Algorithms for network analysis in systems-ADME/Tox using the MetaCore and MetaDrug platforms

被引:104
作者
Ekins, S.
Bugrim, A.
Brovold, L.
Kirillov, E.
Nikolsky, Y.
Rakhmatulin, E.
Sorokina, S.
Ryabov, A.
Serebryiskaya, T.
Melnikov, A.
Metz, J.
Nikolskaya, T.
机构
[1] GeneGo Inc, St Joseph, MI USA
[2] Univ Maryland, Sch Pharm, Dept Pharmaceut Sci, Baltimore, MD 21201 USA
关键词
networks; absorption; distribution; metabolism; excretion and toxicity (ADME/Tox); MetaCore (TM); MetaDrug (TM);
D O I
10.1080/00498250600861660
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
The authors have previously applied two integrated platforms, MetaCore (TM) and MetaDrug (TM), for the assembly and analysis of human biological networks as a useful method for the integration and functional interpretation of high-throughput experimental data. The present study demonstrates in detail the specific algorithms that are used in both software platforms. Using a standard set of genes as input, namely CYP3A4 (an enzyme), PXR (a nuclear hormone receptor), MDR1 (a transporter) and hERG (an ion channel) related to the absorption, distribution, metabolism, excretion and toxicity (ADME/Tox) of xenobiotics, we have now generated networks with each algorithm. The relative advantages and disadvantages of these algorithms are explained using these examples as well as appropriate instances of utility to illustrate further the particular circumstances for their use. In addition, the benefits of the different network algorithms are identified when compared with algorithms available in other products, where this information is available.
引用
收藏
页码:877 / 901
页数:25
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