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Optimization and validation of multi-state NMR protein structures using structural correlations.

ABSTRACT: Recent advances in the field of protein structure determination using liquid-state NMR enable the elucidation of multi-state protein conformations that can provide insight into correlated and non-correlated protein dynamics at atomic resolution. So far, NMR-derived multi-state structures were typically evaluated by means of visual inspection of structure superpositions, target function values that quantify the violation of experimented restraints and root-mean-square deviations that quantify similarity between conformers. As an alternative or complementary approach, we present here the use of a recently introduced structural correlation measure, PDBcor, that quantifies the clustering of protein states as an additional measure for multi-state protein structure analysis. It can be used for various assays including the validation of experimental distance restraints, optimization of the number of protein states, estimation of protein state populations, identification of key distance restraints, NOE network analysis and semiquantitative analysis of the protein correlation network. We present applications for the final quality analysis stages of typical multi-state protein structure calculations.

SUBMITTER: Ashkinadze D

PROVIDER: S-EPMC9018667 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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Optimization and validation of multi-state NMR protein structures using structural correlations.

Ashkinadze Dzmitry D Kadavath Harindranath H Riek Roland R Güntert Peter P

Journal of biomolecular NMR 20220319 1-2

Recent advances in the field of protein structure determination using liquid-state NMR enable the elucidation of multi-state protein conformations that can provide insight into correlated and non-correlated protein dynamics at atomic resolution. So far, NMR-derived multi-state structures were typically evaluated by means of visual inspection of structure superpositions, target function values that quantify the violation of experimented restraints and root-mean-square deviations that quantify sim ...[more]

PMID: 35305195

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Project description:The validation of protein structures through functional assays has been the norm for many years. Functional assays perform this validation for water-soluble proteins very well, but they need to be performed in the same environment as that used for the structural analysis. This is difficult for membrane proteins that are often structurally characterized in detergent environments, although functional assays for these proteins are most frequently performed in lipid bilayers. Because the structure of membrane proteins is known to be sensitive to the membrane mimetic environment, such functional assays are appropriate for validating the protein construct, but not the membrane protein structure. Here, we compare oriented sample solid-state NMR spectral data of diacylglycerol kinase previously published with predictions of such data from recent structures of this protein. A solution NMR structure of diacylglycerol kinase has been obtained in detergent micelles and three crystal structures have been obtained in a monoolein cubic phase. All of the structures are trimeric with each monomer having three transmembrane and one amphipathic helices. However, the solution NMR structure shows typical perturbations induced by a micelle environment that is reflected in the predicted solid-state NMR resonances from the structural coordinates. The crystal structures show few such perturbations, especially for the wild-type structure and especially for the monomers that do not have significant crystal contacts. For these monomers the predicted and observed data are nearly identical. The thermostabilized constructs do show more perturbations, especially the A41C mutation that introduces a hydrophilic residue into what would be the middle of the lipid bilayer inducing additional hydrogen bonding between trimers. These results demonstrate a general technique for validating membrane protein structures with minimal data obtained from membrane proteins in liquid crystalline lipid bilayers by oriented sample solid-state NMR.

Dataset Information

Optimization and validation of multi-state NMR protein structures using structural correlations.

Publications

Optimization and validation of multi-state NMR protein structures using structural correlations.

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