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

来源：

TRENDS IN PHARMACOLOGICAL SCIENCES | 2019年 / 40卷 / 08期

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

页码：550 / 551

页数：2

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