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

Fundamental Research 2024年第4期4卷 715-737页

作者： Hongjie Wu Junkai Liu Runhua Zhang Yaoyao Lu Guozeng Cui Zhiming Cui Yijie Ding School of Electronic and Information Engineering Suzhou University of Science and TechnologySuzhou 215009China Yangtze Delta Region Institute(Quzhou) University of Electronic Science and Technology of ChinaQuzhou 32400China

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 *** particular,the time required for vaccine and drug discovery is prolonged during emergency situations such as the coronavirus 2019 ***,the performance of deep learning methods in drug virtual screening has been particularly *** 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 *** review first introduces the basic concepts of drug virtual screening,common datasets,and data representation ***,large numbers of common deep learning methods for drug virtual screening are compared and *** 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 ***,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

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