AIMC Topic: Drug Discovery

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Geometry-Augmented Molecular Representation Learning for Property Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Oct 9, 2024
Accurate molecular representation plays a crucial role in expediting the process of drug discovery. Graph neural networks (GNNs) have demonstrated robust capabilities in molecular representation learning, adept at capturing structural and spatial inf...
Neural Networks, Computer Drug Discovery Computational Biology Models, Molecular Machine Learning Algorithms
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A deep learning framework combining molecular image and protein structural representations identifies candidate drugs for pain.

Cell reports methods Sep 27, 2024
Artificial intelligence (AI) and deep learning technologies hold promise for identifying effective drugs for human diseases, including pain. Here, we present an interpretable deep-learning-based ligand image- and receptor's three-dimensional (3D)-str...
Humans Algorithms Receptors, G-Protein-Coupled Molecular Imaging Drug Discovery Deep Learning Pain Ligands
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Traversing chemical space with active deep learning for low-data drug discovery.

Nature computational science Sep 27, 2024
Deep learning is accelerating drug discovery. However, current approaches are often affected by limitations in the available data, in terms of either size or molecular diversity. Active deep learning has high potential for low-data drug discovery, as...
Small Molecule Libraries Drug Discovery Humans Deep Learning
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Drug-target interaction prediction with collaborative contrastive learning and adaptive self-paced sampling strategy.

BMC biology Sep 27, 2024
BACKGROUND: Drug-target interaction (DTI) prediction plays a pivotal role in drug discovery and drug repositioning, enabling the identification of potential drug candidates. However, most previous approaches often do not fully utilize the complementa...
Drug Repositioning Drug Discovery Deep Learning Humans
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Microbe-drug association prediction model based on graph convolution and attention networks.

Scientific reports Sep 27, 2024
The human microbiome plays a key role in drug development and precision medicine, but understanding its complex interactions with drugs remains a challenge. Identifying microbe-drug associations not only enhances our understanding of their mechanisms...
Deep Learning Neural Networks, Computer Computational Biology Drug Discovery Microbiota Pharmaceutical Preparations Humans
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A Practical Method for Predicting Compound Brain Concentration-Time Profiles: Combination of PK Modeling and Machine Learning.

Molecular pharmaceutics Sep 26, 2024
Given the aging populations in advanced countries globally, many pharmaceutical companies have focused on developing central nervous system (CNS) drugs. However, due to the blood-brain barrier, drugs do not easily reach the target area in the brain. ...
Tissue Distribution Drug Discovery Mice Models, Biological Central Nervous System Agents Blood-Brain Barrier Animals Brain Computer Simulation Machine Learning
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Approved drugs successfully repurposed against based on machine learning predictions.

Frontiers in cellular and infection microbiology Sep 26, 2024
Drug repurposing is a promising approach towards the discovery of novel treatments against Neglected Tropical Diseases, such as Leishmaniases, presenting the advantage of reducing both costs and duration of the drug discovery process. In previous wor...
Leishmania infantum Leishmania major Inhibitory Concentration 50 Antiprotozoal Agents Leishmaniasis Leishmania Humans Machine Learning Drug Discovery Drug Repositioning
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The Development and Application of KinomePro-DL: A Deep Learning Based Online Small Molecule Kinome Selectivity Profiling Prediction Platform.

Journal of chemical information and modeling Sep 25, 2024
Characterizing the kinome selectivity profiles of kinase inhibitors is essential in the early stages of novel small-molecule drug discovery. This characterization is critical for interpreting potential adverse events caused by off-target polypharmaco...
Drug Discovery Deep Learning Humans Small Molecule Libraries Protein Kinases Protein Kinase Inhibitors
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Data-centric challenges with the application and adoption of artificial intelligence for drug discovery.

Expert opinion on drug discovery Sep 24, 2024
INTRODUCTION: Artificial intelligence (AI) is exhibiting tremendous potential to reduce the massive costs and long timescales of drug discovery. There are however important challenges currently limiting the impact and scope of AI models.
Humans Artificial Intelligence Benchmarking Uncertainty Drug Development Bias Drug Discovery Models, Theoretical
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Artificial intelligence and psychedelic medicine.

Annals of the New York Academy of Sciences Sep 23, 2024
Artificial intelligence (AI) and psychedelic medicines are among the most high-profile evolving disruptive innovations within mental healthcare in recent years. Although AI and psychedelics may not have historically shared any common ground, there ex...
Hallucinogens Mental Disorders Drug Discovery Humans Artificial Intelligence
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