Evidence map›Paper›PMID 37915170›Full record

ArticleBiophysical journal2023

Enzymatic metabolons dramatically enhance metabolic fluxes of low-efficiency biochemical reactions.

Srivastav Ranganathan, Junlang Liu, Eugene Shakhnovich

Open access · bronzeAbstract read
In one paragraph

Article in Biophysical journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.4field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
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  5. Control of encounter kinetics by chemically active droplets.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Srivastav RanganathanDepartment of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts.
Junlang LiuDepartment of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts.
Eugene ShakhnovichDepartment of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts. Electronic address: shakhnovich@chemistry.harvard.edu.
Harvard University · US

Funding

Biophysical foundations of evolutionary dynamicsR35GM139571 · NIGMS · HARVARD UNIVERSITY · PI SHAKHNOVICH, EUGENE I · 2021 to 2025
$3.9M
Structure and Interactions of Conformational Intermediates in gamma-D Crystallin Aggregation, and Their Targeting for Cataract PreventionR01EY030444 · NEI · HARVARD UNIVERSITY · PI SHAKHNOVICH, EUGENE I · 2020 to 2024
$2.1M
NEI NIH HHS R01 EY030444NIGMS NIH HHS R35 GM139571
6 · The paper itself

Abstract

In this work, we investigate how spatial proximity of enzymes belonging to the same pathway (metabolon) affects metabolic flux. Using off-lattice Langevin dynamics simulations in tandem with a stochastic reaction-diffusion protocol and a semi-analytical reaction-diffusion model, we systematically explored how strength of protein-protein interactions, catalytic efficiency, and protein-ligand interactions affect metabolic flux through the metabolon. Formation of a metabolon leads to a greater speedup for longer pathways and especially for reaction-limited enzymes, whereas, for fully optimized diffusion-limited enzymes, the effect is negligible. Notably, specific cluster architectures are not a prerequisite for enhancing reaction flux. Simulations uncover the crucial role of optimal nonspecific protein-ligand interactions in enhancing catalytic efficiency of a metabolon. Our theory implies, and bioinformatics analysis confirms, that longer catalytic pathways are enriched in less optimal enzymes, whereas most diffusion-limited enzymes populate shorter pathways. Our findings point toward a plausible evolutionary strategy where enzymes compensate for less-than-optimal efficiency by increasing their local concentration in the clustered state.

Indexed as

LigandsCatalysisLigands

Identifiers

PMID37915170
PMCPMC10719048
OpenAlexW4388215321

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.