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Elucidating the link between binding statistics and Shannon information in biological networks
Kinshuk Banerjee1, Biswajit Das2
1Department of Chemistry, Acharya Jagadish Chandra Bose College, 1/1B A. J. C. Bose Road, Kolkata 700 020, India.
The Journal of Chemical Physics
|September 25, 2024
Summary
This study links biological network information content to ligand binding statistics. It reveals how Shannon information quantifies binding characteristics and cooperativity in biological systems.
Area of Science:
- Biophysics
- Systems Biology
- Information Theory
Background:
- Biological networks regulate cellular processes through ligand binding.
- Understanding the link between network states and binding statistics is crucial for deciphering information transmission.
Purpose of the Study:
- To investigate the relationship between the information content of biological network states and experimentally measurable binding statistics.
- To quantify information transmission in cooperative ligand binding networks.
Main Methods:
- Utilized the chemical master equation approach to model fundamental cooperative ligand binding networks.
- Employed the differential information index, based on Shannon information, to analyze binding characteristics.
- Examined network states adjacent in time and in both space and time.
Main Results:
- The differential information index shows a linear relationship with logarithmic ligand concentration, with the system size as the slope.
- Shannon information variations correlate with average binding number and variance.
- The Hill slope, a measure of cooperativity, is derived from the logarithmic sensitivity of the information index's slope.
Conclusions:
- Shannon information provides a framework to link microscopic binding events to macroscopic network behavior.
- The study establishes a quantitative connection between information theory and biophysical binding measurements.
- This approach offers insights into the regulatory mechanisms of biological networks.
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