Artificial intelligence (AI), particularly deep learning as a subcategory of AI, provides
opportunities to discover and develop innovative drugs. The use of AI in drug discovery is …

The burgeoning accumulation of large-scale biomedical data in oncology, alongside
significant strides in deep learning (DL) technologies, has established multimodal DL (MDL) …

Drug repositioning is a strategy of repurposing approved drugs for treating new indications,
which can accelerate the drug discovery process, reduce development costs, and lower the …

Drug repositioning greatly reduces drug development costs and time by discovering new
indications for existing drugs. With the development of technology and large-scale biological …

Drug-target binding affinity prediction plays an important role in the early stages of drug
discovery, which can infer the strength of interactions between new drugs and new targets …

Proteins interact with diverse ligands to perform a large number of biological functions, such
as gene expression and signal transduction. Accurate identification of these protein–ligand …

Fluid motion can be considered as a point cloud transformation when using the SPH
method. Compared to traditional numerical analysis methods, using machine learning …

In the binding process between proteins and ligand molecules, water molecules play a
pivotal role by forming hydrogen bonds that enable proteins and ligand molecules to bind …

Accurate calculation of drug-target affinity (DTA) is crucial for various applications in the
pharmaceutical industry, including drug screening, design, and repurposing. However …

Predicting protein-ligand binding affinity is essential for understanding protein-ligand
interactions and advancing drug discovery. Recent research has demonstrated the …