AIMC Topic: Drug Discovery

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Advancing promiscuous aggregating inhibitor analysis with intelligent machine learning classification.

Briefings in bioinformatics May 1, 2025
Small molecules have been playing a crucial role in drug discovery; however, some exhibit nonspecific inhibitory effects during hit screening due to the formation of colloidal aggregators. Such false positives often lead to significant research costs...
Humans Drug Discovery ROC Curve Support Vector Machine Machine Learning Algorithms
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Optimizing Treatment: The Role of Pharmacology, Genomics, and AI in Improving Patient Outcomes.

Drug development research May 1, 2025
Recent advances in pharmacology are revolutionizing drug discovery and treatment strategies through personalized medicine, pharmacogenomics, and artificial intelligence (AI). The objective of the present study is to review the role of personalized me...
Genomics Treatment Outcome Precision Medicine Humans Drug Discovery Artificial Intelligence Pharmacogenetics
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Bioactivity predictions and virtual screening using machine learning predictive model.

Journal of biomolecular structure & dynamics May 1, 2025
Recently, there has been significant attention on machine learning algorithms for predictive modeling. Prediction models for enzyme inhibitors are limited, and it is essential to account for chemical biases while developing them. The lack of repeatab...
Molecular Dynamics Simulation Drug Evaluation, Preclinical Dipeptidyl Peptidase 4 Molecular Docking Simulation Drug Discovery Dipeptidyl-Peptidase IV Inhibitors Humans Machine Learning Algorithms
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Discovery of hematopoietic progenitor kinase 1 inhibitors using machine learning-based screening and free energy perturbation.

Journal of biomolecular structure & dynamics May 1, 2025
Hematopoietic progenitor kinase 1 (HPK1) is a key negative regulator of T-cell receptor (TCR) signaling and a promising target for cancer immunotherapy. The development of novel HPK1 inhibitors is challenging yet promising. In this study, we used a c...
Molecular Dynamics Simulation Protein Kinase Inhibitors Thermodynamics Signal Transduction Protein Serine-Threonine Kinases Machine Learning Structure-Activity Relationship Drug Discovery T-Lymphocytes Protein Binding Molecular Docking Simulation Humans
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AI-Driven Applications in Clinical Pharmacology and Translational Science: Insights From the ASCPT 2024 AI Preconference.

Clinical and translational science Apr 1, 2025
Artificial intelligence (AI) is driving innovation in clinical pharmacology and translational science with tools to advance drug development, clinical trials, and patient care. This review summarizes the key takeaways from the AI preconference at the...
Pharmacology, Clinical Translational Science, Biomedical Translational Research, Biomedical Clinical Trials as Topic Humans Drug Discovery Drug Development Artificial Intelligence
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Lit-OTAR framework for extracting biological evidences from literature.

Bioinformatics (Oxford, England) Mar 29, 2025
SUMMARY: The lit-OTAR framework, developed through a collaboration between Europe PMC and Open Targets, leverages deep learning to revolutionize drug discovery by extracting evidence from scientific literature for drug target identification and valid...
Drug Discovery Deep Learning Computational Biology Humans Software Publications Data Mining
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H2GnnDTI: hierarchical heterogeneous graph neural networks for drug-target interaction prediction.

Bioinformatics (Oxford, England) Mar 29, 2025
MOTIVATION: Identifying drug-target interactions (DTIs) is a crucial step in drug repurposing and drug discovery. The significant increase in demand and the expensive nature for experimentally identifying DTIs necessitate computational tools for auto...
Neural Networks, Computer Software Algorithms Graph Neural Networks Proteins Drug Discovery Drug Repositioning Computational Biology Pharmaceutical Preparations
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Geometric deep learning and multiple-instance learning for 3D cell-shape profiling.

Cell systems Mar 19, 2025
The three-dimensional (3D) morphology of cells emerges from complex cellular and environmental interactions, serving as an indicator of cell state and function. In this study, we used deep learning to discover morphology representations and understan...
Drug Discovery Deep Learning Cell Shape Multiple-Instance Learning Algorithms Imaging, Three-Dimensional Humans Melanoma
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Deep learning in GPCR drug discovery: benchmarking the path to accurate peptide binding.

Briefings in bioinformatics Mar 4, 2025
Deep learning (DL) methods have drastically advanced structure-based drug discovery by directly predicting protein structures from sequences. Recently, these methods have become increasingly accurate in predicting complexes formed by multiple protein...
Humans Ligands Peptides Protein Binding Receptors, G-Protein-Coupled Drug Discovery Benchmarking Deep Learning
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Data imbalance in drug response prediction: multi-objective optimization approach in deep learning setting.

Briefings in bioinformatics Mar 4, 2025
Drug response prediction (DRP) methods tackle the complex task of associating the effectiveness of small molecules with the specific genetic makeup of the patient. Anti-cancer DRP is a particularly challenging task requiring costly experiments as und...
Computational Biology Humans Antineoplastic Agents Neoplasms Deep Learning Drug Discovery Algorithms
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