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Toward high throughput 3D virtual screening using spherical harmonic surface representations.

Lazaros Mavridis1, Brian D Hudson, David W Ritchie

  • 1Department of Computing Science, King's College, University of Aberdeen, Aberdeen AB24 3UE, UK.

Journal of Chemical Information and Modeling
|September 11, 2007
PubMed
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Spherical harmonic molecular shape representations enable rapid and accurate searching and clustering of small-molecule databases. This approach offers an efficient new method for high-throughput 3D virtual screening in drug discovery.

Area of Science:

  • Computational chemistry
  • Cheminformatics
  • Drug discovery

Background:

  • Early-stage drug development involves searching chemical databases for potential drug leads.
  • Efficiently searching and clustering large molecular databases is crucial for identifying promising candidates.

Purpose of the Study:

  • To demonstrate the utility of spherical harmonic molecular shape representations for database searching and clustering.
  • To introduce a novel, efficient approach for high-throughput 3D virtual screening.

Main Methods:

  • Utilizing spherical harmonic expansions to represent molecular shapes.
  • Applying shape-based correlation techniques for database searching.
  • Employing clustering algorithms on molecular shape data.

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Main Results:

  • Low-order spherical harmonic expansions yield chemically meaningful clusters.
  • Low-order spherical harmonic shape-based correlation enables practical and efficient searching of large 3D molecular databases.
  • The method facilitates high-throughput 3D virtual screening.

Conclusions:

  • Spherical harmonic molecular shape representations are powerful tools for rapid and accurate database searching and clustering.
  • This technique provides a valuable new approach for virtual screening in drug discovery.
  • Future work includes extending the method to incorporate arbitrary molecular surface properties.