ArticleJournal of chemical theory and computation2023
Exploration and Exploitation Approaches Based on Generative Machine Learning to Identify Potent Small Molecule Inhibitors of α-Synuclein Secondary Nucleation.
Article in Journal of chemical theory and computation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Multi-objective optimization in the context of generative chemistry.Nature communications · 2026Review
- Natural Products as a Pipeline for Next-Generation Neurodegenerative Drugs: From Single-Target Failure to Multi-Target Opportunity in Alzheimer's and Parkinson's Disease.Molecules (Basel, Switzerland) · 2026Review
- Discovery of TDP-43 aggregation inhibitorsbioRxiv : the preprint server for biology · 2026Article
- Identification of potent high-affinity secondary nucleation inhibitors of Aβ42 aggregation from an ultra-large chemical library using deep docking.Molecular systems biology · 2026Article
- Photochemically synthesized gold nanoparticles conjugated with Boswellic acid inhibit alpha synuclein aggregation and delay fibrillation kinetics.Scientific reports · 2025Article
- Detection of protein oligomers with nanopores.Nature reviews. Chemistry · 2025Review
- Discovery of potent inhibitors of α-synuclein aggregation using structure-based iterative learning.Nature chemical biology · 2024Article
- The thermodynamics of neurodegenerative disease.Biophysics reviews · 2024Review
- Using Generative Modeling to Endow with Potency Initially Inert Compounds with Good Bioavailability and Low Toxicity.Journal of chemical information and modeling · 2024Article
- Multiplexed Digital Characterization of Misfolded Protein Oligomers via Solid-State Nanopores.Journal of the American Chemical Society · 2023Article
- Generative organic electronic molecular design informed by quantum chemistry.Chemical science · 2023Article
- Secondary Processes Dominate the Quiescent, Spontaneous Aggregation of α-Synuclein at Physiological pH with Sodium Salts.ACS chemical neuroscience · 2023Article
- Optimization of a small molecule inhibitor of secondary nucleation in α-synuclein aggregation.Frontiers in molecular biosciences · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The high attrition rate in drug discovery pipelines is an especially pressing issue for Parkinson's disease, for which no disease-modifying drugs have yet been approved. Numerous clinical trials targeting α-synuclein aggregation have failed, at least in part due to the challenges in identifying potent compounds in preclinical investigations. To address this problem, we present a machine learning approach that combines generative modeling and reinforcement learning to identify small molecules that perturb the kinetics of aggregation in a manner that reduces the production of oligomeric species. Training data were obtained by an assay reporting on the degree of inhibition of secondary nucleation, which is the most important mechanism of α-synuclein oligomer production. This approach resulted in the identification of small molecules with high potency against secondary nucleation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.