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Dynamic ion pair behavior stabilizes single α-helices in proteins.

ABSTRACT: Ion pairs are key stabilizing interactions between oppositely charged amino acid side chains in proteins. They are often depicted as single conformer salt bridges (hydrogen-bonded ion pairs) in crystal structures, but it is unclear how dynamic they are in solution. Ion pairs are thought to be particularly important in stabilizing single α-helix (SAH) domains in solution. These highly stable domains are rich in charged residues (such as Arg, Lys, and Glu) with potential ion pairs across adjacent turns of the helix. They provide a good model system to investigate how ion pairs can contribute to protein stability. Using NMR spectroscopy, small-angle X-ray light scattering (SAXS), and molecular dynamics simulations, we provide here experimental evidence that ion pairs exist in a SAH in murine myosin 7a (residues 858-935), but that they are not fixed or long lasting. In silico modeling revealed that the ion pairs within this α-helix exhibit dynamic behavior, rapidly forming and breaking and alternating between different partner residues. The low-energy helical state was compatible with a great variety of ion pair combinations. Flexible ion pair formation utilizing a subset of those available at any one time avoided the entropic penalty of fixing side chain conformations, which likely contributed to helix stability overall. These results indicate the dynamic nature of ion pairs in SAHs. More broadly, thermodynamic stability in other proteins is likely to benefit from the dynamic behavior of multi-option solvent-exposed ion pairs.

SUBMITTER: Batchelor M

PROVIDER: S-EPMC6398138 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Protein secondary structure elements (PSSEs) such as α-helices, β-strands, and turns are the primary building blocks of the tertiary protein structure. Our primary interest here is to reveal the characteristics of the nanoenvironment formed by both PSSEs and their surrounding amino acid residues (AARs), which might contribute to the general understanding of how proteins fold. The characteristics of such nanoenvironments must be specific to each secondary structure element, and we have set our goal here to gather the fullest possible description of the α-helical nanoenvironment. In general, this postulate (the existence of specific nanoenvironments for specific protein substructures/neighbourhoods/regions with distinct functionality) was already successfully explored and confirmed for some protein regions, such as protein-protein interfaces and enzyme catalytic sites. Consequently, PSSEs were the obvious next choice for additional work for further evidence showing that specific nanoenvironments (having characteristics fully describable by means of structural and physical chemical descriptors) do exist for the corresponding and determined intraprotein regions. The nanoenvironment of α-helices (nEoαH) is defined as any region of the protein where this secondary structure element type is detected. The nEoαH, therefore, includes not only the α-helix amino acid residues but also the residues immediately around the α-helix. The hypothesis that motivated this work is that it might in fact be possible to detect a postulated "signal" or "signature" that distinguishes the specific location of α-helices. This "signal" must be discernible by tracking differences in the values of physical, chemical, physicochemical, structural and geometric descriptors immediately before (or after) the PSSE from those in the region along the α-helices. The search for this specific nanoenvironment "signal" was made possible by aligning previously selected α-helices of equal length. Afterward, we calculated the average value, standard deviation and mean square error at each aligned residue position for each selected descriptor. We applied Student's t-test, the Kolmogorov-Smirnov test and MANOVA statistical tests to the dataset constructed as described above, and the results confirmed that the hypothesized "signal"/"signature" is both existing/identifiable and capable of distinguishing the presence of an α-helix inside the specific nanoenvironment, contextualized as a specific region within the whole protein. However, such conclusion might rarely be reached if only one descriptor is considered at a time. A more accurate signal with broader coverage is achieved only if one applies multivariate analysis, which means that several descriptors (usually approximately 10 descriptors) should be considered at the same time. To a limited extent (up to a maximum of 15% of cases), such conclusion is also possible with only a single descriptor, and the conclusion is also possible in general for up to 50-80% of cases when no less than 5 nonlinear descriptors are selected and considered. Using all the descriptors considered in this work, provided all assumptions about data characteristics for this analysis are met, multivariate analysis regularly reached a coverage and accuracy above 90%. Understanding how secondary structure elements are formed and maintained within a protein structure could enable a more detailed understanding of how proteins reach their final 3D structure and consequently, their function. Likewise, this knowledge may also improve the tools used to determine how good a structure is by means of comparing the "signal" around a selected PSSE with the one obtained from the best (resolution and quality wise) protein structures available.

Project description:The electrostatic free energy contribution of an ion pair in a protein depends on two factors, geometrical orientation of the side-chain charged groups with respect to each other and the structural context of the ion pair in the protein. Conformers in NMR ensembles enable studies of the relationship between geometry and electrostatic strengths of ion pairs, because the protein structural contexts are highly similar across different conformers. We have studied this relationship using a dataset of 22 unique ion pairs in 14 NMR conformer ensembles for 11 nonhomologous proteins. In different NMR conformers, the ion pairs are classified as salt bridges, nitrogen-oxygen (N-O) bridges and longer-range ion pairs on the basis of geometrical criteria. In salt bridges, centroids of the side-chain charged groups and at least a pair of side-chain nitrogen and oxygen atoms of the ion-pairing residues are within a 4 A distance. In N-O bridges, at least a pair of the side-chain nitrogen and oxygen atoms of the ion-pairing residues are within 4 A distance, but the distance between the side-chain charged group centroids is greater than 4 A. In the longer-range ion pairs, the side-chain charged group centroids as well as the side-chain nitrogen and oxygen atoms are more than 4 A apart. Continuum electrostatic calculations indicate that most of the ion pairs have stabilizing electrostatic contributions when their side-chain charged group centroids are within 5 A distance. Hence, most (approximately 92%) of the salt bridges and a majority (68%) of the N-O bridges are stabilizing. Most (approximately 89%) of the destabilizing ion pairs are the longer-range ion pairs. In the NMR conformer ensembles, the electrostatic interaction between side-chain charged groups of the ion-pairing residues is the strongest for salt bridges, considerably weaker for N-O bridges, and the weakest for longer-range ion pairs. These results suggest empirical rules for stabilizing electrostatic interactions in proteins.

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Dynamic ion pair behavior stabilizes single α-helices in proteins.

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