Journal of chemical information and modeling
Dec 26, 2025
Accurate prediction of molecular properties is essential for computational design in many areas of chemistry. Deep learning has been used in these prediction tasks for a wide variety of molecular properties, and the availability of user-friendly open...
Environmental geochemistry and health
Dec 10, 2025
Pharmaceutical pollutants are increasingly recognized as emerging contaminants in aquatic environments. Their persistence, bioactivity, and resistance to conventional treatment processes raise ecological and human health concerns, including the sprea...
The application of artificial intelligence in cheminformatics highlights the necessity of comprehensive datasets that fully utilize all available chemical information. While generalist databases such as PubChem provide extensive compound coverage, sp...
Data sparseness is a major limiting factor for deep machine learning. In the natural sciences, data distributions are heterogeneous. For instance, in chemistry and early-phase drug discovery, compound and molecular property data are typically sparse ...
Journal of chemical information and modeling
Sep 12, 2025
A carcinogenicity assessment of possibly carcinogenic chemicals (International Agency for Research on Cancer: IARC class 2B) was conducted using a consensus framework constructed from three complementary machine learning models: BiLSTM with MACCS fin...
Journal of chemical information and modeling
Jul 25, 2025
Machine learning has become an essential tool in computational drug design, enabling models to uncover patterns in molecular data and predict protein-ligand interactions. This study introduces a novel approach by integrating persistence images with M...
Penicillin-binding protein 4 (PBP4) is essential in imparting significant β-lactam antibiotics resistance in Staphylococcus aureus (S. aureus) and the mutation R200L in PBP4 is linked to β-lactam non-susceptibility in natural strains, complicating tr...
Journal of chemical information and modeling
Feb 3, 2025
In recent years, natural language processing (NLP) techniques, including large language modeling (LLM), have contributed significantly to advancements in organic chemistry research. Chemical reaction representations provide a link between NLP models ...
Histone deacetylase 3 (HDAC3) inhibitors keep significant therapeutic promise for treating oncological, neurodegenerative, and inflammatory diseases. In this work, we developed robust QSAR regression models for HDAC3 inhibitory activity and acute tox...
The purpose of this review is two-fold: (1) to summarize artificial intelligence and machine learning approaches and document the role of ligand-protein structures in directing drug discovery; (2) to present examples of drugs from the recent literatu...
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