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Progress on the application of artificial intelligence technology in ligand-based and receptor structure-based drug screening
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Run-zhe LIU, Jun-ke SONG, Ai-lin LIU, Guan-hua DU*
Acta Pharmaceutica Sinica | 2021, 56(8) : 2136 - 2145
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Acta Pharmaceutica Sinica | 2021, 56(8): 2136-2145
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Progress on the application of artificial intelligence technology in ligand-based and receptor structure-based drug screening
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Run-zhe LIU, Jun-ke SONG, Ai-lin LIU, Guan-hua DU*
Affiliations
  • National Center for Pharmaceutical Screening, Beijing Key Lab of Drug Target Identification and Drug Screening, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
Published: 2021-08-12 doi: 10.16438/j.0513-4870.2021-0052
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Artificial intelligence technology is being widely applied in drug screening. This paper introduces the characteristics of artificial intelligence, and summarizes the application and progress of artificial intelligence technology especially deep learning in drug screening, from ligand-based and receptor structure-based aspects. This paper also introduces how to apply artificial intelligence to drug design from these two aspects. Finally, we discuss the main limitations, challenges, and prospects of artificial intelligence technology in the field of drug screening.

artificial intelligence  /  virtual screening  /  computer aided drug design  /  pharmacology
Run-zhe LIU, Jun-ke SONG, Ai-lin LIU, Guan-hua DU. Progress on the application of artificial intelligence technology in ligand-based and receptor structure-based drug screening[J]. Acta Pharmaceutica Sinica, 2021 , 56 (8) : 2136 -2145 . DOI: 10.16438/j.0513-4870.2021-0052
Year 2021 volume 56 Issue 8
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Article Info
doi: 10.16438/j.0513-4870.2021-0052
  • Receive Date:2021-01-11
  • Online Date:2025-12-18
  • Published:2021-08-12
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  • Received:2021-01-11
  • Revised:2021-03-08
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    National Center for Pharmaceutical Screening, Beijing Key Lab of Drug Target Identification and Drug Screening, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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