Catalytic reaction dynamics in inhomogeneous networks

Area of Science:

• Biochemistry
• Complex Systems
• Network Science

Background:

• Biochemical reactions in cells are modeled as catalytic reaction networks (CRNs).
• Homogeneous random-graph CRNs exhibit self-organized criticality (SOC) with power-law avalanche-size distributions.
• Real-world metabolic networks possess significant structural inhomogeneities.

Purpose of the Study:

• To investigate the impact of structural and functional inhomogeneities on the universality class of SOC in CRNs.
• To determine how features of real-world metabolic networks influence catalytic reaction dynamics.

Main Methods:

• Numerical simulations of CRNs with varying degrees of structural inhomogeneity (scale-free, community structures, degree correlations).
• Analysis of CRNs with inhomogeneous catalytic functionality, varying the distribution of catalyzed reaction paths per species.
• Comparison of avalanche-size distributions to assess changes in the SOC universality class.

Main Results:

• SOC universality class remains robust against structural inhomogeneities like scale-free properties, community structures, and degree correlations.
• Inhomogeneous catalytic functionality significantly alters the SOC universality class.
• The degree of inhomogeneity in catalytic functionality, specifically the distribution of reaction paths per species, dictates the SOC universality class.

Conclusions:

• Structural complexity in metabolic networks does not disrupt the fundamental self-organized criticality dynamics.
• Catalytic functionality is a critical factor determining the SOC behavior in complex biochemical networks.
• Understanding catalytic functionality distribution is key to predicting reaction dynamics in biological systems.