A review of deep learningg methods for ligand based drug virtual screening  

作　　者：Hongjie Wu Junkai Liu Runhua Zhang Yaoyao Lu Guozeng Cui Zhiming Cui Yijie Ding 

机构地区：[1]School of Electronic and Information Engineering,Suzhou University of Science and Technology,Suzhou 215009,China [2]Yangtze Delta Region Institute(Quzhou),University of Electronic Science and Technology of China,Quzhou 32400,China

出　　处：《Fundamental Research》2024年第4期715-737,共23页自然科学基础研究（英文版）

基　　金：the National Natural Science Foundation of China(62073231,62176175,62172076);National Research Project(2020YFC2006602);Provincial Key Laboratory for Computer Information Processing Technology,Soochow University(KJS2166);Opening Topic Fund of Big Data Intelligent Engineering Laboratory of Jiangsu Province(SDGC2157);Postgraduate Research&Practice Innovation Program of Jiangsu Province.

摘　　要：Drug discovery is costly and time consuming,and modern drug discovery endeavors are progressively reliant on computational methodologies,aiming to mitigate temporal and financial expenditures associated with the process.In particular,the time required for vaccine and drug discovery is prolonged during emergency situations such as the coronavirus 2019 pandemic.Recently,the performance of deep learning methods in drug virtual screening has been particularly prominent.It has become a concern for researchers how to summarize the existing deep learning in drug virtual screening,select different models for different drug screening problems,exploit the advantages of deep learning models,and further improve the capability of deep learning in drug virtual screening.This review first introduces the basic concepts of drug virtual screening,common datasets,and data representation methods.Then,large numbers of common deep learning methods for drug virtual screening are compared and analyzed.In addition,a dataset of different sizes is constructed independently to evaluate the performance of each deep learning model for the difficult problem of large-scale ligand virtual screening.Finally,the existing challenges and future directions in the field of virtual screening are presented.

关 键 词：Virtual screening Deeplearning Drug discovery Drug-targetinteraction Drug-target affinity 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]