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Targeting Monoamine Oxidase B for the Treatment of Alzheimer’s and Parkinson’s Diseases Using Novel Inhibitors Identified Using an Integrated Approach of Machine Learning and Computer-Aided Drug Design

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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UCSF Chimera—A visualization system for exploratory research and analysis
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Data Mining in Agriculture
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Support-Vector Networks
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Top 10 algorithms in data mining
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Dual coordinate descent methods for logistic regression and maximum entropy models
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Structure-based design and analysis of MAO-B inhibitors for Parkinson’s disease: using in silico approaches
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Computer modeling in predicting the bioactivity of human 5-lipoxygenase inhibitors
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Computational models for the classification of mPGES-1 inhibitors with fingerprint descriptors
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EGFRisopred: a machine learning-based classification model for identifying isoform-specific inhibitors against EGFR and HER2
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Selective inhibitors of monoamine oxidase type B and the “cheese effect”
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Synthesis, monoamine oxidase inhibitory activity and computational study of novel isoxazole derivatives as potential antiparkinson agents
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Lead- and drug-like compounds: the rule-of-five revolution
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Knowledge based identification of MAO-B selective inhibitors using pharmacophore and structure based virtual screening models
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In silico design of novel 2H-chromen-2-one derivatives as potent and selective MAO-B inhibitors
inferredcites →https://doi.org/10.1016/j.fct.2009.12.019openalex-snapshot
β-Carboline alkaloids in Peganum harmala and inhibition of human monoamine oxidase (MAO)
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Computational screening of camostat and related compounds against human TMPRSS2: A potential treatment of COVID-19
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On the Binding of Monoamine Oxidase Inhibitors to Some Sites Distinct from the MAO Active Site, and Effects Thereby Elicited
inferredcites →https://doi.org/10.1016/s0161-813x(03)00106-2openalex-snapshot
Monoamine Oxidase-B Inhibition in Alzheimer's Disease
inferredcites →https://doi.org/10.1021/acs.jcim.6b00608openalex-snapshot
Understanding the Molecular Determinant of Reversible Human Monoamine Oxidase B Inhibitors Containing 2H-Chromen-2-One Core: Structure-Based and Ligand-Based Derived Three-Dimensional Quantitative Structure–Activity Relationships Predictive Models
inferredcites →https://doi.org/10.1021/acschemneuro.1c00430openalex-snapshot
Identification of a Chlorogenic Ester as a Monoamine Oxidase (MAO-B) Inhibitor by Integrating “Traditional and Machine Learning” Virtual Screening and In Vitro as well as In Vivo Validation: A Lead against Neurodegenerative Disorders?
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Multitask Machine Learning for Classifying Highly and Weakly Potent Kinase Inhibitors
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Rapid Shape-Based Ligand Alignment and Virtual Screening Method Based on Atom/Feature-Pair Similarities and Volume Overlap Scoring
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Novel Method for Generating Structure-Based Pharmacophores Using Energetic Analysis
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Glide: A New Approach for Rapid, Accurate Docking and Scoring. 1. Method and Assessment of Docking Accuracy
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Extra Precision Glide: Docking and Scoring Incorporating a Model of Hydrophobic Enclosure for Protein−Ligand Complexes
inferredcites →https://doi.org/10.1021/jm070677yopenalex-snapshot
Structures of Human Monoamine Oxidase B Complexes with Selective Noncovalent Inhibitors: Safinamide and Coumarin Analogs
inferredcites →https://doi.org/10.1038/s41573-019-0024-5openalex-snapshot
Applications of machine learning in drug discovery and development
inferredcites →https://doi.org/10.1038/sj.bjp.0706464openalex-snapshot
Monoamine oxidase: isoforms and inhibitors in Parkinson's disease and depressive illness
inferredcites →https://doi.org/10.1074/jbc.m110.169482openalex-snapshot
Potentiation of Ligand Binding through Cooperative Effects in Monoamine Oxidase B
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In silicoidentification and design of potent peptide inhibitors against PDZ-3 domain of Postsynaptic Density Protein (PSD-95)
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Revealing the role of fluorine pharmacophore in chalcone scaffold for shifting the MAO-B selectivity: investigation of a detailed molecular dynamics and quantum chemical study
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The Protein Data Bank
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The ChEMBL database in 2017
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Half a Century of Antidepressant Drugs
inferredcites →https://doi.org/10.1109/72.159058openalex-snapshot
Multilayer perceptron, fuzzy sets, and classification
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Machine Learning for Classification of Inhibitors of Hepatic Drug Transporters
inferredcites →https://doi.org/10.1146/annurev.neuro.22.1.197openalex-snapshot
MONOAMINE OXIDASE: From Genes to Behavior
inferredcites →https://doi.org/10.14712/fb2019065050212openalex-snapshot
Machine Learning and Deep Learning Approaches in Breast Cancer Survival Prediction Using Clinical Data
inferredcites →https://doi.org/10.1592/phco.27.12part2.161sopenalex-snapshot
Pharmacotherapy for Parkinson's Disease
inferredcites →https://doi.org/10.2174/1386207320666170310121337openalex-snapshot
Therapeutic, Molecular and Computational Aspects of Novel Monoamine Oxidase (MAO) Inhibitors
inferredcites →https://doi.org/10.2174/1573409915666190503113617openalex-snapshot
Identification of Novel Phyto-chemicals from Ocimum basilicum for the Treatment of Parkinson’s Disease using In Silico Approach
inferredcites →https://doi.org/10.2307/j.ctvcm4h07.63openalex-snapshot
Erwin Schrödinger
inferredcites →https://doi.org/10.3390/math11020416openalex-snapshot
Dynamic Extraction of Initial Behavior for Evasive Malware Detection
inferredcites →https://doi.org/10.3390/math11030494openalex-snapshot
Flight Delay Propagation Prediction Based on Deep Learning
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Machine Learning Methods in Drug Discovery
inferredcites →https://doi.org/10.3390/pharmaceutics14071415openalex-snapshot
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inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-snapshot
Scikit-learn: Machine Learning in Python
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Monoamine oxidases in major depressive disorder and alcoholism
inferredcites →https://doi.org/10.5607/en.2011.20.1.1openalex-snapshot
MAO-inhibitors in Parkinson's Disease

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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