Phenotypic screening is undergoing a resurgence in the field of targeted protein degradation as a powerful complement to target-based approaches, which are often constrained by requirements for detailed structural and ligand-binding information. Phen...
Journal of chemical information and modeling
Aug 27, 2025
Benzimidazole hybrids are promising antibacterial agents, but the growing problem of antibiotic resistance has led to the necessity of developing novel compounds with enhanced antimicrobial activity. This study utilizes AI methods to generate new ant...
Journal of chemical information and modeling
Aug 27, 2025
Neural network potentials trained on quantum-mechanical data can calculate molecular interactions with relatively high speed and accuracy. However, not all neural network potentials are suitable for molecular simulations, as they might exhibit instab...
Journal of chemical information and modeling
Aug 21, 2025
The transient receptor potential vanilloid 1 (TRPV1) ion channel is a key mediator of pain and inflammation, making it a crucial target for developing new analgesics. Despite progress in understanding TRPV1's role, novel modulators that effectively i...
Journal of chemical information and modeling
Aug 21, 2025
Predicting compound-protein interaction (CPI) plays a critical role in drug discovery and development, but traditional screening experiments consume much time and resources. Therefore, deep learning methods for CPI prediction are popular now. However...
Cancer is a leading cause of death worldwide and a major burden on the healthcare system. Current treatment methods are limited as they have low selectivity, unspecific targeting and increasing multidrug resistance. Therefore, newer modes of therapeu...
Journal of chemical information and modeling
Aug 20, 2025
Accurate prediction of molecular properties is essential in drug discovery and related fields. However, existing graph neural networks (GNNs) often struggle to simultaneously capture both local and global molecular structures. In this work, we propos...
Machine learning is a vital tool in advancing drug development by accurately predicting the physical, chemical, and biological properties of various compounds. This study utilizes MATLAB program-based algorithms to calculate topological indices and m...
Journal of chemical information and modeling
Aug 18, 2025
Antimicrobial peptides (AMPs) have emerged as vital candidates in the fight against antibiotic resistance. The traditional processes for AMP design and discovery are often time-consuming and inefficient. Here, we propose the AMPGP model, which employ...
Journal of chemical information and modeling
Aug 18, 2025
Achieving structural novelty in drug discovery remains a critical challenge. Artificial intelligence (AI) has demonstrated remarkable potential in deciphering the complex relationships between molecular structures and activities from vast amounts of ...
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