# Virtual Cell and Metabolic Control Analysis: Control Coefficients for Glycolytic Flux Are Highly Dependent on the Subsystem Selected for Analysis

**Authors:** Michael V. Martinov, Fazoil I. Ataullakhanov, Eugene S. Protasov, Victor M. Vitvitsky

PMC · DOI: 10.3390/life16030414 · Life · 2026-03-04

## TL;DR

This study shows that the control coefficients of enzymes in glycolysis change significantly depending on the subsystem analyzed, especially when other processes like ATPase activity are included.

## Contribution

The study reveals that metabolic control analysis results are highly sensitive to the subsystem selected and the presence of allosteric regulation.

## Key findings

- Control coefficients for glycolytic enzymes vary greatly across different subsystems.
- Adding ATPase to the subsystem reduces the control coefficients of hexokinase and phosphofructokinase.
- Disabling PFK's allosteric regulation alters control coefficients when ATPase is included.

## Abstract

The metabolic control analysis (MCA) was applied to several subsystems selected from the model of human erythrocyte energy metabolism. These subsystems represent varying degrees of simplification of energy metabolism, from the simplest subsystem of the first three glycolytic reactions that determine the steady-state rate of glycolysis, to an expanded subsystem that includes all glycolytic reactions plus passive and active ion transport across the cell membrane. The control coefficients of enzyme activities for the rate of glycolysis are found to be very different in different subsystems. However, no specific trend is observed in changes in control coefficients as the subsystem becomes more complex. Thus, in subsystems containing only glycolysis, the control coefficients of hexokinase (HK) and phosphofructokinase (PFK) together amount to 0.99. When ATPases are added, this value decreases to 0.18 and below, and the maximum control coefficient goes to ATPase (0.82–1.00). It would seem that there is a natural decrease in the contribution of HK and PFK to the regulation of the rate of glycolysis as the dimension of the system increases. However, disabling the allosteric regulation of PFK by AMP completely changes the picture. In a subsystem containing only glycolysis, disabling this regulation does not affect the control coefficients. After adding ATPase to such a subsystem, the HK and PFK control coefficients increase, and the control coefficient of ATPase takes on a negative value. Thus, we found that in extended subsystems involving glycolysis and ATPase or transmembrane ion transport, information on the initial regulation of glycolysis may not be revealed in the MCA results. It appears that the MCA alone cannot reveal regulatory mechanisms of metabolic systems in the presence of strong allosteric and feedback regulation.

## Linked entities

- **Proteins:** HK1 (hexokinase 1), DNAH8 (dynein axonemal heavy chain 8)
- **Species:** Homo sapiens (taxon 9606)

## Full-text entities

- **Genes:** HK1 (hexokinase 1) [NCBI Gene 3098] {aka CNSHA5, HK, HK1-ta, HK1-tb, HK1-tc, HKD}, DNAH8 (dynein axonemal heavy chain 8) [NCBI Gene 1769] {aka ATPase, SPGF46, hdhc9}
- **Chemicals:** ion (MESH:D007477), AMP (MESH:D000249)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

35 references — full list in the complete paper: https://tomesphere.com/paper/PMC13027950/full.md

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Source: https://tomesphere.com/paper/PMC13027950