Artificial Intelligence: A Novel Approachfor Drug Discovery

被引:21
|
作者
Diaz, Oscar [1 ,2 ,3 ,4 ]
Dalton, James A. R. [1 ,2 ,3 ,4 ]
Giraldo, Jesus [1 ,2 ,3 ,4 ]
机构
[1] Univ Autonoma Barcelona, Unitat Bioestadist, Lab Mol Neuropharmacol & Bioinformat, Bellaterra 08193, Spain
[2] Univ Autonoma Barcelona, Inst Neurociencies, Bellaterra 08193, Spain
[3] Inst Salud Carlos III, Ctr Invest Biomed Red Salud Mental, CIBERSAM, Bellaterra 08193, Spain
[4] Univ Autonoma Barcelona, Inst Neurociencies, I3PT, Unitat Neurociencia Traslac,Parc Tauli Hosp Univ, Bellaterra 08193, Spain
关键词
MOLECULAR-DYNAMICS;
D O I
10.1016/j.tips.2019.06.005
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Molecular dynamics (MD) simulations can mechanistically explain receptor function. However, the enormous data sets that they may imply can be a hurdle. Plante and colleagues (Molecules, 2019) recently described a machine learning approach to the analysis of MD simulations. The approach successfully classified ligands and identified functional receptor motifs and thus it seems promising for mechanism-based drug discovery.
引用
收藏
页码:550 / 551
页数:2
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