AIMC Topic: Drug Discovery

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AI in 3D compound design.

Current opinion in structural biology Jan 31, 2022
The success of Artificial Intelligence (AI) across a wide range of domains has fuelled significant interest in its application to designing novel compounds and screening compounds against a specific target. However, many existing AI methods either do...
Artificial Intelligence Drug Discovery Ligands Machine Learning Drug Design
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Technique of Augmenting Molecular Graph Data by Perturbating Hidden Features.

Molecular informatics Jan 27, 2022
Quantitative structure-property relationship models are useful in efficiently searching for molecules with desired properties in drug discovery and materials development. In recent years, many such models based on graph neural networks, showing good ...
Drug Discovery Quantitative Structure-Activity Relationship Neural Networks, Computer
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Chemical Reactivity Prediction: Current Methods and Different Application Areas.

Molecular informatics Jan 22, 2022
The ability to predict chemical reactivity of a molecule is highly desirable in drug discovery, both ex vivo (synthetic route planning, formulation, stability) and in vivo: metabolic reactions determine pharmacodynamics, pharmacokinetics and potentia...
Drug Design Drug Discovery Cheminformatics Machine Learning Algorithms
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Graph neural network approaches for drug-target interactions.

Current opinion in structural biology Jan 21, 2022
Developing new drugs remains prohibitively expensive, time-consuming, and often involves safety issues. Accurate prediction of drug-target interactions (DTIs) can guide the drug discovery process and thus facilitate drug development. Non-Euclidian da...
Molecular Structure Drug Discovery Drug Interactions Drug Development Neural Networks, Computer
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Turbo prediction: a new approach for bioactivity prediction.

Journal of computer-aided molecular design Jan 21, 2022
Nowadays, activity prediction is key to understanding the mechanism-of-action of active structures discovered from phenotypic screening or found in natural products. Machine learning is currently one of the most important and rapidly evolving topics ...
Drug Discovery Cluster Analysis Machine Learning Algorithms
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Mycobacterium abscessus drug discovery using machine learning.

Tuberculosis (Edinburgh, Scotland) Jan 20, 2022
The prevalence of infections by nontuberculous mycobacteria is increasing, having surpassed tuberculosis in the United States and much of the developed world. Nontuberculous mycobacteria occur naturally in the environment and are a significant proble...
Machine Learning Drug Discovery Bayes Theorem Antitubercular Agents Humans Mycobacterium abscessus
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Novel Big Data-Driven Machine Learning Models for Drug Discovery Application.

Molecules (Basel, Switzerland) Jan 18, 2022
Most contemporary drug discovery projects start with a 'hit discovery' phase where small chemicals are identified that have the capacity to interact, in a chemical sense, with a protein target involved in a given disease. To assist and accelerate thi...
Drug Discovery Receptors, Opioid, kappa Protein Conformation Algorithms Big Data Humans Protein Binding Computer Simulation Receptor, Adenosine A2A Ligands Machine Learning
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Transfer inhibitory potency prediction to binary classification: A model only needs a small training set.

Computer methods and programs in biomedicine Jan 17, 2022
One of the most laborious for drug discovery is to select compounds from a library for experimental evaluation. Hence, we propose a machine learning model only needs to be trained on a small dataset to predict the inhibition constant (Ki) and half ma...
Support Vector Machine Machine Learning Drug Discovery
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Ligand Based Virtual Screening Using Self-organizing Maps.

The protein journal Jan 13, 2022
Conventional drug discovery methods rely primarily on in-vitro experiments with a target molecule and an extensive set of small molecules to choose the suitable ligand. The exploration space for the selected ligand being huge; this approach is highly...
Drug Discovery Support Vector Machine Ligands Neural Networks, Computer Algorithms
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Advancing pharmacy and healthcare with virtual digital technologies.

Advanced drug delivery reviews Jan 5, 2022
Digitalisation of the healthcare sector promises to revolutionise patient healthcare globally. From the different technologies, virtual tools including artificial intelligence, blockchain, virtual, and augmented reality, to name but a few, are provid...
Humans Artificial Intelligence Drug Discovery Virtual Reality Machine Learning Research Design Biomedical Technology Health Information Exchange Clinical Trials as Topic Health Care Sector Remote Sensing Technology United States United States Food and Drug Administration Drug Development Digital Technology Time Factors Drug Industry Mobile Applications
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