Cited by 103Computational Drug Discovery MethodsCholinesterase and Neurodegenerative DiseasesAlzheimer's disease research and treatments

In silico repurposing of antipsychotic drugs for Alzheimer’s disease

Open access
Kumar, Shivani, Chowdhury, Suman, Kumar, Suresh·2017·BMC Neuroscience

Abstract

BACKGROUND: Alzheimer's disease (AD) is the most prevalent form of dementia and represents one of the highest unmet requirements in medicine today. There is shortage of novel molecules entering into market because of poor pharmacokinetic properties and safety issues. Drug repurposing offers an opportunity to reinvigorate the slowing drug discovery process by finding new uses for existing drugs. The major advantage of the drug repurposing approach is that the safety issues are already investigated in the clinical trials and the drugs are commercially available in the marketplace. As this approach provides an effective solution to hasten the process of providing new alternative drugs for AD, the current study shows the molecular interaction of already known antipsychotic drugs with the different protein targets implicated in AD using in silico studies. RESULT: A computational method based on ligand-protein interaction was adopted in present study to explore potential antipsychotic drugs for the treatment of AD. The screening of approximately 150 antipsychotic drugs was performed on five major protein targets (AChE, BuChE, BACE 1, MAO and NMDA) by molecular docking. In this study, for each protein target, the best drug was identified on the basis of dock score and glide energy. The top hits were then compared with the already known inhibitor of the respective proteins. Some of the drugs showed relatively better docking score and binding energies as compared to the already known inhibitors of the respective targets. Molecular descriptors like molecular weight, number of hydrogen bond donors, acceptors, predicted octanol/water partition coefficient and percentage human oral absorption were also analysed to determine the in silico ADME properties of these drugs and all were found in the acceptable range and follows Lipinski's rule. CONCLUSION: The present study have led to unravel the potential of leading antipsychotic drugs such as pimozide, bromperidol, melperone, anisoperidone, benperidol and anisopirol against multiple targets associated with AD. Benperidol was found to be the best candidate drug interacting with different target proteins involved in AD.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/s12868-017-0394-8

Cites

56 of 56 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Kumar, S., Chowdhury, S., & Kumar, S.
Affiliations
Guru Gobind Singh Indraprastha University (IN)
Corresponding author
Kumar, Suresh
Venue
BMC Neuroscience
Published
2017-10-27
Volume
18
Issue
1
Pages
76-76
ISSN
1471-2202 (ISSN-L)
OpenAlex
W2765951174
Cited by
103
References
56
Citations by year
2026: 4 · 2025: 10 · 2024: 12 · 2023: 15 · 2022: 19 · 2021: 14 · 2020: 16 · 2019: 9 · 2018: 4
FWCI
5.95
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • BMC Neuroscience (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Faculty Research Grant Scheme, GGSIPU (GGSIPU/DRC)
Topics
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
  • Health Sciences › Medicine › Pharmacology › Cholinesterase and Neurodegenerative Diseases
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
Keywords
Alzheimer's disease, drug repurposing, antipsychotic drugs, protein-ligand interactions, acetylcholinesterase, butyrylcholinesterase, beta-secretase, monoamine oxidase, NMDA receptor, benperidol, pimozide, bromperidol, melperone, ADME properties, Lipinski's rule, molecular docking
MeSH terms
Acetylcholinesterase, Alzheimer Disease, Butyrophenones, Butyrylcholinesterase, Glucosides, Haloperidol, Humans, Monoamine Oxidase, Pimozide, Psychotropic Drugs, Antipsychotic Agents, Molecular Structure, Receptors, N-Methyl-D-Aspartate, Aspartic Acid Endopeptidases, Norisoprenoids, Amyloid Precursor Protein Secretases, Drug Repositioning, Molecular Docking Simulation

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review