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Comparative molecular moment analysis (CoMMA): 3D-QSAR without molecular superposition

B D Silverman1, D E Platt

  • 1IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598, USA.

Journal of Medicinal Chemistry
|May 24, 1996
PubMed
Summary
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This study introduces Comparative Molecular Moment Analysis (CoMMA) for 3D-QSAR, using molecular moments to describe shape and charge. CoMMA successfully predicts molecular activity without superposition, highlighting the importance of quadrupolar moments.

Area of Science:

  • Computational Chemistry
  • Medicinal Chemistry
  • Molecular Modeling

Background:

  • 3D-QSAR methods analyze molecular shape and charge distributions for ligand-receptor binding.
  • Comparative Molecular Moment Analysis (CoMMA) uses mass and charge moments for similarity descriptors.
  • Defining reference frames is crucial for 3D-QSAR analysis.

Purpose of the Study:

  • To introduce and validate a novel 3D-QSAR approach using molecular moments.
  • To assess the utility of molecular electrostatic quadrupolar moments in 3D-QSAR.
  • To demonstrate CoMMA's ability to predict molecular activity without superposition.

Main Methods:

  • Utilized moments of molecular mass and charge distributions up to second order.
  • Defined Cartesian reference frames based on principal inertial and quadrupolar axes.

Related Experiment Videos

  • Employed partial least squares (PLS) cross-validation for activity prediction.
  • Introduced molecular electrostatic quadrupolar moments into 3D-QSAR analysis.

    • Main Results:

    • CoMMA descriptors effectively characterize molecular shape and charge relationships.
    • Descriptors involving quadrupolar moments were essential for significant predictive power.
    • Achieved significant cross-validated predictive r2 values.
    • Demonstrated that CoMMA eliminates the need for molecular superposition.

    Conclusions:

    • Molecular electrostatic quadrupolar moments are valuable descriptors in 3D-QSAR.
    • CoMMA provides a robust and efficient method for 3D-QSAR analysis.
    • The CoMMA approach enhances the prediction of molecular activity.