Evidence map›Paper›PMID 38317814›Full record

ArticleReports of biochemistry & molecular biology2023

γ-Secretase Inhibitors Selected by Molecular Docking, to Develop a New Drug Against Alzheimer's Disease.

Carlos Humberto Trasviña-Arenas, Luis Alejandro Ayala Medina, José Luis Vique-Sánchez

Abstract read
In one paragraph

Article in Reports of biochemistry & molecular biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Unveiling Neuroprotective Potential in Tempeh Peptide Extracts byReports of biochemistry & molecular biology · 2025
    Article
  3. Review
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.

Carlos Humberto Trasviña-ArenasResearch Center on Aging, Center for Research and Advanced Studies of the National Polytechnic Institute (CINVESTAV), Calzada de los Tenorios No. 235, 14330, Mexico City, Mexico.
Luis Alejandro Ayala MedinaSchool of Medicine Campus Mexicali, Autonomous University of Baja California, Mexicali, 21000, BC, México.
José Luis Vique-SánchezSchool of Medicine Campus Mexicali, Autonomous University of Baja California, Mexicali, 21000, BC, México.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Alzheimer´s disease (AD) is one of the most common forms of dementia, is characterized by memory loss and cognitive impairment that affects more than 30 million people worldwide. The pathogenesis of Alzheimer's disease is primary driven by brain accumulation of the amyloid β peptide generated from the amyloid-β precursor protein (APP) via cleavages by β- and γ-secretase. In this study, we propose an approach by molecular docking to select compounds as γ-secretase inhibitors for decreasing the APP generation. Methods: We selected potential γ-secretase inhibitors by molecular docking in the potential site between Asp257, Lue268, Asp385, Ile387, Phe388, and Leu432 amino acids in presenilin-1 (PS-1), using a chemical library of over 500,000 compounds. Results: Eight compounds (AZ1 - AZ8) were selected by molecular docking to develop γ-secretase inhibitors for decreasing the APP generation. Conclusions: AZ1 - AZ8 compounds could be interacting in the potential site between Asp257, Lue268, Asp385, Ile387, Phe388, and Leu432 amino acids in PS-1. These compounds could specifically interact in the binding pocket in PS-1 to prevent/decrease the APP generation, to develop a new drug against Alzheimer's disease.

Indexed as

Alzheimer's diseaseAmyloid Beta-Protein PrecursorAmyloid Precursor Protein SecretasesMolecular Docking SimulationPresenilin-1

Identifiers

PMID38317814
PMCPMC10838598

What Socratic holds

Textmetadata
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 Socratic graph.