AIMC Topic: Drug Design
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PROFIS: Design of Target-Focused Libraries by Probing Continuous Fingerprint Space with Recurrent Neural Networks.
Journal of chemical information and modeling
May 12, 2025
This study introduces PROFIS, a new generative model capable of the design of structurally novel and target-focused compound libraries. The model relies on a recurrent neural network that was trained to decode embedded molecular fingerprints into SMI...
Knowledge-aware contrastive heterogeneous molecular graph learning.
PLoS computational biology
May 1, 2025
Molecular representation learning is pivotal in predicting molecular properties and advancing drug design. Traditional methodologies, which predominantly rely on homogeneous graph encoding, are limited by their inability to integrate external knowled...
Susana Vázquez Torres: the power of computational protein design.
Bulletin of the World Health Organization
May 1, 2025
Susana Vázquez Torres talks to Ana Lesher Treviño about AI-guided protein design for antivenoms and her aim to improve access to lifesaving treatments in low-resource settings.
Artificial intelligence to predict inhibitors of drug-metabolizing enzymes and transporters for safer drug design.
Expert opinion on drug discovery
May 1, 2025
INTRODUCTION: Drug-metabolizing enzymes (DMEs) and transporters (DTs) play integral roles in drug metabolism and drug-drug interactions (DDIs) which directly impact drug efficacy and safety. It is well-established that inhibition of DMEs and DTs ofte...
Self-awareness of retrosynthesis via chemically inspired contrastive learning for reinforced molecule generation.
Briefings in bioinformatics
Mar 4, 2025
The recent progress of deep generative models in modeling complex real-world data distributions has enabled the generation of novel compounds with potential therapeutic applications for various diseases. However, most studies fail to optimize the pro...
Deep-Learning-Based Approaches for Rational Design of Stapled Peptides With High Antimicrobial Activity and Stability.
Microbial biotechnology
Mar 1, 2025
Antimicrobial peptides (AMPs) face stability and toxicity challenges in clinical use. Stapled modification enhances their stability and effectiveness, but its application in peptide design is rarely reported. This study built ten prediction models fo...
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...
Trends of Artificial Intelligence (AI) Use in Drug Targets, Discovery and Development: Current Status and Future Perspectives.
Current drug targets
Jan 1, 2025
The applications of artificial intelligence (AI) in pharmaceutical sectors have advanced drug discovery and development methods. AI has been applied in virtual drug design, molecule synthesis, advanced research, various screening methods, and decisio...
Ligand identification in CryoEM and X-ray maps using deep learning.
Bioinformatics (Oxford, England)
Dec 26, 2024
MOTIVATION: Accurately identifying ligands plays a crucial role in the process of structure-guided drug design. Based on density maps from X-ray diffraction or cryogenic-sample electron microscopy (cryoEM), scientists verify whether small-molecule li...
Machine learning trims the peptide drug design process to a sweet spot.
Nature chemistry
Sep 1, 2024
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