Having an accurate reaction coordinate (RC) is essential for reliable kinetic characterization of molecular processes, but there are few quantitative metrics to evaluate RC quality. In this study, we consider the dimensionless γ metric from the Expon...
Machine learning (ML) is increasingly used in DNA-encoded library (DEL) screening for ligand discovery, but its success depends on access to suitable data sets, which are often proprietary and costly. To overcome this, we present the first fully open...
Proceedings of the National Academy of Sciences of the United States of America
Oct 6, 2025
AI models have shown great potential in structure-based drug design, generating ligands with high binding affinities. However, existing models have often overlooked a crucial physical prior: Atoms must maintain a minimum pairwise distance to avoid at...
Co-folding models represent a major innovation in deep-learning-based protein-ligand structure prediction. The recent publications of RoseTTAFold All-Atom, AlphaFold3, and others have shown high-quality results on predicting the structures of protein...
Journal of chemical information and modeling
Oct 3, 2025
Accurately predicting protein-ligand binding affinity (PLA) is essential in drug discovery for identifying lead compounds. The sequence and structural contexts of an amino acid residue (i.e., microenvironment) describe the surrounding chemical proper...
Structure-based virtual screening approaches like molecular docking rely on accurately identifying and precisely calculating binding pockets to efficiently search for potential ligands. In this paper, we introduce GENEOnet, a machine learning model d...
Journal of chemical information and modeling
Sep 29, 2025
FMRFamide-activated sodium channels (FaNaCs) represent a unique class of neuropeptide-gated ion channels within the degenerin/epithelial sodium channel (DEG/ENaC) superfamily. While cryo-electron microscopy has revealed static binding architectures, ...
Journal of agricultural and food chemistry
Sep 26, 2025
Traditional chemical pesticides have raised significant environmental and health concerns, driving the pursuit of safer alternatives. Aphids, notorious for causing extensive agricultural damage and transmitting plant diseases, represent prime targets...
Journal of chemical information and modeling
Sep 25, 2025
The main protease (Mpro) is a critical target in the design of antiviral drugs against coronaviruses, while accurately predicting the binding affinity between small molecules and this target remains a key challenge. In the recent Polaris challenge of...
Journal of chemical information and modeling
Sep 22, 2025
In this work, we introduce auxiliary discriminator sequence generative adversarial networks (ADSeqGAN), a novel approach for molecular generation in small-sample data sets. Traditional generative models often struggle with limited training data, part...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.