VITAL NMR: using chemical shift derived secondary structure information for a limited set of amino acids to assess homology model accuracy
 

VITAL NMR: using chemical shift derived secondary structure information for a limited set of amino acids to assess homology model accuracy


Abstract Homology modeling is a powerful tool for predicting protein structures, whose success depends on obtaining a reasonable alignment between a given structural template and the protein sequence being analyzed. In order to leverage greater predictive power for proteins with few structural templates, we have developed a method to rank homology models based upon their compliance to secondary structure derived from experimental solid-state NMR (SSNMR) data. Such data is obtainable in a rapid manner by simple SSNMR experiments (e.g., 13Câ??13C 2D correlation spectra). To test our homology model scoring procedure for various amino acid labeling schemes, we generated a library of 7,474 homology models for 22 protein targets culled from the TALOS+/SPARTA+ training set of protein structures. Using subsets of amino acids that are plausibly assigned by SSNMR, we discovered that pairs of the residues Val, Ile, Thr, Ala and Leu (VITAL) emulate an ideal dataset where all residues are site specifically assigned. Scoring the models with a predicted VITAL site-specific dataset and calculating secondary structure with the Chemical Shift Index resulted in a Pearson correlation coefficient (â??0.75) commensurate to the control (â??0.77), where secondary structure was scored site specifically for all amino acids (ALL 20) using STRIDE. This method promises to accelerate structure procurement by SSNMR for proteins with unknown folds through guiding the selection of remotely homologous protein templates and assessing model quality.

• Content Type Journal Article
• Category Article
• Pages 1-16
• DOI 10.1007/s10858-011-9576-3
• Authors
  • Michael C. Brothers, Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
  • Anna E. Nesbitt, Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
  • Michael J. Hallock, Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
  • Sanjeewa G. Rupasinghe, Department of Cell and Developmental Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
  • Ming Tang, Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
  • Jason Harris, Department of Biochemistry, Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA
  • Jerome Baudry, Department of Biochemistry, Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA
  • Mary A. Schuler, Department of Cell and Developmental Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
  • Chad M. Rienstra, Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA

• • Journal Journal of Biomolecular NMR
  • Online ISSN 1573-5001
  • Print ISSN 0925-2738

Source: Journal of Biomolecular NMR