#pone.0179271.g001" target="_blank">Fig 1A</a>. The tertiary interactions are shown as dotted lines at the top of the tweezers and are encircled. The flexibility of the P1 region is indicated by the differently sized arrows at the bottom. B: The ligand-unbound state; C: The ligand (purple) has a stabilizing influence on the P1 region, but more so if the tertiary interactions are present.</p

Structural features of the guanine-sensing riboswitch aptamer domain and behavior of Mg²⁺ ions.

<p>A: Schematic view of transcriptional regulation by the guanine-sensing riboswitch. In the unbound state (top), the switching sequence (purple) is involved in the formation of the anti-terminator. In the guanine (purple oval) bound state (bottom), the P1 region is stabilized, and part of the switching sequence is involved in the formation of the transcription terminator loop. Regions are assigned according to ref. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0179271#pone.0179271.ref008" target="_blank">8</a>]; grey: P1, green: P2, orange: P3, red: L2, blue: L3, yellow: J1/2, cyan: J2/3, brown: J3/1. B: Tertiary structure of the guanine-sensing riboswitch bound to hypoxanthine (HPA in purple) (PDB ID 4FE5) colored according to secondary structure elements as in panel A; the box marks the mutation site. C: Difference between Gsw^apt (top) and Gsw^loop (bottom) in the loop region. The G37A/C61U mutation results in a loss of two hydrogen bonds. Bases are colored as in panels A and B according to which loop they belong to. D: Exchange of two Mg²⁺ ions over a time of 8 ns. The positions of the two Mg²⁺ ions are shown as spheres and colored according to time with two different color scales. E: Comparison of preferred sites of occupancy of Mg²⁺ ions during 550 ns of MD simulations (green) to experimentally determined ion binding sites (red/orange: binding sites of [Co(NH₃)₆]³⁺ ions in X-ray structures with PDB ID 4FE5 [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0179271#pone.0179271.ref017" target="_blank">17</a>]/3RKF [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0179271#pone.0179271.ref018" target="_blank">18</a>]) and nucleotides showing chemical shift changes upon magnesium titration in NMR experiments (blue) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0179271#pone.0179271.ref018" target="_blank">18</a>].</p

Root mean square deviations of Gsw^apt and Gsw^loop as a whole and for substructures^[a].

<p>Root mean square deviations of Gsw^apt and Gsw^loop as a whole and for substructures<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0179271#t001fn001" target="_blank">^[a]</a>.</p

Hydrogen bond occupancy in the L2/L3 loop region of Gsw^apt and Gsw^loop ^[a].

<p>Hydrogen bond occupancy in the L2/L3 loop region of Gsw^apt and Gsw^loop <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0179271#t002fn001" target="_blank">^[a]</a>.</p

Radius of gyration of Gsw^apt and Gsw^loop ^[a].

<p>Radius of gyration of Gsw^apt and Gsw^loop <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0179271#t003fn001" target="_blank">^[a]</a>.</p

Cumulative Millisecond-Long Sampling for a Comprehensive Energetic Evaluation of Aqueous Ionic Liquid Effects on Amino Acid Interactions

The interactions of amino acid side-chains confer diverse energetic contributions and physical properties to a protein’s stability and function. Various computational tools estimate the effect of changing a given amino acid on the protein’s stability based on parametrized (free) energy functions. When parametrized for the prediction of protein stability in water, such energy functions can lead to suboptimal results for other solvents, such as ionic liquids (IL), aqueous ionic liquids (aIL), or salt solutions. However, to our knowledge, no comprehensive data are available describing the energetic effects of aIL on intramolecular protein interactions. Here, we present the most comprehensive set of potential of mean force (PMF) profiles of pairwise protein–residue interactions to date, covering 50 relevant interactions in water, the two biotechnologically relevant aIL [BMIM/Cl] and [BMIM/TfO], and [Na/Cl]. These results are based on a cumulated simulation time of >1 ms. aIL and salt ions can weaken, but also strengthen, specific residue interactions by more than 3 kcal mol–1, depending on the residue pair, residue–residue configuration, participating ions, and concentration, necessitating considering such interactions specifically. These changes originate from a complex interplay of competitive or cooperative noncovalent ion–residue interactions, changes in solvent structural dynamics, or unspecific charge screening effects and occur at the contact distance but also at larger, solvent-separated distances. This data provide explanations at the atomistic and energetic levels for complex IL effects on protein stability and should help improve the prediction accuracies of computational tools that estimate protein stability based on (free) energy functions