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Methods for displaying macromolecular structural uncertainty: application to the globins

R B Altman1, C Hughes, M B Gerstein

  • 1Section on Medical Informatics, Stanford University, California 94305-5479, USA.

Journal of Molecular Graphics
|June 1, 1995
PubMed
Summary
This summary is machine-generated.

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This study introduces PROTEAND, a new program visualizing atomic coordinate uncertainty in molecular structures. It enhances structural analysis by representing uncertainty through superposed models, ellipsoids, and rigid-body volumes.

Area of Science:

  • Structural biology
  • Computational chemistry
  • Bioinformatics

Background:

  • Molecular graphics programs typically display atomic coordinates as precise points, neglecting inherent uncertainties.
  • Experimental and computational methods generate structural data with associated uncertainties for each atom.

Purpose of the Study:

  • To develop novel graphical representations for visualizing atomic coordinate uncertainty in molecular structures.
  • To introduce PROTEAND, an interactive program for displaying these uncertainties.

Main Methods:

  • Developed PROTEAND, an interactive display program.
  • Implemented three methods for representing uncertainty: superposed models, ellipsoidal uncertainty (Gaussian model), and rigid-body volumes (dot clouds).
  • Applied PROTEAND to analyze structural variations within the globin protein family.

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Main Results:

  • PROTEAND effectively visualizes structural uncertainty using distinct graphical modalities.
  • Ellipsoidal representations provide insights into atomic correlations.
  • Rigid-body volumes illustrate the motion of substructures like alpha helices.
  • Different display methods are optimal for illustrating specific types of structural variation.

Conclusions:

  • PROTEAND offers versatile tools for representing and analyzing atomic coordinate uncertainty in molecular structures.
  • The choice of visualization method depends on the specific type of structural variation being studied.
  • This approach enhances the interpretation of structural data from various sources.