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 ...
Machine Learning Drug Discovery Humans RNA-Seq Cluster Analysis Gene Expression Profiling Transcriptome
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GraphGIM: rethinking molecular graph contrastive learning via geometry image modeling.

BMC biology Jul 1, 2025
BACKGROUND: Learning molecular representations is crucial for accurate drug discovery. Using graphs to represent molecules is a popular solution, and many researchers have used contrastive learning to improve the generalization of molecular graph rep...
Drug Discovery Machine Learning
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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...
Drug Discovery Humans Molecular Dynamics Simulation Artificial Intelligence
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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 Quantum Theory Machine Learning
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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...
Alzheimer Disease Acetylcholinesterase Drug Discovery Humans Peptides Cholinesterase Inhibitors Structure-Activity Relationship Machine Learning Molecular Docking Simulation
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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...
Quantum Theory Drug Industry Academia Machine Learning Drug Discovery Neural Networks, Computer 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 Drug Discovery Molecular Targeted Therapy Immunoconjugates Biological Products High-Throughput Screening Assays Artificial Intelligence Humans Animals
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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...
Bacteria Antimicrobial Peptides Drug Discovery Humans 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 Drug Discovery Humans
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