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How to Use Protein 1- D Structure Predicted by PROFphd

  • Burkhard Rost
Protocol
Part of the Springer Protocols Handbooks book series (SPH)

Abstract

The abbreviations used in this chapter are as follows:
  • ™ 1-D structure: one-dimensional structure, i.e., any structural feature that describes single residues, such as protein sequence or string of secondary structure and solvent accessibil- ity assignments per residue.

  • ™ 3-D structure: three-dimensional coordinates of protein structure.

  • ™ EVA: server automatically evaluating structure prediction methods (1, 2, 3).

  • ™ META-PP: Internet service allowing access to a variety of bioinformatics tools through a single interface (4).

  • ™ PDB: Protein Data Bank of experimentally determined 3-D structures of proteins (5).

  • ™ PHDhtm: profile-based neural network prediction of transmembrane helices (6, 7, 8).

  • ™ PHDpsi: divergent profile (PSI-BLAST) based neural network prediction (9).

  • ™ PP (PredictProtein): Internet server for protein sequence analysis and protein structure prediction (7,10,11).

  • ™ PROFphd: advanced profile-based neural network prediction of secondary structure (PROFsec) and solvent accessibility (PROFacc) (11).

  • ™ SWISS-PROT: data base of protein sequences (12).

  • ™ Notations used:

  • ™ Secondary structure: H = helix; E = strand; L = other.

  • ™ Solvent accessibility: e = exposed (≥16% relative accessible surface); b = buried (<16%).

  • ™ Transmembrane helices: T = transmembrane; N = globular.

Keywords

Secondary Structure Reliability Index Transmembrane Helix Solvent Accessibility Fold Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Humana Press Inc., Totowa, NJ 2005

Authors and Affiliations

  • Burkhard Rost
    • 1
  1. 1.CUBIC, Department of Biochemistry and Molecular BiophysicsColumbia University, Columbia University Center for Computational Biology and Bioinformatics, NorthEast Structural Genomics Consortium, Department of Biochemistry and Molecular Biophysics, Columbia UniversityNY

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