AIMC Topic: Drug Discovery

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Molecular Optimization Based on a Monte Carlo Tree Search and Multiobjective Genetic Algorithm.

Journal of chemical information and modeling Jun 2, 2025
In the realm of medicinal chemistry, the predominant challenge in molecular design lies in managing extensive molecular data sets and effectively screening for, as well as preserving, molecules with potential value. Traditional methodologies typicall...
Monte Carlo Method Genetic Algorithms Drug Design Drug Discovery Algorithms
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Data Scaling and Generalization Insights for Medicinal Chemistry Deep Learning Models.

Journal of chemical information and modeling Jun 2, 2025
Predictive models hold considerable promise in enabling the faster discovery of safer, more efficacious therapeutics. To better understand and improve the performance of small-molecule predictive models for drug discovery, we conduct multiple experim...
Drug Discovery Deep Learning Chemistry, Pharmaceutical Humans Neural Networks, Computer
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Artificial intelligence revolution in drug discovery: A paradigm shift in pharmaceutical innovation.

International journal of pharmaceutics May 30, 2025
Integrating artificial intelligence (AI) into drug discovery has revolutionized pharmaceutical innovation, addressing the challenges of traditional methods that are costly, time-consuming, and suffer from high failure rates. By utilizing machine lear...
Humans Drug Discovery Drug Repositioning COVID-19 Drug Treatment Artificial Intelligence Drug Design
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Prediction of drug-target interactions based on substructure subsequences and cross-public attention mechanism.

PloS one May 30, 2025
Drug-target interactions (DTIs) play a critical role in drug discovery and repurposing. Deep learning-based methods for predicting drug-target interactions are more efficient than wet-lab experiments. The extraction of original and substructural feat...
Proteins Drug Repositioning Data Mining Pharmaceutical Preparations Humans Algorithms Drug Discovery Deep Learning
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Discovery of CYP1A1 Inhibitors for Host-Directed Therapy against Sepsis.

Journal of medicinal chemistry May 29, 2025
Bacterial sepsis remains a leading cause of death globally, exacerbated by the rise of multidrug resistance (MDR). Host-directed therapy (HDT) has emerged as a promising nonantibiotic approach to combat infections; thus, multiple HDT targets have bee...
Cytochrome P-450 CYP1A1 Phagocytosis Acinetobacter baumannii Drug Discovery Microbial Sensitivity Tests Sepsis Mice Humans Methicillin-Resistant Staphylococcus aureus Macrophages Anti-Bacterial Agents Structure-Activity Relationship Animals
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How generative Artificial Intelligence can transform drug discovery?

European journal of medicinal chemistry May 27, 2025
Generative Artificial Intelligence (Generative AI) is transforming drug discovery by enabling advanced analysis of complex biological and chemical data. This review explores key Generative AI models, including Generative Adversarial Networks (GANs), ...
Artificial Intelligence Drug Discovery Generative Artificial Intelligence Humans
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Role of artificial intelligence in cancer drug discovery and development.

Cancer letters May 23, 2025
The role of artificial intelligence (AI) in cancer drug discovery and development has garnered significant attention due to its potential to transform the traditionally time-consuming and expensive processes involved in bringing new therapies to mark...
Machine Learning Neoplasms Drug Design Drug Discovery Humans Antineoplastic Agents Drug Development Deep Learning Artificial Intelligence
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Applying computational protein design to therapeutic antibody discovery - current state and perspectives.

Frontiers in immunology May 22, 2025
Machine learning applications in protein sciences have ushered in a new era for designing molecules in silico. Antibodies, which currently form the largest group of biologics in clinical use, stand to benefit greatly from this shift. Despite the prol...
Humans Antibodies Drug Design Protein Engineering Machine Learning Drug Discovery Animals Computational Biology
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Effective and Explainable Molecular Property Prediction by Chain-of-Thought Enabled Large Language Models and Multi-Modal Molecular Information Fusion.

Journal of chemical information and modeling May 20, 2025
Molecular property prediction (MPP) plays a critical role in drug design and discovery. Due to the multimodal nature of molecular data (e.g., 1D SMILES strings and 2D molecular graphs), multimodal information fusion can generally achieve better perfo...
Large Language Models Drug Design Drug Discovery
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TCoCPIn reveals topological characteristics of chemical protein interaction networks for novel feature discovery.

Scientific reports May 18, 2025
Understanding chemical-protein interactions (CPIs) is crucial for drug discovery and biological research, yet their complexity often challenges traditional methods. We propose TCoCPIn, a novel framework integrating graph neural networks (GNN) with th...
Drug Discovery Algorithms Protein Interaction Maps Humans Computational Biology Tumor Necrosis Factor-alpha Neural Networks, Computer Ibuprofen
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