Theoretical Modeling Expressions for Networked Enzymatic Signal Processing Steps as Logic Gates Optimized by Filtering

TL;DR

This paper develops theoretical models for enzyme-based signal processing networks, incorporating biochemical filtering, to enable simplified analysis and understanding of complex enzymatic cascades used in bioinformatics.

Contribution

It introduces a novel modeling framework that captures biochemical filtering effects in enzymatic networks, facilitating analysis of their signal processing capabilities.

Findings

Derived simple, few-parameter expressions for enzymatic cascades.

Explained features of enzymatic processes as network components.

Validated models against previous experimental observations.

Abstract

We describe modeling approaches to a "network" of connected enzyme-catalyzed reactions, with added (bio)chemical processes that introduce biochemical filtering steps into the functioning of such a biocatalytic cascade. Theoretical expressions are derived that allow simple, few-parameter modeling of processes concatenated in such cascades, both with and without filtering. The modeling approach captures and explains features identified in earlier studies of enzymatic processes considered as potential "network components" for multi-step information/signal processing systems.