AIMC Topic: Drug Discovery

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LGGA-MPP: Local Geometry-Guided Graph Attention for Molecular Property Prediction.

Journal of chemical information and modeling Mar 22, 2024
Molecular property prediction is a fundamental task of drug discovery. With the rapid development of deep learning, computational approaches for predicting molecular properties are experiencing increasing popularity. However, these existing methods o...
Models, Molecular Neural Networks, Computer Deep Learning Drug Discovery
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Towards explainable interaction prediction: Embedding biological hierarchies into hyperbolic interaction space.

PloS one Mar 21, 2024
Given the prolonged timelines and high costs associated with traditional approaches, accelerating drug development is crucial. Computational methods, particularly drug-target interaction prediction, have emerged as efficient tools, yet the explainabi...
Proteins Drug Discovery Machine Learning Drug Development
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Outline and background for the EU-OS solubility prediction challenge.

SLAS discovery : advancing life sciences R & D Mar 20, 2024
In June 2022, EU-OS came to the decision to make public a solubility data set of 100+K compounds obtained from several of the EU-OS proprietary screening compound collections. Leveraging on the interest of SLAS for screening scientific development it...
Machine Learning Drug Discovery Humans Solubility Cheminformatics
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Predictive Modelling in pharmacokinetics: from in-silico simulations to personalized medicine.

Expert opinion on drug metabolism & toxicology Mar 20, 2024
INTRODUCTION: Pharmacokinetic parameters assessment is a critical aspect of drug discovery and development, yet challenges persist due to limited training data. Despite advancements in machine learning and in-silico predictions, scarcity of data hamp...
Pharmacokinetics Pharmaceutical Preparations Models, Biological Drug Discovery Pharmacogenetics Drug Development Models, Molecular Humans Reproducibility of Results Precision Medicine Artificial Intelligence Drug Design Machine Learning Computer Simulation
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GraphormerDTI: A graph transformer-based approach for drug-target interaction prediction.

Computers in biology and medicine Mar 18, 2024
The application of Artificial Intelligence (AI) to screen drug molecules with potential therapeutic effects has revolutionized the drug discovery process, with significantly lower economic cost and time consumption than the traditional drug discovery...
Drug Evaluation, Preclinical Artificial Intelligence Neural Networks, Computer Drug Discovery
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Enhancing Multi-species Liver Microsomal Stability Prediction through Artificial Intelligence.

Journal of chemical information and modeling Mar 18, 2024
Liver microsomal stability, a crucial aspect of metabolic stability, significantly impacts practical drug discovery. However, current models for predicting liver microsomal stability are based on limited molecular information from a single species. T...
Humans Pharmaceutical Preparations Artificial Intelligence Animals Microsomes, Liver Mice Machine Learning Drug Discovery Rats
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Deciphering the Lexicon of Protein Targets: A Review on Multifaceted Drug Discovery in the Era of Artificial Intelligence.

Molecular pharmaceutics Mar 11, 2024
Understanding protein sequence and structure is essential for understanding protein-protein interactions (PPIs), which are essential for many biological processes and diseases. Targeting protein binding hot spots, which regulate signaling and growth,...
Artificial Intelligence Drug Discovery Quantitative Structure-Activity Relationship Machine Learning Drug Design
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Augmenting DMTA using predictive AI modelling at AstraZeneca.

Drug discovery today Mar 8, 2024
Design-Make-Test-Analyse (DMTA) is the discovery cycle through which molecules are designed, synthesised, and assayed to produce data that in turn are analysed to inform the next iteration. The process is repeated until viable drug candidates are ide...
Drug Discovery Biological Assay Artificial Intelligence
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Ligand-based pharmacophore modeling and machine learning for the discovery of potent aurora A kinase inhibitory leads of novel chemotypes.

Molecular diversity Mar 6, 2024
Aurora-A (AURKA) is serine/threonine protein kinase involved in the regulation of numerous processes of cell division. Numerous studies have demonstrated strong association between AURKA and cancer. AURKA is overexpressed in many cancers, such as col...
Humans Protein Kinase Inhibitors Machine Learning Pharmacophore Drug Discovery Ligands Aurora Kinase A Models, Molecular Quantitative Structure-Activity Relationship
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Benchmarking Active Learning Protocols for Ligand-Binding Affinity Prediction.

Journal of chemical information and modeling Mar 6, 2024
Active learning (AL) has become a powerful tool in computational drug discovery, enabling the identification of top binders from vast molecular libraries. To design a robust AL protocol, it is important to understand the influence of AL parameters, a...
Drug Discovery Ligands Machine Learning
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