Evidence map›Paper›PMID 24900984›Full record

ArticleBioMed research international2014

In silico design of BACE1 inhibitor for Alzheimer's disease by traditional Chinese medicine.

Hung-Jin Huang, Cheng-Chun Lee, Calvin Yu-Chian Chen

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2014. 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
0.4field-weighted citation impact, top 35% 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, 9 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Hung-Jin HuangDepartment of Chinese Pharmaceutical Sciences and Chinese Medicine Resources, College of Pharmacy, China Medical University, Taichung 40402, Taiwan.
Cheng-Chun LeeSchool of Medicine, College of Medicine, China Medical University, Taichung 40402, Taiwan.
Calvin Yu-Chian ChenSchool of Medicine, College of Medicine, China Medical University, Taichung 40402, Taiwan ; Department of Biomedical Informatics, Asia University, Taichung 41354, Taiwan.
China Medical University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The β-site APP cleaving enzyme 1 (BACE1) is an important target for causing Alzheimer's disease (AD), due to the brain deposition peptide amyloid beta (Aβ) require cleavages of amyloid precursor protein (APP) by BACE1 and γ-secretase, but treatments of AD still have side effect in recent therapy. This study utilizes the world largest traditional Chinese medicine (TCM) database and database screening to provide potential BACE1 inhibited compound. Molecular dynamics (MD) simulation was carried out to observe the dynamics structure after ligand binding. We found that Triptofordin B1 has less toxicity than pyrimidine analogue, which has more potent binding affinity with BACE1. For trajectory analysis, all conformations are tending to be stable during 5000 ps simulation time. In dynamic protein validation, the residues of binding region are still stable after MD simulation. For snapshot comparison, we found that Triptofordin B1 could reduce the binding cavity; the results reveal that Triptofordin B1 could bind to BACE1 and better than control, which could be used as potential lead drug to design novel BACE1 inhibitor for AD therapy.

Indexed as

Alzheimer DiseaseAmyloid Precursor Protein SecretasesAspartic Acid EndopeptidasesBrainDatabases, PharmaceuticalHumansLigandsMedicine, Chinese TraditionalMolecular Dynamics SimulationSmall Molecule LibrariesAmyloid Precursor Protein SecretasesAspartic Acid EndopeptidasesBACE1 protein, humanLigandsSmall Molecule Libraries

Identifiers

PMID24900984
PMCPMC4034430
OpenAlexW2069850060

What OpenQuestion holds

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LicenceCC BY
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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.