Decoding informational entropy of fatty acid and phospholipid vesicle via ordering combinatorial output of hydrazones

Abstract

Leveraging information entropy to quantitatively measure the organizational diversity and complexity of different chemical systems is a compelling need for next-generation supramolecular and systems chemistry. It can also be a strategy for digitalizing and bottom-up development of life-like complex systems following the probable origin of life scenarios. According to the lipid world hypothesis, lipid molecules appear first to facilitate compartmentalization, catalysis, information processing, etc. It is envisaged that fatty acid-based vesicles are more primitive than phospholipid vesicles. Herein, we decode the difference in information storage capability of a fatty acid (oleic acid, (OA)) and phospholipid (1,2-Dioleoyl-sn-glycero-3-phosphocholine (DOPC)) vesicle by measuring vesicle-templated formation of nine different hydrazones through permutations and hierarchical ordering of combinatorial matrices involving three aldehydes and three hydrazines by determining Shannon entropy and Gini coefficient at systems level. It signifies a higher diversity and lower selectivity towards successful chemical reactions in OA vesicle, whereas DOPC vesicle is more selective and less diverse. Exploiting information theory in combinatorial supramolecular synthesis and unraveling information capacity relevant to cell membrane evolution will be important in understanding the information dynamicity of different transient and self-propagated synthetic and natural assembly processes with time.

Supplementary files

Article information

Article type
Edge Article
Submitted
14 Jun 2025
Accepted
21 Aug 2025
First published
22 Aug 2025
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY-NC license

Chem. Sci., 2025, Accepted Manuscript

Decoding informational entropy of fatty acid and phospholipid vesicle via ordering combinatorial output of hydrazones

R. Yadav, N. Adikessavane, R. R. Mahato and S. Maiti, Chem. Sci., 2025, Accepted Manuscript , DOI: 10.1039/D5SC04365D

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