AIMC Topic: Molecular Structure

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Artificial Intelligence Applied to the Rapid Identification of New Antimalarial Candidates with Dual-Stage Activity.

ChemMedChem Mar 16, 2021
Increasing reports of multidrug-resistant malaria parasites urge the discovery of new effective drugs with different chemical scaffolds. Protein kinases play a key role in many cellular processes such as signal transduction and cell division, making ...
Structure-Activity Relationship Plasmodium falciparum Molecular Structure Artificial Intelligence Dose-Response Relationship, Drug Protozoan Proteins Protein Kinase Inhibitors Mitogen-Activated Protein Kinase Kinases Drug Evaluation, Preclinical Antimalarials Parasitic Sensitivity Tests
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A novel artificial intelligence protocol to investigate potential leads for diabetes mellitus.

Molecular diversity Mar 9, 2021
Dipeptidyl peptidase-4 (DPP4) is highly participated in regulating diabetes mellitus (DM), and inhibitors of DPP4 may act as potential DM drugs. Therefore, we performed a novel artificial intelligence (AI) protocol to screen and validate the potentia...
Machine Learning Algorithms Molecular Docking Simulation Humans Neural Networks, Computer Artificial Intelligence Workflow Molecular Dynamics Simulation Quantitative Structure-Activity Relationship Hydrogen Bonding Binding Sites Dipeptidyl-Peptidase IV Inhibitors Protein Binding Drug Design Hypoglycemic Agents Drug Discovery Molecular Structure
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CryoDRGN: reconstruction of heterogeneous cryo-EM structures using neural networks.

Nature methods Feb 4, 2021
Cryo-electron microscopy (cryo-EM) single-particle analysis has proven powerful in determining the structures of rigid macromolecules. However, many imaged protein complexes exhibit conformational and compositional heterogeneity that poses a major ch...
Neural Networks, Computer Macromolecular Substances Molecular Structure Cryoelectron Microscopy
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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...
Cheminformatics Leukotriene Antagonists Receptors, Leukotriene Quantitative Structure-Activity Relationship Binding Sites Reproducibility of Results Drug Discovery ROC Curve Protein Binding Models, Molecular Molecular Structure 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 Artificial Intelligence Machine Learning Humans
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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...
Neural Networks, Computer Ligands Drug Discovery Molecular Structure
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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...
Stereoisomerism Optical Rotation Machine Learning Algorithms Neural Networks, Computer Molecular Structure
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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...
Models, Chemical Pharmaceutical Preparations Chemical and Drug Induced Liver Injury Humans Deep Learning Molecular Structure
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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...
Biphenyl Compounds Chromatography Picrates Oxidation-Reduction Molecular Structure Plant Stems Rubiaceae Antioxidants Plant Leaves Microbial Sensitivity Tests Humans Mass Spectrometry Phytochemicals Cell Line, Tumor Anti-Bacterial Agents Cell Survival Plant Bark 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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