Rethinking Robust Adaptation: Characterization of Structural Mechanisms for Biochemical Network Robustness through Topological Invariants DOI Creative Commons
Yuji Hirono, Ankit Gupta, Mustafa Khammash

et al.

PRX Life, Journal Year: 2025, Volume and Issue: 3(1)

Published: March 20, 2025

Biological systems rely on robust perfect adaptation (RPA) to maintain stability despite external disturbances, a property critical for their survival. In biochemical networks, achieving RPA without fine-tuning parameters presents significant challenge due complex reaction dynamics and nonlinear interactions. This study introduces framework characterizing mechanisms in deterministic chemical utilizing topological invariants systematically identify all structural configurations that enable robustness. We establish each corresponds specific subnetwork with unique features, which we term “labeled buffering structures.” correspondence allows us map enumerate such properties by analyzing network topology alone, independent of kinetic details. further integral feedback controllers associated mechanism, demonstrating alignment the Internal Model Principle control theory. Our findings offer complete characterization kinetics-independent robustness paving way rational design synthetic providing insights into fundamental architectures resilience biological systems. work lays groundwork understanding as universal principle dynamical systems, propose “Robust Adaptation is Topological” (RAT) principle. Published American Physical Society 2025

Language: Английский

Rethinking Robust Adaptation: Characterization of Structural Mechanisms for Biochemical Network Robustness through Topological Invariants DOI Creative Commons
Yuji Hirono, Ankit Gupta, Mustafa Khammash

et al.

PRX Life, Journal Year: 2025, Volume and Issue: 3(1)

Published: March 20, 2025

Biological systems rely on robust perfect adaptation (RPA) to maintain stability despite external disturbances, a property critical for their survival. In biochemical networks, achieving RPA without fine-tuning parameters presents significant challenge due complex reaction dynamics and nonlinear interactions. This study introduces framework characterizing mechanisms in deterministic chemical utilizing topological invariants systematically identify all structural configurations that enable robustness. We establish each corresponds specific subnetwork with unique features, which we term “labeled buffering structures.” correspondence allows us map enumerate such properties by analyzing network topology alone, independent of kinetic details. further integral feedback controllers associated mechanism, demonstrating alignment the Internal Model Principle control theory. Our findings offer complete characterization kinetics-independent robustness paving way rational design synthetic providing insights into fundamental architectures resilience biological systems. work lays groundwork understanding as universal principle dynamical systems, propose “Robust Adaptation is Topological” (RAT) principle. Published American Physical Society 2025

Language: Английский

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