Highlights•The ML-based and DL-based approaches for profiling kinase targets are
outlined.•The commonly used datasets and computational tools for kinase profiling …

Identifying protein–protein interactions (PPIs) is crucial for deciphering biological pathways.
Numerous prediction methods have been developed as cheap alternatives to biological …

Existing drug-target interaction (DTI) prediction methods generally fail to generalize well to
novel (unseen) proteins and drugs. In this study, we propose a protein-specific meta …

Compound–protein interactions (CPI) play significant roles in drug development. To avoid
side effects, it is also crucial to evaluate drug selectivity when binding to different targets …

Biomolecular nuclear magnetic resonance (NMR) spectroscopy and artificial intelligence
(AI) have a burgeoning synergy. Deep learning-based structural predictors have forever …

Drug–target interactions (DTIs) are considered a crucial component of drug design and drug
discovery. To date, many computational methods were developed for drug–target …

Diet is a well-known modifiable risk factor for cardiovascular diseases, which are the leading
cause of death worldwide. However, our current understanding of the human diet is still …

Social ties, either positive or negative, lead to signed network patterns, the subject of
balance theory. For example, strong balance introduces cycles with even numbers of …

Given the prolonged timelines and high costs associated with traditional approaches,
accelerating drug development is crucial. Computational methods, particularly drug-target …

With the emergence of next‐generation nucleotide sequencing and mass spectrometry‐
based proteomics and metabolomics tools, we have comprehensive and scalable methods …