Evidence map›Paper›PMID 37975004›Full record

ReviewBiophysical reviews2023

Protein translational diffusion as a way to detect intermolecular interactions.

Yuriy F Zuev, Aleksandra M Kusova, Aleksandr E Sitnitsky

Abstract readReview
In one paragraph

Review in Biophysical reviews, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. In Situ Online Spectroscopy and Light Scattering Techniques.Advances in biochemical engineering/biotechnology · 2026
    Review
  2. 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

3 authors.

Yuriy F ZuevKazan Institute of Biochemistry and Biophysics, FRC Kazan Scientific Center of RAS, Lobachevsky St., 2/31, 420111 Kazan, Russia.ORCID 0000-0002-6715-2530
Aleksandra M KusovaKazan Institute of Biochemistry and Biophysics, FRC Kazan Scientific Center of RAS, Lobachevsky St., 2/31, 420111 Kazan, Russia.ORCID https://orcid.org/0000-0001-9006-4160
Aleksandr E SitnitskyKazan Institute of Biochemistry and Biophysics, FRC Kazan Scientific Center of RAS, Lobachevsky St., 2/31, 420111 Kazan, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this work, we analyze the information on the protein intermolecular interactions obtained from macromolecular diffusion. We have shown that the most hopeful results are given by our approach based on analysis of protein translational self-diffusion and collective diffusion obtained by dynamic light scattering and pulsed-field gradient NMR (PFG NMR) spectroscopy with the help of Vink's approach to analyze diffusion motion of particles by frictional formalism of non-equilibrium thermodynamics and the usage of the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory of colloid particles interactions in electrolyte solutions. Early we have shown that integration of Vink's theory with DLVO provides a reliable basis for uniform interpreting of PFG NMR and DLS experiments on concentration dependence of diffusion coefficients. Basic details of theoretical and mathematical procedures and a broad analysis of experimental attestation of proposed conception on proteins of various structural form, size, and shape are presented. In the present review, the main capabilities of our approach obtain the details of intermolecular interactions of proteins with different shapes, internal structures, and mass. The universality of Vink's approach is experimentally shown, which gives the appropriate description of experimental results for proteins of complicated structure and shape.

Indexed as

DLS and NMRProtein-protein interactionsTranslational diffusion

Identifiers

PMID37975004
PMCPMC10643801

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Registered trials

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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.