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A box-counting-based algorithm for computing Shannon entropy in molecular dynamics simulations.

Luis Lorenzo1, Ricardo A Mosquera

  • 1Dpto. Química Física, Facultade de Ciencias, Universidade de Vigo, Lagoas-Marcosende s/n, 36200-Vigo, Galicia, Spain.

Journal of Computational Chemistry
|April 1, 2003
PubMed
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A new algorithm, Shannon Entropy Box Counting (SEBC), accurately calculates Shannon entropy for continuous functions and molecular dynamics simulations. It shows a linear correlation with experimental thermodynamic entropies, enabling reliable entropy estimations.

Area of Science:

  • Computational chemistry
  • Statistical mechanics
  • Information theory

Background:

  • Calculating Shannon entropy for continuous functions is challenging.
  • Molecular dynamics simulations offer insights into molecular behavior.

Purpose of the Study:

  • To develop and validate a novel algorithm for computing Shannon entropy.
  • To assess the utility of this algorithm in analyzing molecular dynamics data.
  • To establish a correlation between computed and experimental thermodynamic entropies.

Main Methods:

  • Developed the Shannon Entropy Box Counting (SEBC) algorithm.
  • Tested SEBC on known continuous distribution functions.
  • Applied SEBC to compute Shannon entropy of steric energy from molecular dynamics simulations of amino acids.

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Main Results:

  • SEBC accurately reproduced analytical and numerical integration results for Shannon entropy.
  • SEBC successfully computed Shannon entropies of amino acid steric energies.
  • A linear correlation was observed between computed and experimental thermodynamic entropies.

Conclusions:

  • SEBC is a reliable method for numerical computation of Shannon entropy.
  • Shannon entropy from molecular dynamics simulations can be empirically linked to thermodynamic entropies.
  • This approach facilitates straightforward and reliable calculations of thermodynamic entropies.