AIMC Topic: Drug Discovery

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Cross modality learning of cell painting and transcriptomics data improves mechanism of action clustering and bioactivity modelling.

Scientific reports Jul 2, 2025
In drug discovery, different data modalities (chemical structure, cell biology, quantum mechanics, etc.) are abundant, and their integration can help with understanding aspects of chemistry, biology, and their interactions. Within cell biology, cell ...
Humans Machine Learning Transcriptome RNA-Seq Drug Discovery Gene Expression Profiling Cluster Analysis
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BGATT-GR: accurate identification of glucocorticoid receptor antagonists based on data augmentation combined with BiGRU-attention.

Scientific reports Jul 1, 2025
The glucocorticoid receptor (GR) is a critical nuclear receptor that regulates a broad spectrum of physiological functions, including stress adaptation, immune response, and metabolism. Given the association between aberrant GR signaling and various ...
Receptors, Glucocorticoid Drug Discovery Deep Learning Humans
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Molecular dynamics-driven drug discovery.

Physical chemistry chemical physics : PCCP Jun 18, 2025
Molecular dynamics (MD) simulation is an important tool and has a wide range of applications in many scientific fields, including drug discovery. Herein, focusing on drug discovery, the early compound discovery stage in particular, we discuss some of...
Humans Molecular Dynamics Simulation Artificial Intelligence Drug Discovery
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LumiCharge: Spherical Harmonic Convolutional Networks for Atomic Charge Prediction in Drug Discovery.

The journal of physical chemistry letters Jun 16, 2025
Atomic charge is crucial in drug design for analyzing reactive sites and interactions between ligands and targets. While quantum mechanical methods offer high accuracy, they are generally computationally costly. Conversely, empirical approaches, whil...
Ligands Receptors, Androgen Drug Discovery Machine Learning Quantum Theory
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Discovery of Novel Anti-Acetylcholinesterase Peptides Using a Machine Learning and Molecular Docking Approach.

Drug design, development and therapy Jun 14, 2025
OBJECTIVE: Alzheimer's disease poses a significant threat to human health. Currenttherapeutic medicines, while alleviate symptoms, fail to reverse the disease progression or reduce its harmful effects, and exhibit toxicity and side effects such as ga...
Humans Machine Learning Peptides Molecular Docking Simulation Cholinesterase Inhibitors Alzheimer Disease Drug Discovery Acetylcholinesterase Structure-Activity Relationship
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Quantum Machine Learning in Drug Discovery: Applications in Academia and Pharmaceutical Industries.

Chemical reviews Jun 6, 2025
The nexus of quantum computing and machine learning─quantum machine learning─offers the potential for significant advancements in chemistry. This Review specifically explores the potential of quantum neural networks on gate-based quantum computers wi...
Drug Industry Academia Neural Networks, Computer Machine Learning Drug Discovery Quantum Theory Humans
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The latest advances with natural products in drug discovery and opportunities for the future: a 2025 update.

Expert opinion on drug discovery Jun 5, 2025
INTRODUCTION: The landscape of drug discovery is rapidly evolving, with natural products (NPs) playing a pivotal role in the development of novel therapeutics. Despite their historical significance, challenges persist in fully harnessing their potent...
Computational Biology Drug Development Neoplasms Humans Drug Discovery Artificial Intelligence Molecular Targeted Therapy Biological Products Animals Immunoconjugates High-Throughput Screening Assays
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AI-Driven Antimicrobial Peptide Discovery: Mining and Generation.

Accounts of chemical research Jun 3, 2025
ConspectusThe escalating threat of antimicrobial resistance (AMR) poses a significant global health crisis, potentially surpassing cancer as a leading cause of death by 2050. Traditional antibiotic discovery methods have not kept pace with the rapidl...
Antimicrobial Peptides Humans Drug Discovery Bacteria Artificial Intelligence Anti-Bacterial Agents
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Predicting drug-target interactions using machine learning with improved data balancing and feature engineering.

Scientific reports Jun 3, 2025
Drug-Target Interaction (DTI) prediction is a vital task in drug discovery, yet it faces significant challenges such as data imbalance and the complexity of biochemical representations. This study makes several contributions to address these issues, ...
Deep Learning Machine Learning Humans 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...
Genetic Algorithms Algorithms Drug Design Monte Carlo Method Drug Discovery
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