The in silico search for endogenous anti‐Alzheimer's compounds
Bibliographic record
Abstract
Abstract Background Since many peptide and proteins are susceptible to oligomerization analogous to Aβ and tau, there is evolutionary pressure to inhibit deleterious protein misfolding; likewise, the immunoinflammatory cascade triggered by such misfolding is also subject to homeostatic regulation. Accordingly, it is reasonable to postulate the existence of endogenous molecules within the human brain that could modulate or even interrupt the neurotoxic cascade of AD by blocking both the proteopathy and immunopathy of Alzheimer's disease (AD). Such compounds would constitute platforms for future drug development. Method We sought to identify a single anti‐proteopathic and anti‐immunopathic agent endogenous to the human central nervous system; to find this compound, we created a comprehensive library of 1,376 molecules (molecular weight < 600 Da) naturally occurring within the human brain and employed an in silico screening assay. Using computer‐aided screening with a molecular mechanics force field, we docked these endogenous molecules against computer models of in Aβ(HHQK16LVFF), tau(KKAK144), IL‐1R1(HKEK80), IL‐1β(KLRK76), C1qA(KKGH225), IFN‐gamma(KKKR112) and RANTES(RKNR70). Additional molecular dynamics simulations were done to refine the docking. Finally, multiple in vitro assays were done, verifying that the in silico hits had correctly predicted the ability to block oligomerization and to bind to multiple immunopeptides. Result Several zwitterionic and aromatic‐anionic compounds capable of binding to these multiple amyloid, tau and immunoprotein targets were identified. Strong in silico hits included 2‐aminoethanesulfonic acid, L‐phosphoserine, 5‐hydroxytryptamine and 3‐hydroxyanthranilic acid. These predictions were verified using in vitro assays, including the kinetic Thioflavin T [ThT] aggregation assay. Conclusion Searching for an “endogenous anti‐AD compound” represents an unexplored concept. Our in silico and in vitro studies suggest that compounds endogenous to the human brain can inhibit pathological both the proteopathic and immunopathic pathogeneses of AD. The value of a novel in silico screening assay to identify such endogenous agent capable of "one‐drug‐multiple‐targets" has also been demonstrated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".