Evidence map›Paper›PMID 40305350›Full record

ReviewBiomolecules2025

AFM for Studying the Functional Activity of Enzymes.

Irina A Ivanova, Anastasia A Valueva, Maria O Ershova, Tatiana O Pleshakova

Abstract readReview
In one paragraph

Review in Biomolecules, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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.

Irina A IvanovaInstitute of Biomedical Chemistry, Pogodinskaya Str., 10, 119121 Moscow, Russia.ORCID 0000-0002-2103-2998
Anastasia A ValuevaInstitute of Biomedical Chemistry, Pogodinskaya Str., 10, 119121 Moscow, Russia.
Maria O ErshovaInstitute of Biomedical Chemistry, Pogodinskaya Str., 10, 119121 Moscow, Russia.
Tatiana O PleshakovaInstitute of Biomedical Chemistry, Pogodinskaya Str., 10, 119121 Moscow, Russia.ORCID 0000-0003-3217-9095

Funding

Ministry of Science and Higher Education of the Russian Federation Agreement No. 075-15-2024-643
6 · The paper itself

Abstract

The conventional approach to investigating enzyme systems involves the simultaneous investigation of a large number of molecules and observing ensemble-averaged properties. However, modern science allows us to study the properties of single molecules and to obtain data on biochemical systems at a fundamentally new level, significantly expanding our understanding of the mechanisms of biochemical processes. Imaging of single biomolecules with high spatial and temporal resolution is among such modern research tools. To effectively image the individual steps or intermediates of biochemical reactions in single-molecule experiments, we need to develop a methodology for data acquisition and analysis. Its development will make it possible to solve the problem of separating the static and dynamic disorder present in the parameters identified by traditional proteomic methods. Such a methodology may be based on AFM imaging, the high-resolution microscopic visualization of enzymes. This review focuses on this direction of research, including the relevant methodological and practical solutions related to the potential of developing a single-molecule approach to the study of enzyme systems using AFM-based techniques. We focus on the results of enzyme reaction studies, as there are still few such studies, as opposed to the AFM studies of the mechanical properties of individual enzyme molecules.

Indexed as

EnzymesMicroscopy, Atomic ForceHumansSingle Molecule ImagingEnzymesAFM imagingatomic force microscopyprotein functionprotein structuresingle-molecule enzymology

Identifiers

PMID40305350
PMCPMC12025057

What Socratic holds

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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 Socratic graph.