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A self-organizing algorithm for molecular alignment and pharmacophore development.

Deepak Bandyopadhyay1, Dimitris K Agrafiotis

  • 1Johnson & Johnson Pharmaceutical Research and Development, L.L.C., 665 Stockton Drive, Exton, Pennsylvania 19341, USA.

Journal of Computational Chemistry
|November 14, 2007
PubMed
Summary
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We developed a fast Stochastic Proximity Embedding (SPE) method for simultaneous 3D structure generation and pharmacophore alignment. This approach efficiently aligns diverse ligands based on 3D pharmacophore hypotheses, improving drug discovery.

Area of Science:

  • Computational chemistry
  • Drug discovery
  • Molecular modeling

Background:

  • Current flexible molecular alignment methods are often slow or rely on pre-existing conformations.
  • Iterative structure generation and alignment methods, like genetic algorithms, can be computationally intensive.
  • Stochastic Proximity Embedding (SPE) has previously shown efficient 3D conformational space sampling.

Purpose of the Study:

  • To present a novel method for simultaneous 3D structure generation and pharmacophore-based alignment.
  • To improve the speed and efficiency of aligning multiple molecules based on pharmacophore models.
  • To enable testing of 3D pharmacophore hypotheses against diverse ligand sets.

Main Methods:

  • Utilized the Stochastic Proximity Embedding (SPE) algorithm on an ensemble of molecules.

Related Experiment Videos

  • Incorporated distance terms to align pharmacophore points and their associated vectors across molecules.
  • Allowed pharmacophore points to be constrained by external binding site coordinates.
  • Applied postprocessing minimization of distance and energy functions for refinement.

    • Main Results:

    • Achieved simultaneous 3D structure generation and pharmacophore alignment.
    • Demonstrated efficient alignment of diverse ligands based on pharmacophore hypotheses.
    • Showcased the ability to test 3D pharmacophores using SPE with improved speed and accuracy.
    • Refined molecular structures and validated pharmacophore feasibility through postprocessing.

    Conclusions:

    • The SPE-based method offers a fast and effective approach for 3D molecular alignment and pharmacophore hypothesis testing.
    • This method facilitates the evaluation of 3D pharmacophores for drug discovery, starting from basic hypotheses.
    • The simultaneous generation and alignment process improves computational efficiency compared to existing techniques.