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Efficient algorithm for expanding theoretical electron densities in canterakis-zernike functions.

Gabriel A Urquiza-Carvalho1, Gerd B Rocha1, Rafael López2

  • 1Departamento de Química, Universidade Federal da Paraíba, João Pessoa, Brazil.

Journal of Computational Chemistry
|October 14, 2018
PubMed
Summary

This study introduces an efficient algorithm for calculating molecular electron density moments and fingerprint indices. The method optimizes computation for various molecular structures, improving efficiency in computational chemistry.

Keywords:
Canterakis-Zernike momentselectron density expansionmolecular fingerprintsmolecular pattern recognitionquantum molecular similarity

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Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • Molecular Modeling

Background:

  • Molecular electron densities are crucial for understanding chemical properties.
  • Calculating these densities and derived descriptors can be computationally intensive.
  • Existing methods may lack efficiency for diverse computational frameworks.

Purpose of the Study:

  • To develop and report an efficient algorithm for computing Canterakis-Zernike moments.
  • To enable the derivation of rotationally invariant fingerprint indices from these moments.
  • To provide a versatile tool applicable to various computational chemistry contexts.

Main Methods:

  • The algorithm utilizes a one-center expansion of electron density using real regular spherical harmonics.
  • Translation techniques are employed to facilitate moment computation via single 1D numerical integration.
  • The method is designed for densities expressed using Gaussian- or Slater-type functions within the LCAO framework.

Main Results:

  • Demonstrated efficient computation of Canterakis-Zernike moments for molecular electron densities.
  • Successfully derived rotationally invariant fingerprint indices.
  • Identified radial factor computation as the primary computational bottleneck.

Conclusions:

  • The reported algorithm offers an efficient approach for calculating molecular descriptors.
  • It is applicable to a wide range of molecular densities from standard computational packages.
  • The method enhances the utility of electron density-based molecular characterization.