AIMC Topic: Drug Discovery

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Enhancing Opioid Bioactivity Predictions through Integration of Ligand-Based and Structure-Based Drug Discovery Strategies with Transfer and Deep Learning Techniques.

The journal of physical chemistry. B Dec 11, 2023
The opioid epidemic has cast a shadow over public health, necessitating immediate action to address its devastating consequences. To effectively combat this crisis, it is crucial to discover better opioid drugs with reduced addiction potential. Artif...
Ligands Analgesics, Opioid Artificial Intelligence Deep Learning Drug Discovery
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A deep learning method for drug-target affinity prediction based on sequence interaction information mining.

PeerJ Dec 11, 2023
BACKGROUND: A critical aspect of drug discovery involves the prediction of drug-target affinity (DTA). Conducting wet lab experiments to determine affinity is both expensive and time-consuming, making it necessary to find alternative approaches. In ...
Biological Evolution Drug Delivery Systems Deep Learning Drug Discovery
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Integrating QSAR modelling and deep learning in drug discovery: the emergence of deep QSAR.

Nature reviews. Drug discovery Dec 8, 2023
Quantitative structure-activity relationship (QSAR) modelling, an approach that was introduced 60 years ago, is widely used in computer-aided drug design. In recent years, progress in artificial intelligence techniques, such as deep learning, the rap...
Quantum Theory Quantitative Structure-Activity Relationship Deep Learning Computing Methodologies Artificial Intelligence Drug Discovery Drug Design Humans
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Data science in drug discovery safety: Challenges and opportunities.

Experimental biology and medicine (Maywood, N.J.) Dec 7, 2023
Early de-risking of drug targets and chemistry is essential to provide drug projects with the best chance of success. Target safety assessments (TSAs) use target biology, gene and protein expression data, genetic information from humans and animals, ...
Drug Discovery Data Science Animals Artificial Intelligence Humans Computational Biology
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Computational drug discovery on human immunodeficiency virus with a customized long short-term memory variational autoencoder deep-learning architecture.

CPT: pharmacometrics & systems pharmacology Dec 5, 2023
Despite attempts to control the spread of human immunodeficiency virus (HIV) through the use of anti-HIV medications, the absence of an effective vaccine continues to present a significant obstacle. In addition, the development of drug resistance by ...
Neural Networks, Computer Artificial Intelligence Humans HIV Deep Learning HIV Infections Drug Discovery
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Fusion-Based Deep Learning Architecture for Detecting Drug-Target Binding Affinity Using Target and Drug Sequence and Structure.

IEEE journal of biomedical and health informatics Dec 5, 2023
Accurately predicting drug-target binding affinity plays a vital role in accelerating drug discovery. Many computational approaches have been proposed due to costly and time-consuming of wet laboratory experiments. In the input representation, most m...
Drug Discovery Neural Networks, Computer Humans Deep Learning
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ChatGPT or LLM in next-generation drug discovery and development: pharmaceutical and biotechnology companies can make use of the artificial intelligence-based device for a faster way of drug discovery and development.

International journal of surgery (London, England) Dec 1, 2023
Drug Industry Biotechnology Humans Drug Development Drug Discovery Artificial Intelligence
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VGAE-MCTS: A New Molecular Generative Model Combining the Variational Graph Auto-Encoder and Monte Carlo Tree Search.

Journal of chemical information and modeling Nov 22, 2023
Molecular generation is crucial for advancing drug discovery, materials science, and chemical exploration. It expedites the search for new drug candidates, facilitates tailored material creation, and enhances our understanding of molecular diversity....
Drug Development Monte Carlo Method Learning Drug Discovery Artificial Intelligence
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A novel efficient drug repurposing framework through drug-disease association data integration using convolutional neural networks.

BMC bioinformatics Nov 22, 2023
Drug repurposing is an exciting field of research toward recognizing a new FDA-approved drug target for the treatment of a specific disease. It has received extensive attention regarding the tedious, time-consuming, and highly expensive procedure wit...
Drug Discovery Neural Networks, Computer Drug Repositioning
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A knowledge-guided pre-training framework for improving molecular representation learning.

Nature communications Nov 21, 2023
Learning effective molecular feature representation to facilitate molecular property prediction is of great significance for drug discovery. Recently, there has been a surge of interest in pre-training graph neural networks (GNNs) via self-supervised...
Artificial Intelligence Electric Power Supplies Anti-HIV Agents Drug Discovery Hydrolases
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