Evidence map›Paper›PMID 35982231›Full record

ArticleCommunications biology2022

A thermodynamic investigation of amyloid precursor protein processing by human γ-secretase.

Xiaoli Lu, Jing Huang

Open access · goldAbstract read
In one paragraph

Article in Communications biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

8 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Molecular mechanisms of NaBiophysical journal · 2024
    Article
  5. Review
  6. Review
  7. Article
  8. 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

2 authors at 1 institution in 1 country.

Xiaoli LuCollege of Life Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China.
Jing HuangKey Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, 18 Shilongshan Road, Hangzhou, 310024, Zhejiang, China. huangjing@westlake.edu.cn.ORCID 0000-0001-9639-2907
Westlake University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human γ-secretase cleaves the transmembrane domains (TMDs) of amyloid precursor protein (APP) into pathologically relevant amyloid-β peptides (Aβs). The detailed mechanisms of the unique endoproteolytic cleavage by the presenilin 1 domain (PS1) of γ-secretase are still poorly understood. Herein, we provide thermodynamic insights into how the α-helical APP TMD is processed by γ-secretase and elucidate the specificity of Aβ48/Aβ49 cleavage using unbiased molecular dynamics and bias-exchange metadynamics simulations. The thermodynamic data show that the unwinding of APP TMD is driven by water hydration in the intracellular pocket of PS1, and the scissile bond T32-L33 or L33-V34 of the APP TMD can slide down and up to interact with D257/D385 to achieve endoproteolysis. In the wild-type system, the L33-V34 scissile bond is more easily hijacked by D257/D385 than T32-L33, resulting in higher Aβ49 cleavage, while the T32N mutation on the APP TMD decreases the energy barrier of the sliding of the scissile bonds and increases the hydrogen bond occupancy for Aβ48 cleavage. In summary, the thermodynamic analysis elucidates possible mechanisms of APP TMD processing by PS1, which might facilitate rational drug design targeting γ-secretase.

Indexed as

Amyloid beta-Protein PrecursorAmyloid Precursor Protein SecretasesAmyloid beta-PeptidesHumansMutationThermodynamicsAmyloid beta-PeptidesAmyloid beta-Protein PrecursorAmyloid Precursor Protein Secretases

Identifiers

PMID35982231
PMCPMC9388646
OpenAlexW4292212889

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.