AIMC Topic: Drug Discovery

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A machine learning method for predicting molecular antimicrobial activity.

Scientific reports Feb 24, 2025
In response to the increasing concern over antibiotic resistance and the limitations of traditional methods in antibiotic discovery, we introduce a machine learning-based method named MFAGCN. This method predicts the antimicrobial efficacy of molecul...
Anti-Infective Agents Drug Discovery Machine Learning Anti-Bacterial Agents
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Predicting Antimicrobial Class Specificity of Small Molecules Using Machine Learning.

Journal of chemical information and modeling Feb 23, 2025
While the useful armory of antibiotic drugs is continually depleted due to the emergence of drug-resistant pathogens, the development of novel therapeutics has also slowed down. In the era of advanced computational methods, approaches like machine le...
Bacteria Small Molecule Libraries Anti-Infective Agents Drug Discovery Microbial Sensitivity Tests Machine Learning Anti-Bacterial Agents
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Food-derived DPP4 inhibitors: Drug discovery based on high-throughput virtual screening and deep learning.

Food chemistry Feb 21, 2025
Dipeptidyl peptidase-4 (DPP-4) is a critical target for the treatment of type 2 diabetes. This study outlines the development of six compounds derived from food sources and modified to create promising candidates for the treatment of diabetes. These ...
Deep Learning Diabetes Mellitus, Type 2 Humans Drug Discovery High-Throughput Screening Assays Dipeptidyl Peptidase 4 Dipeptidyl-Peptidase IV Inhibitors Hypoglycemic Agents Molecular Dynamics Simulation
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Enhanced in silico QSAR-based screening of butyrylcholinesterase inhibitors using multi-feature selection and machine learning.

SAR and QSAR in environmental research Feb 21, 2025
Butyrylcholinesterase inhibition offers one of the formulated solutions to tackle the aggravating symptoms of dementia that downgrades to cholinergic neuronal loss in Alzheimer's disease. We developed a QSAR model to facilitate the identification of ...
Computer Simulation Drug Discovery Quantitative Structure-Activity Relationship Butyrylcholinesterase Cholinesterase Inhibitors Machine Learning Algorithms Humans
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Hyperbolic multivariate feature learning in higher-order heterogeneous networks for drug-disease prediction.

Artificial intelligence in medicine Feb 19, 2025
New drug discovery has always been a costly, time-consuming process with a high failure rate. Repurposing existing drugs offers a valuable alternative and reduces the risks associated with developing new drugs. Various experimental methods have been ...
Algorithms Drug Discovery Drug Repositioning Data Mining Computational Biology Humans Machine Learning Multivariate Analysis
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From part to whole: AI-driven progress in fragment-based drug discovery.

Current opinion in structural biology Feb 18, 2025
Fragment-based drug discovery is a technique that finds potent binding fragments to the binding hotspots and makes them a hit compound. The combination of fragments allows us to explore the large chemical space. Thus, it becomes an effective methodol...
Models, Molecular Drug Discovery Deep Learning Humans Artificial Intelligence
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T-ALPHA: A Hierarchical Transformer-Based Deep Neural Network for Protein-Ligand Binding Affinity Prediction with Uncertainty-Aware Self-Learning for Protein-Specific Alignment.

Journal of chemical information and modeling Feb 18, 2025
There is significant interest in targeting disease-causing proteins with small molecule inhibitors to restore healthy cellular states. The ability to accurately predict the binding affinity of small molecules to a protein target in silico enables the...
SARS-CoV-2 Drug Discovery Humans Neural Networks, Computer Proteins Ligands ErbB Receptors Deep Learning Protein Binding Uncertainty
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Artificial Intelligence for Drug Discovery: An Update and Future Prospects.

Seminars in nuclear medicine Feb 17, 2025
Artificial intelligence (AI) has become a pivotal tool for medical image analysis, significantly enhancing drug discovery through improved diagnostics, staging, prognostication, and response assessment. At a high level, AI-driven image analysis enabl...
Humans Artificial Intelligence Drug Discovery
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Emerging horizons of AI in pharmaceutical research.

Advances in pharmacology (San Diego, Calif.) Feb 16, 2025
Artificial Intelligence (AI) has revolutionized drug discovery by enhancing data collection, integration, and predictive modeling across various critical stages. It aggregates vast biological and chemical data, including genomic information, protein ...
Drug Design Drug Discovery Quantitative Structure-Activity Relationship Pharmaceutical Research Machine Learning Animals Humans Artificial Intelligence
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Identifying RNA-small Molecule Binding Sites Using Geometric Deep Learning with Language Models.

Journal of molecular biology Feb 15, 2025
RNAs are emerging as promising therapeutic targets, yet identifying small molecules that bind to them remains a significant challenge in drug discovery. This underscores the crucial role of computational modeling in predicting RNA-small molecule bind...
Models, Molecular RNA Binding Sites Small Molecule Libraries Nucleic Acid Conformation Deep Learning Computational Biology Drug Discovery
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