TDR Targets 6: driving drug discovery for human pathogens through intensive chemogenomic data integration

被引:36
|
作者
Landaburu, Lionel Uran [1 ,2 ]
Berenstein, Ariel J. [3 ,7 ]
Videla, Santiago [3 ]
Maru, Parag [4 ,5 ]
Shanmugam, Dhanasekaran [4 ,5 ]
Chernomoretz, Ariel [3 ,6 ]
Aguero, Fernan [1 ,2 ]
机构
[1] Univ San Martin, Inst Invest Biotecnol Rodolfo Ugalde IIB, B1650HMP, San Martin, Buenos Aires, Argentina
[2] Consejo Nacl Invest Cient & Tecn, Inst Invest Biotecnol IIBIO, B1650HMP, San Martin, Buenos Aires, Argentina
[3] Fdn Inst Leloir, Patricias Argentinas 435, RA-435 Buenos Aires, DF, Argentina
[4] Natl Chem Lab, Biochem Sci Div, CSIR, Pune, Maharashtra, India
[5] Acad Sci & Innovat Res AcSIR, Fac Sci, Ghaziabad, India
[6] Univ Buenos Aires, Fac Ciencias Exactas & Nat, Dept Fis, C1428EGA, Buenos Aires, DF, Argentina
[7] Hosp Ninos Dr Ricardo Gutierrez, CONICET GCBA, IMIPP, Lab Biol Mol,Div Patol, Buenos Aires, DF, Argentina
关键词
MODEL; POLYADENYLATION; ABUNDANCE;
D O I
10.1093/nar/gkz999
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
The volume of biological, chemical and functional data deposited in the public domain is growing rapidly, thanks to next generation sequencing and highly-automated screening technologies. These datasets represent invaluable resources for drug discovery, particularly for less studied neglected disease pathogens. To leverage these datasets, smart and intensive data integration is required to guide computational inferences across diverse organisms. The TDR Targets chemogenomics resource integrates genomic data from human pathogens and model organisms along with information on bioactive compounds and their annotated activities. This report highlights the latest updates on the available data and functionality in TDR Targets 6. Based on chemogenomic network models providing links between inhibitors and targets, the database now incorporates network-driven target prioritizations, and novel visualizations of network subgraphs displaying chemical- and target-similarity neighborhoods along with associated target-compound bioactivity links. Available data can be browsed and queried through a new user interface, that allow users to perform prioritizations of protein targets and chemical inhibitors. As such, TDR Targets now facilitates the investigation of drug repurposing against pathogen targets, which can potentially help in identifying candidate targets for bioactive compounds with previously unknown targets. TDR Targets is available at https://tdrtargets.org.
引用
收藏
页码:D992 / D1005
页数:14
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