Getting SMARt in drug discovery: chemoinformatics approaches for mining structure-multiple activity relationships

被引:20
|
作者
Saldivar-Gonzalez, Fernanda I. [1 ]
Jesus Naveja, J. [1 ,2 ,3 ]
Palomino-Hernandeza, Oscar [1 ]
Medina-Franco, Jose L. [1 ]
机构
[1] Univ Nacl Autonoma Mexico, Fac Quim, Dept Farm, Ave Univ 3000, Mexico City 04510, DF, Mexico
[2] Univ Nacl Autonoma Mexico, Fac Med, PECEM, Ave Univ 3000, Mexico City 04510, DF, Mexico
[3] Helmholtz Zentrum Munchen, Inst Bioinformat & Syst Biol, D-85764 Neuherberg, Germany
来源
RSC ADVANCES | 2017年 / 7卷 / 02期
关键词
LIGAND INTERACTION FINGERPRINTS; CONSENSUS-ACTIVITY-CLIFFS; ACTIVITY LANDSCAPES; PROTEIN-LIGAND; COMPOUND DATABASES; SIMILARITY; INDEXES; GENERATORS; INHIBITORS; NETWORKS;
D O I
10.1039/c6ra26230a
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
In light of the high relevance of polypharmacology, multi-target screening is a major trend in drug discovery. As such, the increasing amount of available structure-activity data requires the application of chemoinformatic approaches to mine structure-multiple activity relationships. To this end, activity landscape methods, initially developed to explore the structure-activity relationships for compounds screened against one target, have been adapted to mine Structure-Multiple Activity Relationships (SMARt). Herein, we survey advances in the chemoinformatic approaches to retrieve SMARt from screening data sets. Case studies relevant to modern drug discovery are discussed. The methods covered in this survey are general and can be implemented to explore the SMARt of other data sets screened across multiple biologically endpoints.
引用
收藏
页码:632 / 641
页数:10
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