Protein structure validation and refinement using amide proton chemical shifts derived from quantum mechanics

PLoS One. 2013 Dec 31;8(12):e84123. doi: 10.1371/journal.pone.0084123. eCollection 2013.

Abstract

We present the ProCS method for the rapid and accurate prediction of protein backbone amide proton chemical shifts--sensitive probes of the geometry of key hydrogen bonds that determine protein structure. ProCS is parameterized against quantum mechanical (QM) calculations and reproduces high level QM results obtained for a small protein with an RMSD of 0.25 ppm (r = 0.94). ProCS is interfaced with the PHAISTOS protein simulation program and is used to infer statistical protein ensembles that reflect experimentally measured amide proton chemical shift values. Such chemical shift-based structural refinements, starting from high-resolution X-ray structures of Protein G, ubiquitin, and SMN Tudor Domain, result in average chemical shifts, hydrogen bond geometries, and trans-hydrogen bond ((h3)J(NC')) spin-spin coupling constants that are in excellent agreement with experiment. We show that the structural sensitivity of the QM-based amide proton chemical shift predictions is needed to obtain this agreement. The ProCS method thus offers a powerful new tool for refining the structures of hydrogen bonding networks to high accuracy with many potential applications such as protein flexibility in ligand binding.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Amides / chemistry*
  • Bacterial Proteins / chemistry*
  • Crystallography, X-Ray
  • Humans
  • Hydrogen Bonding
  • Magnetic Resonance Imaging
  • Models, Molecular
  • Molecular Dynamics Simulation
  • Monte Carlo Method
  • Nuclear Magnetic Resonance, Biomolecular*
  • Protein Conformation
  • Protons*
  • Quantum Theory*
  • SMN Complex Proteins / chemistry*
  • Ubiquitin / chemistry*

Substances

  • Amides
  • Bacterial Proteins
  • IgG Fc-binding protein, Streptococcus
  • Protons
  • SMN Complex Proteins
  • Ubiquitin

Grants and funding

ASC is funded by the Novo Nordisk STAR PhD program. MB is funded by the Danish Council for Independent Research (FTP, 09-066546). WB and KL-L are supported by a Hallas-Møller stipend (to KL-L) from the Novo Nordisk Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.