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Computational Screening of 1,348 FDA-Approved Drugs as Potential BACE1 Inhibitors for Alzheimer's Disease Drug Repurposing
Rathi R.. Research Square, 2026-07-28
Topic: Disease mechanisms in lab and animal studies
Alzheimer's disease (AD) remains one of the most devastating and economically costly neurological conditions of the modern era, affecting over 55 million individuals worldwide with no approved disease-modifying therapy. Beta-secretase 1 (BACE1), the enzyme responsible for initiating amyloid-beta (Aβ) peptide production through cleavage of the amyloid precursor protein (APP), represents the most extensively validated pharmacological target in AD drug discovery. Despite decades of research and multiple large-scale clinical trials of BACE1 inhibitors, no candidate has succeeded in demonstrating both efficacy and an acceptable safety profile in human subjects. This study presents, to our knowledge, the first comprehensive computational screen of all FDA-approved drugs (n = 1,348) against the AlphaFold2-predicted BACE1 structure (UniProt accession P56817) using automated molecular docking via AutoDock Vina 1.2.5. Blind docking across a 40×40×40 Å search volume encompassing the complete BACE1 surface was conducted through a custom Python-automated pipeline. Of the 1,348 compounds screened, 809 (60%) demonstrated binding affinity below the −7.0 kcal/mol significance threshold. The top hit, Paritaprevir — a Hepatitis C NS3/4A protease inhibitor — achieved a binding affinity of −12.48 kcal/mol, surpassing the published docking scores of all known clinical-stage BACE1 inhibitors. Critically, three of the top five hits were Hepatitis C antiviral agents (Paritaprevir, Ledipasvir, Simeprevir), representing a novel structural drug class never previously associated with BACE1 inhibition. Nilotinib, a leukemia drug independently shown to reduce tau and amyloid pathology in preclinical AD models, appeared among the top hits, providing methodological cross-validation. Sertraline (−7.50 kcal/mol), identified in an initial six-compound pilot screen, was confirmed in the full screen. These findings establish Hepatitis C antivirals as a novel and structurally compelling class of BACE1 repurposing candidates worthy of experimental investigation.
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APA 7th
Rathi, R. (2026). Computational Screening of 1,348 FDA-Approved Drugs as Potential BACE1 Inhibitors for Alzheimer's Disease Drug Repurposing. Research Square. https://doi.org/10.21203/rs.3.rs-10484841/v1
Vancouver
Rathi R. Computational Screening of 1,348 FDA-Approved Drugs as Potential BACE1 Inhibitors for Alzheimer's Disease Drug Repurposing. Research Square. 2026. doi:10.21203/rs.3.rs-10484841/v1.
BibTeX
@article{rathi2026-5bb621f8,
author = {Rathi, R.},
title = {{Computational Screening of 1,348 FDA-Approved Drugs as Potential BACE1 Inhibitors for Alzheimer's Disease Drug Repurposing}},
journal = {Research Square},
year = {2026},
doi = {10.21203/rs.3.rs-10484841/v1},
url = {https://doi.org/10.21203/rs.3.rs-10484841/v1}
}
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Key findings
- Of the 1,348 compounds screened, 809 (60%) demonstrated binding affinity below the −7.0 kcal/mol significance threshold.
- Critically, three of the top five hits were Hepatitis C antiviral agents (Paritaprevir, Ledipasvir, Simeprevir), representing a novel structural drug class never previously associated with BACE1 inhibition.
- These findings establish Hepatitis C antivirals as a novel and structurally compelling class of BACE1 repurposing candidates worthy of experimental investigation.
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Study details
- Participants1,348
- Evidence strengthLow
How this study scored 16/100
Preprint — not yet peer-reviewed. It scored 31 on the same rubric, but non-peer-reviewed sources are capped at 16, so it shows as 16. Scored zero for study design, effect reported and randomised / blinded because the record does not state it. We have no data on times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 19 of the 62 points we could judge it on, which is 31 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 2 / 10 | Tier 4 — not a peer-reviewed journal (Research Square) |
| Journal's citation record | 0 / 4 | Not a journal article, so the journal's record does not count |
| 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 | 4 / 10 | Preprint — not yet peer-reviewed. Hosted on a preprint server. |
| How recent | 5 / 5 | 2026 — within 1 year(s) of the newest study here |
| Sample size | 3 / 4 | 1,348 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 1 / 2 | Not in PubMed, but has a DOI |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 19 / 62 | Scored on 12 of 20 parts. We have no data for the rest, so they are left out: 19 of the 62 points we could judge it on is 31 out of 100. |
| Total | 31 / 100 | Capped to 16 because this is not a peer-reviewed article. |
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