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Molecular modeling to simulation: insights into Gaussian QSAR, molecular docking, and DFT for identification of HDAC3 inhibitors for neurocognitive vascular dementia
Debojyoti Halder, Suvankar Banerjee, Swati Biswas, Nilanjan Adhikari, Balaram Ghosh. Scientific Reports, 2025-12-01
Topic: Brain proteins, microglia and lab models
Vascular dementia is the second most common form of dementia. It is characterized by reduced blood flow in the cerebral cortex due to neurodegeneration and neuroinflammation. Almost 10 crore people will be suffering from it by 2030. Still, there are no therapeutics reported for the treatment of neurocognitive vascular dementia. Hence, we have explored an epigenetic pathway for the targeted inhibition of histone deacetylase 3 (HDAC3) that can further cure the neurocognitive impairment. In the present study, we have incorporated in silico methodologies for small-molecule inhibitor screening. The methodologies include multi-model pharmacophore development, validation, virtual screening by HDAC3 targeted docking and dynamics simulation, quantum chemical analysis, and ADMET properties. After the virtual screening, the best two compounds were selected according to the docking score, MM/GBSA scoring, and IFD. The top two hits—57402 and 46381 represented interactions with zinc-binding and amino acids such as HIE172 and HIE135 GLY143, and ASP93 residues compared with RGFP966. Furthermore, the density function theory study was employed to understand the reactivity and stability of the compounds, and quantum chemical properties relevant to drug design were compared with standard RGFP966. Following the molecular dynamics simulation and ADMET analysis, which evaluates how a substance is absorbed, distributed, metabolized, and excreted, along with its toxicity, the two hit compounds—57402 and 46381 showed superior binding scores and targeted inhibition of HDAC3 by zinc chelation. Therefore, the study is of great significance in the quest for new molecules for the treatment of vascular dementia targeting HDAC3.
Key findings
- The top two hits—57402 and 46381 represented interactions with zinc-binding and amino acids such as HIE172 and HIE135 GLY143, and ASP93 residues compared with RGFP966.
- Furthermore, the density function theory study was employed to understand the reactivity and stability of the compounds, and quantum chemical properties relevant to drug design were compared with standard RGFP966.
Why it matters
This is a computer-based (in silico) study that screened small molecules for inhibiting HDAC3 as a possible approach to vascular dementia, selecting two top compounds based on docking and simulation. It is early computational work and no compound has been tested in patients, so it does not yet show any treatment, cure or prevention.
Study details
- Evidence strengthLow
How this study scored 41/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on senior author's track record, so that was left out: it earned 39 of the 96 points we could judge it on, which is 41 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Scientific Reports) |
| Journal's citation record | 3 / 4 | Scientific Reports: journal h-index 463 (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) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 2 / 7 | Cited 11 times (OpenAlex, 2026-10-10) |
| Citations per year | 2 / 5 | 3.7 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 3 / 6 | Cited 5.5× 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 11 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | 0 / 3 | Jadavpur University: institution h-index 329 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 4 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 41326481) |
| Free to read | 2 / 2 | Free to read |
| Points | 39 / 96 | Scored on 19 of 20 parts. We have no data for the rest, so they are left out: 39 of the 96 points we could judge it on is 41 out of 100. |
| Total | 41 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
- DOI: 10.1038/s41598-025-28304-y
- PubMed: 41326481
- Original source →
- Free full text: Scientific Reports →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
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.
APA 7th
Halder, D., Banerjee, S., Biswas, S., Adhikari, N., & Ghosh, B. (2025). Molecular modeling to simulation: insights into Gaussian QSAR, molecular docking, and DFT for identification of HDAC3 inhibitors for neurocognitive vascular dementia. Scientific Reports. https://doi.org/10.1038/s41598-025-28304-y
Vancouver
Halder D, Banerjee S, Biswas S, Adhikari N, Ghosh B. Molecular modeling to simulation: insights into Gaussian QSAR, molecular docking, and DFT for identification of HDAC3 inhibitors for neurocognitive vascular dementia. Scientific Reports. 2025. doi:10.1038/s41598-025-28304-y. PMID: 41326481.
BibTeX
@article{halder2025-41326481,
author = {Halder, Debojyoti and Banerjee, Suvankar and Biswas, Swati and Adhikari, Nilanjan and Ghosh, Balaram},
title = {{Molecular modeling to simulation: insights into Gaussian QSAR, molecular docking, and DFT for identification of HDAC3 inhibitors for neurocognitive vascular dementia}},
journal = {Scientific Reports},
year = {2025},
doi = {10.1038/s41598-025-28304-y},
pmid = {41326481},
url = {https://doi.org/10.1038/s41598-025-28304-y}
}