In the last five years, there has been tremendous growth in machine learning and artificial
intelligence as applied to polymer science. Here, we highlight the unique challenges …

The application of Explainable Artificial Intelligence (XAI) in the field of chemistry has
garnered growing interest for its potential to justify the prediction of black-box machine …

Graph neural networks (GNNs) have been widely used in molecular property prediction, but
explaining their black-box predictions is still a challenge. Most existing explanation methods …

Lipophilicity (log D) and aqueous solubility (log S w) play a central role in drug development.
The accurate prediction of these properties remains to be solved due to data scarcity …

Carcinogenicity assessment of any compound is a laborious and expensive exercise with
several associated ethical and practical concerns. While artificial intelligence (AI) offers …

Chronic liver disease (CLD) is a major global health challenge, characterized by chronic
inflammation that can progress to liver fibrosis, cirrhosis, and ultimately hepatocellular …

Traditionally, the exogenous allosteric modulators of G protein-coupled receptors (GPCRs)
have been extensively investigated due to their pharmacological significance. However, to …

Traditionally, the exogenous allosteric modulators of G protein-coupled receptors (GPCRs)
have been extensively investigated due to their pharmacological signi cance. However, to …