AIMC Topic: Drug Discovery

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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...
Drug Discovery Databases, Protein Drug Evaluation, Preclinical Small Molecule Libraries Humans Machine Learning
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Machine Learning Platform to Discover Novel Growth Inhibitors of Neisseria gonorrhoeae.

Pharmaceutical research Jul 13, 2020
PURPOSE: To advance fundamental biological and translational research with the bacterium Neisseria gonorrhoeae through the prediction of novel small molecule growth inhibitors via naïve Bayesian modeling methodology.
Gonorrhea Databases, Chemical Structure-Activity Relationship Molecular Structure Bayes Theorem Neisseria gonorrhoeae Drug Discovery Microbial Sensitivity Tests Machine Learning Anti-Bacterial Agents
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Automated design and optimization of multitarget schizophrenia drug candidates by deep learning.

European journal of medicinal chemistry Jul 12, 2020
Complex neuropsychiatric diseases such as schizophrenia require drugs that can target multiple G protein-coupled receptors (GPCRs) to modulate complex neuropsychiatric functions. Here, we report an automated system comprising a deep recurrent neural ...
Schizophrenia Automation Receptor, Serotonin, 5-HT2A Molecular Targeted Therapy Deep Learning Animals Mice Drug Discovery Receptors, Dopamine D2 Receptor, Serotonin, 5-HT1A
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Deep Learning-Based Imbalanced Data Classification for Drug Discovery.

Journal of chemical information and modeling Jul 8, 2020
Drug discovery studies have become increasingly expensive and time-consuming processes. In the early phase of drug discovery studies, an extensive search has been performed to find drug-like compounds, which then can be optimized over time to become ...
Drug Discovery Deep Learning Machine Learning Algorithms Neural Networks, Computer
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Artificial Intelligence in Drug Discovery: Into the Great Wide Open.

Journal of medicinal chemistry Jul 8, 2020
Machine Learning Drug Discovery Periodicals as Topic Humans
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Machine learning and AI-based approaches for bioactive ligand discovery and GPCR-ligand recognition.

Methods (San Diego, Calif.) Jul 6, 2020
In the last decade, machine learning and artificial intelligence applications have received a significant boost in performance and attention in both academic research and industry. The success behind most of the recent state-of-the-art methods can be...
Neural Networks, Computer Artificial Intelligence Drug Discovery Deep Learning Machine Learning Software Ligands Receptors, G-Protein-Coupled Supervised Machine Learning
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The art of atom descriptor design.

Drug discovery today. Technologies Jul 3, 2020
This review provides an overview of descriptions of atoms applied to the understanding of phenomena like chemical reactivity and selectivity, pK values, Site of Metabolism prediction, or hydrogen bond strengths, but also the substitution of quantum m...
Drug Discovery Quantum Theory Pharmaceutical Preparations Humans Machine Learning
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Predicting Binding from Screening Assays with Transformer Network Embeddings.

Journal of chemical information and modeling Jul 1, 2020
Cheminformatics aims to assist in chemistry applications that depend on molecular interactions, structural characteristics, and functional properties. The arrival of deep learning and the abundance of easily accessible chemical data from repositories...
Computer Simulation Drug Discovery Neural Networks, Computer Software
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Molecular property prediction: recent trends in the era of artificial intelligence.

Drug discovery today. Technologies Jul 1, 2020
Artificial intelligence (AI) has become a powerful tool in many fields, including drug discovery. Among various AI applications, molecular property prediction can have more significant immediate impact to the drug discovery process since most algorit...
Molecular Structure Humans Artificial Intelligence Drug Discovery
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Applications of machine-learning methods for the discovery of NDM-1 inhibitors.

Chemical biology & drug design Jun 20, 2020
The emergence of New Delhi metal beta-lactamase (NDM-1)-producing bacteria and their worldwide spread pose great challenges for the treatment of drug-resistant bacterial infections. These bacteria can hydrolyze most β-lactam antibacterials. Unfortuna...
Machine Learning beta-Lactamases Drug Discovery Anti-Bacterial Agents Humans Drug Evaluation, Preclinical beta-Lactamase Inhibitors
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