Automaton of molecular perceptions in biochemical reactions

TL;DR

This paper introduces an agent-based automaton model for molecular perceptions in biochemical reactions, emphasizing local interactions and environmental influences to improve upon traditional kinetic models.

Contribution

It presents a novel automaton framework for modeling molecular perceptions and environmental effects in biochemical reactions, integrating graph-based systems with agent-based approaches.

Findings

Provides a new perspective on enzyme regulation through environmental influence

Overcomes limitations of classical kinetic models by incorporating local interactions

Offers a theoretical foundation for future computational modeling of biochemical processes

Abstract

Local interactions among biomolecules, and the role played by their environment, have gained increasing attention in modelling biochemical reactions. By defining the automaton of molecular perceptions, we explore an agent-based representation of the behaviour of biomolecules in living cells. Our approach considers the capability of a molecule to perceive its surroundings a key property of bimolecular interactions, which we investigate from a theoretical perspective. Graph-based reaction systems are then leveraged to abstract enzyme regulation as a result of the influence exerted by the environment on a catalysed reaction. By combining these methods, we aim at overcoming some limitations of current kinetic models, which do not take into account local molecular interactions and the way they are affected by the reaction environment.