Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in Machine Learning. According to news reporting originating from Beijing,People's Republic of China,by NewsRx correspondents,research stated,"Developing new d rugs is too expensive and time -consuming. Accurately predicting the interaction between drugs and targets will likely change how the drug is discovered." Financial supporters for this research include National Key Research and Develop ment Program of China,National Key Research & Development Program of China. Our news editors obtained a quote from the research from the Beijing University of Technology,"Machine learning-based protein-ligand interaction prediction has demonstrated significant potential. In this paper,computational methods,focus ing on sequence and structure to study protein-ligand interactions,are examined . Therefore,this paper starts by presenting an overview of the data sets applie d in this area,as well as the various approaches applied for representing prote ins and ligands. Then,sequence-based and structure-based classification criteri a are subsequently utilized to categorize and summarize both the classical machi ne learning models and deep learning models employed in protein-ligand interacti on studies. Moreover,the evaluation methods and interpretability of these model s are proposed. Furthermore,delving into the diverse applications of protein-li gand interaction models in drug research is presented."
NETL
NSTL