Evidence map›Paper›PMID 35004845›Full record

ReviewFrontiers in molecular biosciences2021

Recent Developments in Data-Assisted Modeling of Flexible Proteins.

Cezary Czaplewski, Zhou Gong, Emilia A Lubecka, Kai Xue, Chun Tang, Adam Liwo

Abstract readReview
In one paragraph

Review in Frontiers in molecular biosciences, 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
–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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Intrinsically Disordered Proteins: An Overview.International journal of molecular sciences · 2022
    Review
  5. Article
  6. 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

6 authors.

Cezary CzaplewskiFaculty of Chemistry, University of Gdańsk, Gdańsk, Poland.
Zhou GongInnovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, China.
Emilia A LubeckaFaculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Gdańsk, Poland.
Kai XuePKU-Tsinghua Center for Life Sciences, Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, China.
Chun TangPKU-Tsinghua Center for Life Sciences, Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, China.
Adam LiwoFaculty of Chemistry, University of Gdańsk, Gdańsk, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many proteins can fold into well-defined conformations. However, intrinsically-disordered proteins (IDPs) do not possess a defined structure. Moreover, folded multi-domain proteins often digress into alternative conformations. Collectively, the conformational dynamics enables these proteins to fulfill specific functions. Thus, most experimental observables are averaged over the conformations that constitute an ensemble. In this article, we review the recent developments in the concept and methods for the determination of the dynamic structures of flexible peptides and proteins. In particular, we describe ways to extract information from nuclear magnetic resonance small-angle X-ray scattering (SAXS), and chemical cross-linking coupled with mass spectroscopy (XL-MS) measurements. All these techniques can be used to obtain ensemble-averaged restraints or to re-weight the simulated conformational ensembles.

Indexed as

chemical cross-linking coupled with mass spectroscopycoarse grainingconformational ensemblesdata-assisted modelingmolecular dynamicsnuclear magnetic resonanceproteinssmall-angle X-ray scattering

Identifiers

PMID35004845
PMCPMC8740120

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.