The PROSECCO server for chemical shift predictions in ordered and disordered proteins

Máximo Sanz-Hernández,Alfonso De Simone

doi:10.1007/s10858-017-0145-2

Abstract

The chemical shifts measured in solution-state and solid-state nuclear magnetic resonance (NMR) are powerful probes of the structure and dynamics of protein molecules. The exploitation of chemical shifts requires methods to correlate these data with the protein structures and sequences. We present here an approach to calculate accurate chemical shifts in both ordered and disordered proteins using exclusively the information contained in their sequences. Our sequence-based approach, protein sequences and chemical shift correlations (PROSECCO), achieves the accuracy of the most advanced structure-based methods in the characterization of chemical shifts of folded proteins and improves the state of the art in the study of disordered proteins. Our analyses revealed fundamental insights on the structural information carried by NMR chemical shifts of structured and unstructured protein states.

Highlights

Biomolecular nuclear magnetic resonance (NMR) spectroscopy has emerged as a powerful technique to accurately characterize the structure and dynamics of proteins and other biomacromolecules (Kay 2005)
We used sequence homology criteria to select a database of non-redundant proteins whose chemical shifts were deposited in the biological magnetic resonance data bank (BMRB) (Ulrich et al 2008) (BMRB, see “Materials and methods”)
Our data show that the sequence-based prediction of chemical shifts in folded proteins can be as accurate as that achieved by structure-based methods, and this feature enables to define a method for treating both structured and disordered proteins

Summary

Introduction

Biomolecular nuclear magnetic resonance (NMR) spectroscopy has emerged as a powerful technique to accurately characterize the structure and dynamics of proteins and other biomacromolecules (Kay 2005). The quantitative interpretation of NMR spectra toward the characterization of the structural properties and atomic fluctuations of protein molecules has attracted considerable interest in the biochemical community In this context, significant progress has been achieved by using statistical mechanics to analyze NMR databases, which enabled the definition of new approaches to study protein structure (Bouvignies et al 2011; Cavalli et al 2007; Hafsa et al 2015; Shen et al 2008) and dynamics (Berjanskii and Wishart 2005, 2013; Boulton et al 2014; Kim et al 2017; Krieger et al 2014; Masterson et al 2010; Neudecker et al 2012; Robustelli et al 2012; Selvaratnam et al 2011) such as those employing exclusively chemical shifts (CS) from solution (Clore and Schwieters 2003; Kuszewski et al 2004; Sgourakis et al 2011) and solid state NMR (Mollica et al 2012; Robustelli et al 2008). In addition to providing a tool for predicting CS using as input exclusively the protein sequence, the parameterization of PROSECCO has revealed key insights into the structural dependences of protein chemical shifts

Methods

Results

Conclusion