AIMC Topic: Drug Discovery
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Machine Learning-Based Discovery of a Novel Noncovalent MurA Inhibitor as an Antibacterial Agent.
Chemical biology & drug design
Mar 1, 2025
The bacterial cell wall is crucial for maintaining the integrity of bacterial cells. UDP-N-acetylglucosamine 1-carboxyethylene transferase (MurA) is an important enzyme involved in bacterial cell wall synthesis. Therefore, it is an important target f...
Meta-MolNet: A Cross-Domain Benchmark for Few Examples Drug Discovery.
IEEE transactions on neural networks and learning systems
Mar 1, 2025
Predicting the pharmacological activity, toxicity, and pharmacokinetic properties of molecules is a central task in drug discovery. Existing machine learning methods are transferred from one resource rich molecular property to another data scarce pro...
SSL-VQ: vector-quantized variational autoencoders for semi-supervised prediction of therapeutic targets across diverse diseases.
Bioinformatics (Oxford, England)
Feb 4, 2025
MOTIVATION: Identifying effective therapeutic targets poses a challenge in drug discovery, especially for uncharacterized diseases without known therapeutic targets (e.g. rare diseases, intractable diseases).
Discovery of New HER2 Inhibitors via Computational Docking, Pharmacophore Modeling, and Machine Learning.
Molecular informatics
Feb 1, 2025
The human epidermal growth factor receptor 2 (HER2) is a critical oncogene implicated in the development of various aggressive cancers, particularly breast cancer. Discovering novel HER2 inhibitors is crucial for expanding therapeutic options for HER...
Reviewing on AI-Designed Antibiotic Targeting Drug-Resistant Superbugs by Emphasizing Mechanisms of Action.
Drug development research
Feb 1, 2025
The emergence of drug-resistant bacteria, often referred to as "superbugs," poses a profound and escalating challenge to global health systems, surpassing the capabilities of traditional antibiotic discovery methods. As resistance mechanisms evolve r...
Engineering the future of medicine: Natural products, synthetic biology and artificial intelligence for next-generation therapeutics.
Clinical and translational medicine
Feb 1, 2025
The eXchange Unit between Thiolation domains approach and artificial intelligence (AI)-driven tools like Synthetic Intelligence are transforming nonribosomal peptide synthetase and polyketide synthase engineering, enabling the creation of novel bioac...
Identification of CXCR4 inhibitory activity in natural compounds using cheminformatics-guided machine learning algorithms.
Integrative biology : quantitative biosciences from nano to macro
Jan 8, 2025
Neurodegenerative disorders are characterised by progressive damage to neurons that leads to cognitive impairment and motor dysfunction. Current treatment options focus only on symptom management and palliative care, without addressing their root cau...
canSAR 2024-an update to the public drug discovery knowledgebase.
Nucleic acids research
Jan 6, 2025
canSAR (https://cansar.ai) continues to serve as the largest publicly available platform for cancer-focused drug discovery and translational research. It integrates multidisciplinary data from disparate and otherwise siloed public data sources as wel...
CGPDTA: An Explainable Transfer Learning-Based Predictor With Molecule Substructure Graph for Drug-Target Binding Affinity.
Journal of computational chemistry
Jan 5, 2025
Identifying interactions between drugs and targets is crucial for drug discovery and development. Nevertheless, the determination of drug-target binding affinities (DTAs) through traditional experimental methods is a time-consuming process. Conventio...
AI in fungal drug development: opportunities, challenges, and future outlook.
Frontiers in cellular and infection microbiology
Jan 1, 2025
The application of artificial intelligence (AI) in fungal drug development offers innovative strategies to address the escalating threat of fungal infections and the challenge of antifungal resistance. This review evaluates the current landscape of f...
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