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A genetic algorithm for structure-based de novo design.

S C Pegg1, J J Haresco, I D Kuntz

  • 1Department of Pharmaceutical Chemistry, University of California, San Francisco, 94143, USA.

Journal of Computer-Aided Molecular Design
|March 29, 2002
PubMed
Summary
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This study introduces ADAPT, a novel genetic algorithm for de novo drug design. ADAPT utilizes molecular docking to guide compound generation, bypassing the need for known ligand data for effective drug discovery.

Area of Science:

  • Computational Chemistry
  • Medicinal Chemistry
  • Drug Discovery

Background:

  • Genetic algorithms are valuable for de novo drug design but typically require known ligand data to navigate vast chemical spaces.
  • Existing methods often rely on information from known ligands to reduce the search space of potential drug compounds.

Purpose of the Study:

  • To present the ADAPT program, a genetic algorithm designed for de novo drug design that does not rely on known ligand information.
  • To demonstrate ADAPT's capability in generating novel compounds by using molecular docking for fitness evaluation.
  • To explore enhanced strategies for genetic algorithms in drug design.

Main Methods:

  • Developed the ADAPT program, a genetic algorithm employing molecular docking calculations as a fitness function.

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  • Implemented a process where an initial set of compounds is iteratively refined based on fitness scores.
  • Applied ADAPT to three well-characterized drug target systems.

    • Main Results:

    • ADAPT successfully reduces the search space without prior knowledge of ligands.
    • The program iteratively generates new compounds based on the performance of preceding sets.
    • Enhanced local sampling and diversity reintroduction strategies improved results over conventional protocols.

    Conclusions:

    • ADAPT offers a ligand-independent approach to de novo drug design using genetic algorithms and docking.
    • The developed strategies of enhanced local sampling and diversity maintenance are crucial for optimizing genetic algorithm performance in drug design.
    • ADAPT represents a promising tool for exploring novel chemical entities in drug discovery.