AIMC Topic: Small Molecule Libraries

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Site-Level Bioactivity of Small-Molecules from Deep-Learned Representations of Quantum Chemistry.

The journal of physical chemistry. A Oct 21, 2020
Atom- or bond-level chemical properties of interest in medicinal chemistry, such as drug metabolism and electrophilic reactivity, are important to understand and predict across arbitrary new molecules. Deep learning can be used to map molecular struc...
Small Molecule Libraries Deep Learning Quantum Theory
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Machine learning-based QSAR models to predict sodium ion channel (Na 1.5) blockers.

Future medicinal chemistry Oct 9, 2020
Conventional experimental approaches used for the evaluation of the proarrhythmic potential of compounds in the drug discovery process are expensive and time consuming but an integral element in the safety profile required for a new drug to be appro...
Humans Machine Learning Small Molecule Libraries NAV1.5 Voltage-Gated Sodium Channel Sodium Channel Blockers Models, Statistical Regression Analysis Quantitative Structure-Activity Relationship
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A multimodal deep learning-based drug repurposing approach for treatment of COVID-19.

Molecular diversity Sep 30, 2020
Recently, various computational methods have been proposed to find new therapeutic applications of the existing drugs. The Multimodal Restricted Boltzmann Machine approach (MM-RBM), which has the capability to connect the information about the multip...
COVID-19 Drug Treatment Small Molecule Libraries Deep Learning Drug Repositioning Probability
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Drug Design of Targeted Chemical Libraries Based on Artificial Intelligence and Pair-Based Multiobjective Optimization.

Journal of chemical information and modeling Sep 9, 2020
Artificial intelligence and multiobjective optimization represent promising solutions to bridge chemical and biological landscapes by addressing the automated design of compounds as a result of a humanlike creative process. In the present study, we ...
Humans Neural Networks, Computer Artificial Intelligence Molecular Docking Simulation Drug Design Influenza A virus Pandemics COVID-19 SARS-CoV-2 Coronavirus 3C Proteases Enzyme Inhibitors Viral Nonstructural Proteins Small Molecule Libraries Cysteine Endopeptidases Betacoronavirus Pneumonia, Viral Antiviral Agents Neuraminidase Coronavirus Infections Acetylcholinesterase Cholinesterase Inhibitors
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Machine learning classification can reduce false positives in structure-based virtual screening.

Proceedings of the National Academy of Sciences of the United States of America Jul 15, 2020
With the recent explosion in the size of libraries available for screening, virtual screening is positioned to assume a more prominent role in early drug discovery's search for active chemical matter. In typical virtual screens, however, only about 1...
Databases, Protein Drug Evaluation, Preclinical Small Molecule Libraries Humans Machine Learning Drug Discovery
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Machine Learning on DNA-Encoded Libraries: A New Paradigm for Hit Finding.

Journal of medicinal chemistry Jun 11, 2020
DNA-encoded small molecule libraries (DELs) have enabled discovery of novel inhibitors for many distinct protein targets of therapeutic value. We demonstrate a new approach applying machine learning to DEL selection data by identifying active molecul...
Estrogen Receptor alpha Epoxide Hydrolases Protein Kinase Inhibitors Neural Networks, Computer Drug Discovery Small Molecule Libraries DNA Proto-Oncogene Proteins c-kit Ligands
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Revealing cytotoxic substructures in molecules using deep learning.

Journal of computer-aided molecular design Apr 16, 2020
In drug development, late stage toxicity issues of a compound are the main cause of failure in clinical trials. In silico methods are therefore of high importance to guide the early design process to reduce time, costs and animal testing. Technical a...
Computer-Aided Design Drug Design Drug Discovery Toxicology Humans Models, Biological Deep Learning Small Molecule Libraries Neural Networks, Computer Hep G2 Cells Cytotoxins Software Cell Survival HEK293 Cells
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Deep-learning- and pharmacophore-based prediction of RAGE inhibitors.

Physical biology Mar 16, 2020
The receptor for advanced glycation end products (RAGE) has been identified as a therapeutic target in a host of pathological diseases, including Alzheimer's disease. RAGE is a target with no crystallographic data on inhibitors in complex with RAGE, ...
Humans Models, Molecular Software Small Molecule Libraries Deep Learning Receptor for Advanced Glycation End Products
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A machine learning approach for handling big data produced by high resolution mass spectrometry after data independent acquisition of small molecules - Proof of concept study using an artificial neural network for sample classification.

Drug testing and analysis Feb 6, 2020
Liquid chromatography coupled to high-resolution mass spectrometry (HRMS) enables data independent acquisition (DIA) and untargeted screening. However, to avoid the handling of the resulting large dataset, most laboratories in that field still use ta...
Machine Learning Reproducibility of Results Cocaine Sensitivity and Specificity Substance Abuse Detection Zolpidem Humans Proof of Concept Study Neural Networks, Computer Small Molecule Libraries Big Data Mass Spectrometry Chromatography, Liquid
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Deep Learning to Generate Chemical Property Libraries and Candidate Molecules for Small Molecule Identification in Complex Samples.

Analytical chemistry Jan 6, 2020
Comprehensive and unambiguous identification of small molecules in complex samples will revolutionize our understanding of the role of metabolites in biological systems. Existing and emerging technologies have enabled measurement of chemical properti...
Metabolomics Molecular Structure Computer Simulation Small Molecule Libraries Deep Learning
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