The emergence of Artificial Intelligence (AI) in drug discovery marks a pivotal shift in
pharmaceutical research, blending sophisticated computational techniques with …

The effects of ligand binding on protein structures and their in vivo functions carry numerous
implications for modern biomedical research and biotechnology development efforts such as …

Advances in deep learning models have revolutionized the study of biomolecule systems
and their mechanisms. Graph representation learning, in particular, is important for …

Determination of protein–ligand binding affinity (PLA) is a key technological tool in hit
discovery and lead optimization, which is critical to the drug development process. PLA can …

Alzheimer's disease (AD) is a common brain disease associated with cognitive impairment
and dementia. donepezil, an acetylcholinesterase (AChE) inhibitor drug as a commercial AD …

Protein N-linked glycosylation is an important post-translational mechanism in Homo
sapiens, playing essential roles in many vital biological processes. It occurs at the NX-[S/T] …

Molecular docking is a vital computational method for predicting how small molecules bind
to target proteins, aiding drug discovery. It involves screening vast small molecule …

Developing new pharmaceutical compounds is a lengthy, costly, and intensive process. In
recent years, the development of Artificial Intelligence (AI), Machine Learning (ML), and …

Accurate and reliable prediction of drug properties is crucial in the biopharmaceutical
industry because they directly impact drug efficacy and safety. However, the traditional …

Predicting protein–ligand binding affinity or free energy can save time and resources in drug
discovery and development by helping to predict new drug candidates and better …