Evidence map›Paper›PMID 34110550›Full record

ArticleJournal of computer-aided molecular design2021

Hampering the early aggregation of PrP-E200K protein by charge-based inhibitors: a computational study.

Mariangela Agamennone, Loriano Storchi, Alessandro Marrone, Roberto Paciotti

Open access · hybridAbstract read
In one paragraph

Article in Journal of computer-aided molecular design, 2021. 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
0.3field-weighted citation impact, top 44% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  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

4 authors at 1 institution in 2 countries.

Mariangela AgamennoneDepartment of Pharmacy, University "G d'Annunzio" of Chieti-Pescara, Chieti, Italy.
Loriano StorchiDepartment of Pharmacy, University "G d'Annunzio" of Chieti-Pescara, Chieti, Italy.
Alessandro MarroneDepartment of Pharmacy, University "G d'Annunzio" of Chieti-Pescara, Chieti, Italy.
Roberto PaciottiDepartment of Pharmacy, University "G d'Annunzio" of Chieti-Pescara, Chieti, Italy. r.paciotti@unich.it.ORCID 0000-0001-5325-9452
University of Chieti-Pescara · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A multilayered computational workflow was designed to identify a druggable binding site on the surface of the E200K pathogenic mutant of the human prion protein, and to investigate the effect of the binding of small molecules in the inhibition of the early aggregation of this protein. At this purpose, we developed an efficient computational tool to scan the molecular interaction properties of a whole MD trajectory, thus leading to the characterization of plausible binding regions on the surface of PrP-E200K. These structural data were then employed to drive structure-based virtual screening and fragment-based approaches to the seeking of small molecular binders of the PrP-E200K. Six promising compounds were identified, and their binding stabilities were assessed by MD simulations. Therefore, analyses of the molecular electrostatic potential similarity between the bound complexes and unbound protein evidenced their potential activity as charged-based inhibitors of the PrP-E200K early aggregation.

Indexed as

Binding SitesHumansHydrophobic and Hydrophilic InteractionsLigandsMolecular Dynamics SimulationMutant ProteinsPrionsProtein BindingProtein ConformationStatic ElectricityStructure-Activity RelationshipLigandsMutant ProteinsPrionsAnti-prion drugsCharge-based inhibitorsMolecular dockingPrP-E200KVirtual screening

Identifiers

PMID34110550
PMCPMC8213589
OpenAlexW3168094351

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.