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Related Experiment Videos

PLUMS: a program for the rapid optimization of focused libraries.

G Bravi1, D V Green, M M Hann

  • 1Computational Chemistry and Informatics, Glaxo Wellcome R&D, Medicines Research Centre, Stevenage, Hertfordshire, UK. gb94807@GlaxoWellcome.co.uk

Journal of Chemical Information and Computer Sciences
|January 11, 2000
PubMed
Summary
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PLUMS is a novel algorithm for selecting monomers in combinatorial chemistry. It optimizes focused libraries by iteratively removing monomers, offering an effective and efficient approach compared to genetic algorithms and monomer frequency analysis.

Area of Science:

  • Computational Chemistry
  • Drug Discovery
  • Chemical Synthesis

Background:

  • Combinatorial chemistry libraries are crucial for drug discovery.
  • Efficient monomer selection is essential for optimizing library properties.
  • Existing methods like GA and MFA have limitations.

Purpose of the Study:

  • Introduce PLUMS, a new method for rational monomer selection.
  • Optimize focused combinatorial libraries with specific 2D/3D properties.
  • Compare PLUMS with existing methods (GA, MFA).

Main Methods:

  • PLUMS identifies virtual hits satisfying property constraints.
  • It iteratively removes monomers from a starting library.
  • A global scoring function balances effectiveness and efficiency.

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Main Results:

  • PLUMS and genetic algorithms (GA) yielded equivalent results on test libraries.
  • Monomer frequency analysis (MFA) was faster but could be misleading.
  • PLUMS effectively optimizes focused libraries.

Conclusions:

  • PLUMS provides a robust method for monomer selection in combinatorial chemistry.
  • It offers a balance between library effectiveness and efficiency.
  • PLUMS is a competitive alternative to GA for library optimization.