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Small-Molecule Inhibitors of Amyloid Beta: Insights from Molecular Dynamics—Part B: Natural Compounds
Mariyana Atanasova. Pharmaceuticals, 2025-09-28
Topic: Amyloid, tau and blood-test diagnosis
Alzheimer's disease (AD) is the most common form of dementia, characterized by progressive memory loss and cognitive decline. Its key pathological hallmarks include extracellular amyloid plaques composed of amyloid beta (Aβ) peptides and intracellular neurofibrillary tangles formed by hyperphosphorylated tau protein. Although numerous studies have investigated the complex pathology of AD, its underlying mechanisms remain incompletely understood. The amyloid cascade hypothesis continues to be the leading model of AD pathogenesis. It suggests that Aβ aggregation is the initial trigger of neurotoxicity, setting off a cascade of pathological events including inflammation, oxidative stress, tau hyperphosphorylation, synaptic dysfunction, and, ultimately, dementia. Molecular dynamics (MD) is a powerful tool in structure-based drug design (SBDD). By simulating biomolecular motions at the atomic level, MD provides unique insights into molecular properties, functions, and inhibition mechanisms-insights often inaccessible through other experimental or computational techniques. When integrated with experimental data, MD further deepens our understanding of molecular interactions and biological processes. Natural compounds, known for their pleiotropic pharmacological activities, favorable safety profiles, and general tolerability (despite occasional side effects), are increasingly explored for their potential in both the treatment and prevention of various diseases, including AD. In this review, we summarize current findings from MD simulations of natural compounds with anti-amyloidogenic potential. This work builds upon our previous publication, which focused on endogenous compounds and repurposed drugs. The review is structured as follows: an overview of the amyloid cascade hypothesis; a discussion of Aβ oligomeric structures and their stabilizing interactions; a section on molecular dynamics, including its challenges and future directions; and a comprehensive analysis of the inhibitory mechanisms of natural compounds, categorized by their shared structural features.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Atanasova, M. (2025). Small-Molecule Inhibitors of Amyloid Beta: Insights from Molecular Dynamics—Part B: Natural Compounds. Pharmaceuticals. https://doi.org/10.3390/ph18101457
Vancouver
Atanasova M. Small-Molecule Inhibitors of Amyloid Beta: Insights from Molecular Dynamics—Part B: Natural Compounds. Pharmaceuticals. 2025. doi:10.3390/ph18101457. PMID: 41155570.
BibTeX
@article{atanasova2025-41155570,
author = {Atanasova, Mariyana},
title = {{Small-Molecule Inhibitors of Amyloid Beta: Insights from Molecular Dynamics—Part B: Natural Compounds}},
journal = {Pharmaceuticals},
year = {2025},
doi = {10.3390/ph18101457},
pmid = {41155570},
url = {https://doi.org/10.3390/ph18101457}
}
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.
Key findings
- It suggests that Aβ aggregation is the initial trigger of neurotoxicity, setting off a cascade of pathological events including inflammation, oxidative stress, tau hyperphosphorylation, synaptic dysfunction, and, ultimately, dementia.
Why it matters
This review discusses how molecular dynamics simulations are used to study natural compounds that might block amyloid-beta aggregation, based on the idea that amyloid-beta clumping starts the disease process. It is a computational and review-based work, so it does not show that any compound prevents or treats Alzheimer's in people.
Study details
- Evidence strengthLow
How this study scored 33/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomized / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Pharmaceuticals) |
| Journal's citation record | 1 / 4 | Pharmaceuticals: journal h-index 146 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomized / blinded | 0 / 2 | No randomization or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 1 / 7 | Cited 4 times (OpenAlex, 2026-10-10) |
| Citations per year | 1 / 5 | 1.3 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 2 / 6 | Cited 2.2× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 1 / 4 | Cited 4 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 1 / 4 | Last-listed author Mariyana Atanasova: h-index 17 (OpenAlex, whole career) |
| Institution's track record | 0 / 3 | Medical University of Sofia: institution h-index 235 (OpenAlex) |
| Multicenter collaboration | 0 / 3 | OpenAlex lists 1 institution(s) in 1 country — scores zero (affiliation lists can be incomplete) |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 41155570) |
| Free to read | 2 / 2 | Free to read |
| Total | 33 / 100 | — |
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