AIMC Topic: Drug Discovery

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Current and Future Roles of Artificial Intelligence in Medicinal Chemistry Synthesis.

Journal of medicinal chemistry Apr 14, 2020
Artificial intelligence and machine learning have demonstrated their potential role in predictive chemistry and synthetic planning of small molecules; there are at least a few reports of companies employing synthetic planning into their overall appr...
Models, Chemical Chemistry, Pharmaceutical Chemistry Techniques, Synthetic Chemical Industry Pharmaceutical Research Machine Learning Drug Discovery
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MEDICASCY: A Machine Learning Approach for Predicting Small-Molecule Drug Side Effects, Indications, Efficacy, and Modes of Action.

Molecular pharmaceutics Apr 13, 2020
To improve the drug discovery yield, a method which is implemented at the beginning of drug discovery that accurately predicts drug side effects, indications, efficacy, and mode of action based solely on the input of the drug's chemical structure is ...
Retrospective Studies Drug Discovery Cell Line, Tumor Humans Machine Learning Benchmarking Drug-Related Side Effects and Adverse Reactions
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The power of deep learning to ligand-based novel drug discovery.

Expert opinion on drug discovery Mar 31, 2020
INTRODUCTION: Deep discriminative and generative neural-network models are becoming an integral part of the modern approach to ligand-based novel drug discovery. The variety of different architectures of neural networks, the methods of their training...
Deep Learning Ligands Algorithms Drug Design Drug Discovery Humans Neural Networks, Computer
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An Artificial Intelligence Approach to Proactively Inspire Drug Discovery with Recommendations.

Journal of medicinal chemistry Mar 30, 2020
Artificial intelligence (AI) is becoming established in drug discovery. For example, many in the industry are applying machine learning approaches to target discovery or to optimize compound synthesis. While our organization is certainly applying the...
Humans Artificial Intelligence Drug Discovery Chemistry, Pharmaceutical Electronic Mail Pharmaceutical Research Surveys and Questionnaires Research Personnel Databases, Chemical
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Big data and artificial intelligence discover novel drugs targeting proteins without 3D structure and overcome the undruggable targets.

Stroke and vascular neurology Mar 29, 2020
The discovery of targeted drugs heavily relies on three-dimensional (3D) structures of target proteins. When the 3D structure of a protein target is unknown, it is very difficult to design its corresponding targeted drugs. Although the 3D structures ...
Artificial Intelligence Animals Computer-Aided Design Humans Molecular Targeted Therapy Protein Conformation Structure-Activity Relationship Molecular Structure Pharmaceutical Preparations Data Mining Ligands Drug Design Big Data Drug Discovery Proteins Databases, Protein
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How could artificial intelligence aid in the fight against coronavirus?

Expert review of anti-infective therapy Mar 29, 2020
SARS-CoV-2 Viral Vaccines Drug Discovery COVID-19 Computer Simulation Humans Artificial Intelligence Pneumonia, Viral Pandemics Drug Evaluation, Preclinical Coronavirus Infections Betacoronavirus
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Using Machine Learning Methods and Structural Alerts for Prediction of Mitochondrial Toxicity.

Molecular informatics Mar 23, 2020
Over the last few years more and more organ and idiosyncratic toxicities were linked to mitochondrial toxicity. Despite well-established assays, such as the seahorse and Glucose/Galactose assay, an in silico approach to mitochondrial toxicity is stil...
Quantitative Structure-Activity Relationship Drug-Related Side Effects and Adverse Reactions Databases, Chemical Machine Learning Computer Simulation Algorithms Drug Discovery Mitochondria
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How Sure Can We Be about ML Methods-Based Evaluation of Compound Activity: Incorporation of Information about Prediction Uncertainty Using Deep Learning Techniques.

Molecules (Basel, Switzerland) Mar 23, 2020
A great variety of computational approaches support drug design processes, helping in selection of new potentially active compounds, and optimization of their physicochemical and ADMET properties. Machine learning is a group of methods that are able ...
Databases, Chemical Deep Learning Models, Chemical Drug Design Drug Discovery
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Distinguishing drug/non-drug-like small molecules in drug discovery using deep belief network.

Molecular diversity Mar 19, 2020
The advent of computational methods for efficient prediction of the druglikeness of small molecules and their ever-burgeoning applications in the fields of medicinal chemistry and drug industries have been a profound scientific development, since onl...
Pharmaceutical Preparations Databases, Pharmaceutical Drug Discovery Deep Learning
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Improving detection of protein-ligand binding sites with 3D segmentation.

Scientific reports Mar 19, 2020
In recent years machine learning (ML) took bio- and cheminformatics fields by storm, providing new solutions for a vast repertoire of problems related to protein sequence, structure, and interactions analysis. ML techniques, deep neural networks espe...
Neural Networks, Computer Binding Sites Machine Learning Drug Design Protein Binding Software Proteins Drug Discovery Ligands
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