Therapeutic Target

Identifying effective therapeutic targets is a crucial step in drug discovery, focusing on pinpointing specific molecules or pathways involved in disease. Current research leverages machine learning, including techniques like graph machine learning and small language models, alongside molecular docking and quantum algorithms, to predict ligand-protein interactions and identify promising targets from vast datasets like BindingDB and genomic information. This work is significantly impacting drug development across various diseases, accelerating the identification of novel drug candidates and improving the efficiency of preclinical research by prioritizing compounds with desirable properties.