Abstract Machine learning (ML) is a promising approach for predicting small molecule
properties in drug discovery. Here, we provide a comprehensive overview of various ML …

Abstract Structure‐based drug design is a widely applied approach in the discovery of new
lead compounds for known therapeutic targets. In most structure‐based drug design …

Recently, topological data analysis (TDA) has become a trending topic in data science and
engineering. However, the key technique of TDA, ie, persistent homology, is defined on …

Persistent topological Laplacians constitute a new class of tools in topological data analysis
(TDA), motivated by the necessity to address challenges encountered in persistent …

Amino acids as biomolecules are essential building blocks of proteins, which are
fundamental to life and living organisms. The pKa values of amino acid residues in proteins …

When designing a machine learning‐based scoring function, we access a limited number of
protein‐ligand complexes with experimentally determined binding affinity values …

Protein (receptor)--ligand interaction prediction is a critical component in computer-aided
drug design, significantly influencing molecular docking and virtual screening processes …

Recently, topological data analysis has become a trending topic in data science and
engineering. However, the key technique of topological data analysis, ie, persistent …

Improving the generalization ability of scoring functions remains a major challenge in protein–
ligand binding affinity prediction. Many machine learning methods are limited by their …

Skin aging refers to a degenerative process that can be affected and regulated by intrinsic
and extrinsic factors. The mesenchymal stem cell secretome covers a considerable number …