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Exploring topological indices and entropy measures of phenylacetone monooxygenase by using Python coding.

Rashad Ismail1, Rimsha Noreen2, Muhammad Farhan Hanif3

  • 1Department of Mathematics, Faculty of Science and Arts, Mahayl Assir, King Khalid University, Abha, 61913, Saudi Arabia.

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|February 28, 2025
PubMed
Summary

This study computes topological indices and Shannon entropy for the phenylacetone monooxygenase enzyme using Python. These calculations help predict the enzyme

Keywords:
Balaban indexForgotten indexPhenylacetone monooxygenase (PAMO)Python codeRedefined firstSecond and third zagreb indexZagreb type index

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Area of Science:

  • Computational chemistry and bioinformatics.
  • Enzyme structure-activity relationship studies.

Background:

  • Topological indices are crucial for assessing molecular physicochemical properties.
  • Shannon entropy offers insights into molecular graph structural properties.
  • Predicting chemical and biological compound properties relies on these indices in QSPR and QSAR studies.

Purpose of the Study:

  • To compute topological indices for the phenylacetone monooxygenase (PAMO) enzyme.
  • To calculate edge-weight-based Shannon entropy for PAMO.
  • To leverage Python for these computational analyses.

Main Methods:

  • Representing PAMO's molecular graph with atoms as nodes and bonds as weighted edges.
  • Utilizing Python programming for the computation of topological indices.
  • Applying Python to calculate edge-weight-based Shannon entropy.

Main Results:

  • Successfully computed various topological indices for PAMO.
  • Quantified the edge-weight-based Shannon entropy for PAMO.
  • Demonstrated the utility of Python in these complex calculations.

Conclusions:

  • The computed topological indices and Shannon entropy provide valuable structural information about PAMO.
  • These findings can aid in understanding PAMO's physicochemical characteristics.
  • The Python-based approach is effective for analyzing enzyme molecular structures.