Journal of Biomolecular NMR

, Volume 32, Issue 1, pp 71–81

Protein energetic conformational analysis from NMR chemical shifts (PECAN) and its use in determining secondary structural elements

  • Hamid R. Eghbalnia
  • Liya Wang
  • Arash Bahrami
  • Amir Assadi
  • John L. Markley
Article

DOI: 10.1007/s10858-005-5705-1

Cite this article as:
Eghbalnia, H., Wang, L., Bahrami, A. et al. J Biomol NMR (2005) 32: 71. doi:10.1007/s10858-005-5705-1

Abstract

We present an energy model that combines information from the amino acid sequence of a protein and available NMR chemical shifts for the purposes of identifying low energy conformations and determining elements of secondary structure. The model (“PECAN”, Protein Energetic Conformational Analysis from NMR chemical shifts) optimizes a combination of sequence information and residue-specific statistical energy function to yield energetic descriptions most favorable to predicting secondary structure. Compared to prior methods for secondary structure determination, PECAN provides increased accuracy and range, particularly in regions of extended structure. Moreover, PECAN uses the energetics to identify residues located at the boundaries between regions of predicted secondary structure that may not fit the stringent secondary structure class definitions. The energy model offers insights into the local energetic patterns that underlie conformational preferences. For example, it shows that the information content for defining secondary structure is localized about a residue and reaches a maximum when two residues on either side are considered. The current release of the PECAN software determines the well-defined regions of secondary structure in novel proteins with assigned chemical shifts with an overall accuracy of 90%, which is close to the practical limit of achievable accuracy in classifying the states.

Keywords

chemical shiftsprotein secondary structurestatistical energy modelstatistical decision

Supplementary material

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Supplementary material

Copyright information

© Springer 2005

Authors and Affiliations

  • Hamid R. Eghbalnia
    • 1
    • 2
  • Liya Wang
    • 1
    • 3
    • 4
  • Arash Bahrami
    • 1
    • 3
    • 4
  • Amir Assadi
    • 2
  • John L. Markley
    • 1
    • 3
    • 4
  1. 1.Biochemistry DepartmentNational Magnetic Resonance Facility at MadisonMadisonUSA
  2. 2.Mathematics DepartmentUniversity of Wisconsin–MadisonMadisonUSA
  3. 3.Center for Eukaryotic Structural GenomicsUniversity of Wisconsin–MadisonMadisonUSA
  4. 4.Graduate Program in BiophysicsUniversity of Wisconsin–MadisonMadisonUSA