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| 001 | 916528 | ||
| 005 | 20231027114350.0 | ||
| 024 | 7 | _ | |a 10.1021/acs.jcim.2c01123 |2 doi |
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| 037 | _ | _ | |a FZJ-2022-06312 |
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| 100 | 1 | _ | |a El Harrar, Till |0 P:(DE-Juel1)176217 |b 0 |
| 245 | _ | _ | |a Cumulative Millisecond-Long Sampling for a Comprehensive Energetic Evaluation of Aqueous Ionic Liquid Effects on Amino Acid Interactions |
| 260 | _ | _ | |a Washington, DC |c 2023 |b American Chemical Society |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 520 | _ | _ | |a 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. |
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| 700 | 1 | _ | |a Gohlke, Holger |0 P:(DE-Juel1)172663 |b 1 |e Corresponding author |
| 773 | _ | _ | |a 10.1021/acs.jcim.2c01123 |g p. acs.jcim.2c01123 |0 PERI:(DE-600)1491237-5 |n 1 |p 281–298 |t Journal of chemical information and modeling |v 63 |y NA |x 0095-2338 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/916528/files/acs.jcim.2c01123.pdf |
| 856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/916528/files/P02v16_MS_rev_final.pdf |
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