Evidence map›Paper›PMID 33738079›Full record

ArticleComputational and structural biotechnology journal2021

Bioinformatic analysis of subfamily-specific regions in 3D-structures of homologs to study functional diversity and conformational plasticity in protein superfamilies.

Daria Timonina, Yana Sharapova, Vytas Švedas, Dmitry Suplatov

Open access · goldAbstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

6 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
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  3. Beyond sequence: Structure-based machine learning.Computational and structural biotechnology journal · 2023
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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

4 authors at 1 institution in 1 country.

Daria TimoninaLomonosov Moscow State University, Faculty of Bioengineering and Bioinformatics, Lenin Hills 1-73, Moscow 119234, Russia.
Yana SharapovaLomonosov Moscow State University, Faculty of Bioengineering and Bioinformatics, Lenin Hills 1-73, Moscow 119234, Russia.
Vytas ŠvedasLomonosov Moscow State University, Faculty of Bioengineering and Bioinformatics, Lenin Hills 1-73, Moscow 119234, Russia.
Dmitry SuplatovLomonosov Moscow State University, Belozersky Institute of Physicochemical Biology, Lenin Hills 1-73, Moscow 119234, Russia.
Lomonosov Moscow State University · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Local 3D-structural differences in homologous proteins contribute to functional diversity observed in a superfamily, but so far received little attention as bioinformatic analysis was usually carried out at the level of amino acid sequences. We have developed Zebra3D - the first-of-its-kind bioinformatic software for systematic analysis of 3D-alignments of protein families using machine learning. The new tool identifies subfamily-specific regions (SSRs) - patterns of local 3D-structure (i.e. single residues, loops, or secondary structure fragments) that are spatially equivalent within families/subfamilies, but are different among them, and thus can be associated with functional diversity and function-related conformational plasticity. Bioinformatic analysis of protein superfamilies by Zebra3D can be used to study 3D-determinants of catalytic activity and specific accommodation of ligands, help to prepare focused libraries for directed evolution or assist development of chimeric enzymes with novel properties by exchange of equivalent regions between homologs, and to characterize plasticity in binding sites. A companion Mustguseal web-server is available to automatically construct a 3D-alignment of functionally diverse proteins, thus reducing the minimal input required to operate Zebra3D to a single PDB code. The Zebra3D + Mustguseal combined approach provides the opportunity to systematically explore the value of SSRs in superfamilies and to use this information for protein design and drug discovery. The software is available open-access at https://biokinet.belozersky.msu.ru/Zebra3D.

Indexed as

3D-structure analysisDrug discovery(H)DBSCAN, (Hierarchical) Density-Based Spatial Clustering of Applications with NoiseMachine learningOPTICS, Ordering Points to Identify the Clustering StructureProtein designProtein superfamiliesRMSD, Root Mean Square DeviationSDR/SDP, Specificity-Determining Residue/PositionSpecificity-determining positionsSSP, Subfamily-Specific PositionSSR, Subfamily-Specific RegionsStructure-function relationship

Identifiers

PMID33738079
PMCPMC7933735
OpenAlexW3132373268

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.