Evidence map›Paper›PMID 24671215›Full record

ArticlePloS one2014

Molecular topology as novel strategy for discovery of drugs with aβ lowering and anti-aggregation dual activities for Alzheimer's disease.

Jun Wang, David Land, Kenjiro Ono, Jorge Galvez, Wei Zhao, Prashant Vempati, John W Steele, Alice Cheng, Masahito Yamada, Samara Levine and 2 more

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Molecular Topology for the Search of New Anti-MRSA Compounds.International journal of molecular sciences · 2021
    Article
  3. Article
  4. Article
  5. 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

12 authors.

Jun WangDepartment of Neurology, Mount Sinai School of Medicine, New York, New York, United States of America; Geriatric Research, Education and Clinical Center, James J. Peters Veterans Affairs Medical Center, Bronx, New York New York, United States of America.
David LandMedisyn Technologies, Inc. Minnetonka, Minnesota, United States of America.
Kenjiro OnoDepartment of Neurology and Neurobiology of Aging, Kanazawa University, Kanazawa, Japan.
Jorge GalvezMolecular Topology & Drug Design Unit, University of Valencia, Valencia, Spain.
Wei ZhaoDepartment of Neurology, Mount Sinai School of Medicine, New York, New York, United States of America.
Prashant VempatiDepartment of Neurology, Mount Sinai School of Medicine, New York, New York, United States of America.
John W SteeleDepartment of Neurology, Mount Sinai School of Medicine, New York, New York, United States of America.
Alice ChengDepartment of Neurology, Mount Sinai School of Medicine, New York, New York, United States of America.
Masahito YamadaDepartment of Neurology and Neurobiology of Aging, Kanazawa University, Kanazawa, Japan.
Samara LevineDepartment of Neurology, Mount Sinai School of Medicine, New York, New York, United States of America.
Paolo MazzolaDepartment of Neurology, Mount Sinai School of Medicine, New York, New York, United States of America.
Giulio M PasinettiDepartment of Neurology, Mount Sinai School of Medicine, New York, New York, United States of America; Geriatric Research, Education and Clinical Center, James J. Peters Veterans Affairs Medical Center, Bronx, New York New York, United States of America.

Funding

UCSD/SDSU IRACDAK12GM068524 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI TREJO, JOANN · 2003 to 2025
$24.4M
NIGMS NIH HHS K12 GM068524
6 · The paper itself

Abstract

background and purposeIn this study, we demonstrate the use of Molecular topology (MT) in an Alzheimer's disease (AD) drug discovery program. MT uses and expands upon the principles governing the molecular connectivity theory of numerically characterizing molecular structures, in the present case, active anti-AD drugs/agents, using topological descriptors to build models. Topological characterization has been shown to embody sufficient molecular information to provide strong correlation to therapeutic efficacy. EXPERIMENTAL APPROACH: We used MT to include multiple bioactive properties that allows for the identification of multi-functional single agent compounds, in this case, the dual functions of β-amyloid (Aβ) -lowering and anti-oligomerization. Using this technology, we identified and designed novel compounds in chemical classes unrelated to current anti-AD agents that exert dual Aβ lowering and anti-Aβ oligomerization activities in animal models of AD. AD is a multifaceted disease with different pathological features. CONCLUSION AND IMPLICATIONS: Our study, for the first time, demonstrated that MT can provide novel strategy for discovering drugs with Aβ lowering and anti-aggregation dual activities for AD.

Indexed as

Drug DiscoveryProtein AggregatesAlzheimer DiseaseAmyloid beta-PeptidesAnimalsDatabases as TopicDisease Models, AnimalDrug Evaluation, PreclinicalFeasibility StudiesFemaleHumansMice, TransgenicModels, MolecularProtein MultimerizationTreatment OutcomeAmyloid beta-PeptidesProtein Aggregates

Identifiers

PMID24671215
PMCPMC3966818

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.