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Visible volume: a robust measure for protein structure characterization

L Lo Conte1, T F Smith

  • 1Computer Science Department, Boston University, MA 02215, USA.

Journal of Molecular Biology
|November 21, 1997
PubMed
Summary

We introduce visible volume, a novel geometric measure for protein structure analysis. This method quantifies conserved spatial constraints for side-chain packing, aiding in protein structure prediction and design.

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Area of Science:

  • Computational Biology
  • Structural Biology
  • Biophysics

Background:

  • Protein structure analysis relies on understanding residue interactions and spatial arrangements.
  • Existing methods may not fully capture the conserved spatial constraints relevant for protein function and stability.

Purpose of the Study:

  • To introduce a new geometric measure, "visible volume," for characterizing protein structure.
  • To quantify conserved physical space for side-chain packing at equivalent positions across protein families.

Main Methods:

  • Representing protein side-chains as ideal tetrahedra fixed to the backbone.
  • Calculating "visible volume" as the non-occluded empty space around residue positions after side-chain removal.
  • Developing a parameter-free, locally computed measure robust to variations.

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Main Results:

  • Visible volume quantifies a new type of invariance related to conserved packing space.
  • The measure is robust to crystallographic uncertainties and natural variations in atomic coordinates.
  • Visible volume correlates with residue exposure and observed rotamers in native proteins.

Conclusions:

  • Visible volume is a powerful tool for analyzing protein structure, identifying conserved positions, and predicting biological function.
  • Applications include protein structure prediction, protein design, homology modeling, and structural alignment.
  • This method offers a robust and parameter-free approach to understanding spatial constraints in proteins.