Developments with multi-target drugs for Alzheimer’s disease: An overview of the current discovery approaches
Open accessAbstract
Introduction: Alzheimer’s disease (AD), the most common type of dementia among older adults, is a chronic neurodegenerative pathology that causes a progressive loss of cognitive functioning with a decline of rational skills. It is well known that AD is multifactorial, so there are many different pharmacological targets that can be pursued.Areas covered: The authors highlight the strategic value of privileged scaffolds in a multi-target lead compound generation against AD, exploring the concept of multi-target design, with a special emphasis on hybrid compounds. Hence, the most promising building blocks for designing and synthesizing hybrid anti-AD drugs are shown, while also presenting the more advanced hybrid compounds.Expert opinion: The available therapeutic arsenal for AD, designed under the traditional paradigm of ‘one-drug/one target/one-disease’, is based on the inhibition of brain acetylcholinesterase (AChE) to increase acetylcholine (ACh) levels. However, this classical approach has not been sufficiently effective when used to treat any multifactor-depending pathology (cancer, diabetes or AD). The multi-target drug concept has been quickly adopted by medicinal chemists. The basic research developments reported in recent years are a solid foundation that will pave the way for the construction of future AD therapeutics.
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Effective therapeutic regimens for Alzheimer's disease may necessitate the utilization of numerous neuroprotective agents.
“Nonetheless, effective therapeutic regimens for AD may necessitate the utilization of numerous neuroprotective agents [33,34].”
From The Multifaceted Role of Neuroprotective Plants in Alzheimer’s Disease Treatment (2022) · cites this paper as [34]
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Alzheimer’s Disease: Key Insights from Two Decades of Clinical Trial Failures
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The Multifaceted Role of Neuroprotective Plants in Alzheimer’s Disease Treatment
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“Nonetheless, effective therapeutic regimens for AD may necessitate the utilization of numerous neuroprotective agents [33,34].”
Background
- Authors
- González, J. F., Alcántara, A. R., Doadrio, A. L., & Sánchez-Montero, J. M.
- Affiliations
- Universidad Complutense de Madrid (ES)
- Corresponding author
- Sánchez-Montero, Jose María
- Venue
- Expert Opinion on Drug Discovery
- Publisher
- Informa UK Limited
- Published
- 2019-06-05
- Volume
- 14
- Issue
- 9
- Pages
- 879-891
- ISSN
- 1746-0441 (ISSN-L)
- 1746-045X
- OpenAlex
- W2949937187
- Cited by
- 98
- References
- 111
- Citations by year
- 2026: 6 · 2025: 13 · 2024: 23 · 2023: 14 · 2022: 13 · 2021: 15 · 2020: 11 · 2019: 3
- FWCI
- 1.35
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- cc-by
- Locations
- Expert Opinion on Drug Discovery (publishedVersion)
- PubMed (publishedVersion)
- Zenodo (CERN European Organization for Nuclear Research) (cc-by)
- Funders
- Universidad Complutense de Madrid Foundation (PR26/16-16B)
- Ministerio de Industria, Economía y Competitividad (CTQ2017-86170)
- Topics
- Health Sciences › Medicine › Pharmacology › Cholinesterase and Neurodegenerative Diseases
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- Alzheimer's disease, multi-target drugs, privileged scaffolds, hybrid molecules, acetylcholinesterase inhibitors, acetylcholine, neurodegeneration, drug discovery, lead compound design
- MeSH terms
- Drug Development, Aged, Alzheimer Disease, Animals, Cholinesterase Inhibitors, Cognition, Humans, Drug Design, Drug Discovery, Molecular Targeted Therapy
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 ›
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