Evidence map›Paper›PMID 40763921›Full record

ReviewBiochemistry2025

Considering Metabolic Context in Enzyme Evolution and Design.

Dhiraj Dokwal, Philip M Brown, Karolina Filipowska, Kimberly A Reynolds

Abstract readReview
In one paragraph

Review in Biochemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Dhiraj DokwalGreen Center for Systems Biology─Lyda Hill Department of Bioinformatics, The University of Texas Southwestern Medical Center, Dallas, Texas 75230, United States.ORCID 0000-0003-2202-0881
Philip M BrownGreen Center for Systems Biology─Lyda Hill Department of Bioinformatics, The University of Texas Southwestern Medical Center, Dallas, Texas 75230, United States.
Karolina FilipowskaGreen Center for Systems Biology─Lyda Hill Department of Bioinformatics, The University of Texas Southwestern Medical Center, Dallas, Texas 75230, United States.
Kimberly A ReynoldsGreen Center for Systems Biology─Lyda Hill Department of Bioinformatics, The University of Texas Southwestern Medical Center, Dallas, Texas 75230, United States.ORCID 0000-0003-4805-0317

Funding

Mapping Genetic Variation in Enzyme Velocity to Growth Rate PhenotypeR01GM136842 · NIGMS · UT SOUTHWESTERN MEDICAL CENTER · PI Kimberly Ann Reynolds · 2020 to 2026
$2.3M
NIGMS NIH HHS R01 GM136842
6 · The paper itself

Abstract

Enzymes are often treated as isolated molecular entities when measuring their biochemical activity and designing synthetic sequences. Yet inside the cell, enzymes interact through shared metabolite pools, physical binding, and regulatory feedback. This coordination is necessary for responsive, cohesive metabolic behavior. Moreover, these interactions place constraints on enzyme activity, specificity, abundance, and ultimately sequence. Defining these interaction-mediated constraints is important to understand metabolic evolution and to design synthetic systems. For example, the influence of the cellular and environmental milieu becomes evident when a heterologous enzyme from one species fails to function properly upon transfer to a new host. In this review we consider how cell context shapes enzyme evolution, and in turn, how variations in enzyme biochemistry, biophysics, and abundance impact cell fitness.

Indexed as

EnzymesEvolution, MolecularHumansEnzymesCRISPRdeep mutational scanningdihydrofolate reductaseEscherichia coliNADPH

Identifiers

PMID40763921
PMCPMC12369633

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.