Imbalance in chemical space: How to facilitate the identification of protein-protein interaction inhibitors

被引:28
|
作者
Kuenemann, Melaine A. [1 ,2 ]
Labbe, Celine M. [1 ,2 ]
Cerdan, Adrien H. [1 ,2 ]
Sperandio, Olivier [1 ,2 ]
机构
[1] Univ Paris Diderot, Sorbonne Paris Cite, Mol Therapeut In Silico, INSERM,UMR S 973, Paris, France
[2] INSERM, U973, Paris, France
来源
SCIENTIFIC REPORTS | 2016年 / 6卷
关键词
DRUG DISCOVERY; DATABASE; PREDICTION; LIBRARIES; RULES;
D O I
10.1038/srep23815
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Protein-protein interactions (PPIs) play vital roles in life and provide new opportunities for therapeutic interventions. In this large data analysis, 3,300 inhibitors of PPIs (iPPIs) were compared to 17 reference datasets of collectively similar to 566,000 compounds (including natural compounds, existing drugs, active compounds on conventional targets, etc.) using a chemoinformatics approach. Using this procedure, we showed that comparable classes of PPI targets can be formed using either the similarity of their ligands or the shared properties of their binding cavities, constituting a proof-of-concept that not only can binding pockets be used to group PPI targets, but that these pockets certainly condition the properties of their corresponding ligands. These results demonstrate that matching regions in both chemical space and target space can be found. Such identified classes of targets could lead to the design of PPI-class-specific chemical libraries and therefore facilitate the development of iPPIs to the stage of drug candidates.
引用
收藏
页数:17
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