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Rapid atomic density methods for molecular shape characterization.

J C Mitchell1, R Kerr, L F Ten Eyck

  • 1San Diego Supercomputer Center, University of California, San Diego, 9500 Gilman Dr., La Jolla, CA, USA. mitchell@sdsc.edu

Journal of Molecular Graphics & Modelling
|July 14, 2001
PubMed
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Two novel methods, Fast Atomic Density Evaluation (FADE) and Pairwise Atomic Density Reverse Engineering (PADRE), rapidly characterize molecular shape using atomic density. These techniques identify surface features and assess shape complementarity for molecular docking.

Area of Science:

  • Computational chemistry
  • Structural biology
  • Biophysics

Background:

  • Accurate molecular shape characterization is crucial for understanding molecular interactions.
  • Existing methods often define shape relative to a fixed surface, limiting local geometric analysis.

Purpose of the Study:

  • To introduce two new, rapid algorithms for molecular shape characterization.
  • To enable detailed analysis of local molecular geometry, including crevices and protrusions.
  • To facilitate the assessment of shape complementarity in molecular docking.

Main Methods:

  • Fast Atomic Density Evaluation (FADE) algorithm utilizing fast Fourier transforms for density estimation.
  • Pairwise Atomic Density Reverse Engineering (PADRE) method deriving density measures from atomic density and potential relationships.

Related Experiment Videos

  • Development of descriptors that measure local geometry from points within 3D space around a molecule.
  • Main Results:

    • FADE and PADRE provide rapid and efficient characterization of molecular shape.
    • The methods successfully identify and quantify local geometric features like crevices and protrusions.
    • Descriptors generated by FADE and PADRE are effective for testing shape complementarity.

    Conclusions:

    • FADE and PADRE offer advanced tools for molecular shape analysis.
    • These methods enhance the understanding of molecular surface topography.
    • The techniques are valuable for improving the accuracy of molecular docking predictions.