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Using NMR Chemical Shifts to Determine Residue-Specific Secondary Structure Populations for Intrinsically Disordered Proteins.

ABSTRACT: Protein disorder is a pervasive phenomenon in biology and a natural consequence of polymer evolution that facilitates cell signaling by organizing sites for posttranslational modifications and protein-protein interactions into arrays of short linear motifs that can be rearranged by RNA splicing. Disordered proteins are missing the long-range nonpolar interactions that form tertiary structures, but they often contain regions with residual secondary structure that are stabilized by protein binding. NMR spectroscopy is uniquely suited to detect residual secondary structure in a disordered protein and it can provide atomic resolution data on the structure and dynamics of disordered protein interaction sites. Here we describe how backbone chemical shifts are used for assigning residual secondary structure in disordered proteins and discuss some of the tools available for estimating secondary structure populations with a focus on disordered proteins containing different levels of alpha helical secondary structure which are stabilized by protein binding.

SUBMITTER: Borcherds WM

PROVIDER: S-EPMC8130511 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Using NMR Chemical Shifts to Determine Residue-Specific Secondary Structure Populations for Intrinsically Disordered Proteins.

Borcherds Wade M WM Daughdrill Gary W GW

Methods in enzymology 20181022

Protein disorder is a pervasive phenomenon in biology and a natural consequence of polymer evolution that facilitates cell signaling by organizing sites for posttranslational modifications and protein-protein interactions into arrays of short linear motifs that can be rearranged by RNA splicing. Disordered proteins are missing the long-range nonpolar interactions that form tertiary structures, but they often contain regions with residual secondary structure that are stabilized by protein binding ...[more]

PMID: 30471686

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Project description:By merging advanced dimensionality reduction (DR) and clustering algorithm (CA) techniques, our study advances the sampling procedure for predicting NMR chemical shifts (CS) in intrinsically disordered proteins (IDPs), making a significant leap forward in the field of protein analysis/modeling. We enhance NMR CS sampling by generating clustered ensembles that accurately reflect the different properties and phenomena encapsulated by the IDP trajectories. This investigation critically assessed different rapid CS predictors, both neural network (e.g., Sparta+ and ShiftX2) and database-driven (ProCS-15), and highlighted the need for more advanced quantum calculations and the subsequent need for more tractable-sized conformational ensembles. Although neural network CS predictors outperformed ProCS-15 for all atoms, all tools showed poor agreement with HN CSs, and the neural network CS predictors were unable to capture the influence of phosphorylated residues, highly relevant for IDPs. This study also addressed the limitations of using direct clustering with collective variables, such as the widespread implementation of the GROMOS algorithm. Clustered ensembles (CEs) produced by this algorithm showed poor performance with chemical shifts compared to sequential ensembles (SEs) of similar size. Instead, we implement a multiscale DR and CA approach and explore the challenges and limitations of applying these algorithms to obtain more robust and tractable CEs. The novel feature of this investigation is the use of solvent-accessible surface area (SASA) as one of the fingerprints for DR alongside previously investigated α carbon distance/angles or ϕ/ψ dihedral angles. The ensembles produced with SASA tSNE DR produced CEs better aligned with the experimental CS of between 0.17 and 0.36 r2 (0.18-0.26 ppm) depending on the system and replicate. Furthermore, this technique produced CEs with better agreement than traditional SEs in 85.7% of all ensemble sizes. This study investigates the quality of ensembles produced based on different input features, comparing latent spaces produced by linear vs nonlinear DR techniques and a novel integrated silhouette score scanning protocol for tSNE DR.

Dataset Information

Using NMR Chemical Shifts to Determine Residue-Specific Secondary Structure Populations for Intrinsically Disordered Proteins.

Publications

Using NMR Chemical Shifts to Determine Residue-Specific Secondary Structure Populations for Intrinsically Disordered Proteins.

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