ArticleBiomolecules2022
Discovery of MAO-B Inhibitor with Machine Learning, Topomer CoMFA, Molecular Docking and Multi-Spectroscopy Approaches.
Article in Biomolecules, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 13 citations in OpenAlex.
- Design, synthesis and biological evaluation of donepezil-safinamide hybrids as dual AChE and MAO-B inhibitor for Alzheimer's disease treatment.Journal of enzyme inhibition and medicinal chemistry · 2026Article
- An Integrated in Silico, in Vitro, and in Vivo Assessment of the Antioxidant and Neuroprotective Profile of Selenocyanate Compounds.Biological trace element research · 2026Article
- Machine Learning-Driven Bioprospecting of Cholinergic Medicinal Plants for Putative Leads Against Butyrylcholinesterase Towards Alzheimer's Care.Biochemistry research international · 2026Article
- Pterostilbene: A natural neuroprotective stilbene with anti-Alzheimer's disease properties.Journal of pharmaceutical analysis · 2025Review
- QSAR analysis of VEGFR-2 inhibitors based on machine learning, Topomer CoMFA and molecule docking.BMC chemistry · 2024Article
- Bioinformatics and machine learning driven key genes screening for hepatocellular carcinoma.Biochemistry and biophysics reports · 2024Article
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Alzheimer's disease (AD) is the most common type of dementia and is a serious disruption to normal life. Monoamine oxidase-B (MAO-B) is an important target for the treatment of AD. In this study, machine learning approaches were applied to investigate the identification model of MAO-B inhibitors. The results showed that the identification model for MAO-B inhibitors with K-nearest neighbor(KNN) algorithm had a prediction accuracy of 94.1% and 88.0% for the 10-fold cross-validation test and the independent test set, respectively. Secondly, a quantitative activity prediction model for MAO-B was investigated with the Topomer CoMFA model. Two separate cutting mode approaches were used to predict the activity of MAO-B inhibitors. The results showed that the cut model with q
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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.