AIMC Topic: Molecular Structure

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Classification models and SAR analysis on CysLT1 receptor antagonists using machine learning algorithms.

Molecular diversity Feb 3, 2021
Cysteinyl leukotrienes 1 (CysLT1) receptor is a promising drug target for rhinitis or other allergic diseases. In our study, we built classification models to predict bioactivities of CysLT1 receptor antagonists. We built a dataset with 503 CysLT1 re...
ROC Curve Protein Binding Models, Molecular Reproducibility of Results Drug Discovery Cheminformatics Leukotriene Antagonists Receptors, Leukotriene Molecular Structure Quantitative Structure-Activity Relationship Binding Sites Machine Learning Algorithms
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Single-Step Retrosynthesis Prediction Based on the Identification of Potential Disconnection Sites Using Molecular Substructure Fingerprints.

Journal of chemical information and modeling Feb 3, 2021
The proper application of retrosynthesis to identify possible transformations for a given target compound requires a lot of chemistry knowledge and experience. However, because the complexity of this technique scales together with the complexity of t...
Molecular Structure Humans Artificial Intelligence Machine Learning
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Using Domain-Specific Fingerprints Generated Through Neural Networks to Enhance Ligand-Based Virtual Screening.

Journal of chemical information and modeling Jan 26, 2021
Similarity-based virtual screening is a fundamental tool in the early drug discovery process and relies heavily on molecular fingerprints. We propose a novel strategy of generating domain-specific fingerprints by training neural networks on target-sp...
Drug Discovery Molecular Structure Neural Networks, Computer Ligands
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Machine Learning Classification of One-Chiral-Center Organic Molecules According to Optical Rotation.

Journal of chemical information and modeling Dec 22, 2020
In this study, machine learning algorithms were investigated for the classification of organic molecules with one carbon chiral center according to the sign of optical rotation. Diverse heterogeneous data sets comprising up to 13,080 compounds and th...
Machine Learning Algorithms Molecular Structure Stereoisomerism Optical Rotation Neural Networks, Computer
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Deep Graph Learning with Property Augmentation for Predicting Drug-Induced Liver Injury.

Chemical research in toxicology Dec 21, 2020
Drug-induced liver injury (DILI) is a crucial factor in determining the qualification of potential drugs. However, the DILI property is excessively difficult to obtain due to the complex testing process. Consequently, an screening in the early stage...
Humans Models, Chemical Deep Learning Pharmaceutical Preparations Molecular Structure Chemical and Drug Induced Liver Injury
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Phytochemical, antibacterial, antioxidant and cytoxicity investigation of .

Zeitschrift fur Naturforschung. C, Journal of biosciences Dec 17, 2020
The phytochemical investigation of led to the isolation of 18 known compounds of which were four flavones, three anthraquinones, one phenyl propanoic derivative, five triterpenoids, four steroids and a mixture of glucose. Luteolin () and soranjidiol...
Molecular Structure Biphenyl Compounds Chromatography Antioxidants Plant Bark Picrates Mass Spectrometry Oxidation-Reduction Plant Stems Cell Survival Humans Microbial Sensitivity Tests Rubiaceae Plant Leaves Anti-Bacterial Agents Cell Line, Tumor Phytochemicals Bacteria
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Generative deep learning for macromolecular structure and dynamics.

Current opinion in structural biology Dec 15, 2020
Much scientific enquiry across disciplines is founded upon a mechanistic treatment of dynamic systems that ties form to function. A highly visible instance of this is in molecular biology, where characterizing macromolecular structure and dynamics is...
Neural Networks, Computer Deep Learning Computational Biology Molecular Structure Molecular Biology
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Towards Deep Neural Network Models for the Prediction of the Blood-Brain Barrier Permeability for Diverse Organic Compounds.

Molecules (Basel, Switzerland) Dec 13, 2020
Permeation through the blood-brain barrier (BBB) is among the most important processes controlling the pharmacokinetic properties of drugs and other bioactive compounds. Using the fragmental (substructural) descriptors representing the occurrence num...
Molecular Structure Workflow Models, Biological Biological Transport Permeability Blood-Brain Barrier Animals Organic Chemicals Neural Networks, Computer Algorithms Humans
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Towards compound identification of synthetic opioids in nontargeted screening using machine learning techniques.

Drug testing and analysis Dec 9, 2020
The constant evolution of the illicit drug market makes the identification of unknown compounds problematic. Obtaining certified reference materials for a broad array of new analogues can be difficult and cost prohibitive. Machine learning provides a...
Animals Structure-Activity Relationship Molecular Structure Machine Learning Reproducibility of Results Tandem Mass Spectrometry Spectrometry, Mass, Electrospray Ionization Substance Abuse Detection Analgesics, Opioid Fentanyl Chromatography, High Pressure Liquid Horses
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Accelerating the identification of subtype selective inhibitors via Three-Dimensional Biologically Relevant Spectrum (BRS-3D): The monoamine oxidase subtypes as a case study.

Bioorganic chemistry Nov 24, 2020
Subtype-selective drugs are of great therapeutic importance as they are expected to be more effective and with less side-effects. However, discovery of subtype selective inhibitors was hampered by the high similarity of the binding sites within subfa...
Monoamine Oxidase Humans Monoamine Oxidase Inhibitors Support Vector Machine Dose-Response Relationship, Drug Structure-Activity Relationship Molecular Structure
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