Metabolic graphs, LIFE method and the modeling of drug action on Mycobacterium tuberculosis

TL;DR

This paper introduces metabolic graphs and extends the LIFE methodology to model drug effects on metabolism, specifically applied to Mycobacterium tuberculosis, providing a framework for simulating drug interactions and metabolic responses.

Contribution

It presents a novel framework combining metabolic graphs with LIFE dynamics to analyze drug actions on complex metabolic networks, including inhibitory and enhancing interactions.

Findings

Extended LIFE dynamics to metabolic graphs with complex interactions

Analyzed conditions for equilibrium existence and uniqueness

Simulated drug effects on Mycobacterium tuberculosis

Abstract

This paper serves as a framework for designing advanced models for drug action on metabolism. Drug treatment may affect metabolism by either enhancing or inhibiting metabolic reactions comprising a metabolic network. We introduce the concept of \textit{metabolic graphs}, a generalization of hypergraphs having specialized features common to metabolic networks. Linear-in-flux-expression (briefly LIFE) is a methodology for analyzing metabolic networks and simulating virtual patients. We extend LIFE dynamics to be compatible with metabolic graphs, including the more complex interactions of enhancer and inhibitor molecules that affect biochemical reactions. We discuss results considering network structure required for existence and uniqueness of equilibria on metabolic graphs and show simulations of drug action on \textit{Mycobacterium tuberculosis} (briefly MTB)