A Mapping of Drug Space from the Viewpoint of Small Molecule Metabolism

被引:28
作者
Adams, James Corey [1 ]
Keiser, Michael J. [2 ]
Basuino, Li [3 ]
Chambers, Henry F. [3 ]
Lee, Deok-Sun [4 ,5 ,6 ,7 ,8 ,9 ]
Wiest, Olaf G. [10 ]
Babbitt, Patricia C. [11 ,12 ,13 ]
机构
[1] Univ Calif San Francisco, Grad Program Pharmaceut Sci & Pharmacogenom, San Francisco, CA 94143 USA
[2] Univ Calif San Francisco, Grad Program Bioinformat, San Francisco, CA 94143 USA
[3] Univ Calif San Francisco, San Francisco Gen Hosp, San Francisco, CA USA
[4] Northeastern Univ, Ctr Complex Network Res, Boston, MA 02115 USA
[5] Northeastern Univ, Dept Phys, Boston, MA 02115 USA
[6] Northeastern Univ, Dept Biol, Boston, MA 02115 USA
[7] Northeastern Univ, Dept Comp Sci, Boston, MA 02115 USA
[8] Dana Farber Canc Inst, Ctr Canc Syst Biol, Boston, MA 02115 USA
[9] Inha Univ, Dept Nat Med Sci, Inchon, South Korea
[10] Univ Notre Dame, Dept Chem & Biochem, Notre Dame, IN 46556 USA
[11] Univ Calif San Francisco, Dept Bioengn & Therapeut Sci, San Francisco, CA 94143 USA
[12] Univ Calif San Francisco, Dept Pharmaceut Chem, San Francisco, CA 94143 USA
[13] Univ Calif San Francisco, Calif Inst Quantitat Biosci, San Francisco, CA 94143 USA
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
SYSTEMS BIOLOGY; DISCOVERY; INHIBITORS; SYNTHASE; METABOLOMICS; STRATEGIES; GENOME; MITOCHONDRIA; PATHWAYS; TARGETS;
D O I
10.1371/journal.pcbi.1000474
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Small molecule drugs target many core metabolic enzymes in humans and pathogens, often mimicking endogenous ligands. The effects may be therapeutic or toxic, but are frequently unexpected. A large-scale mapping of the intersection between drugs and metabolism is needed to better guide drug discovery. To map the intersection between drugs and metabolism, we have grouped drugs and metabolites by their associated targets and enzymes using ligand-based set signatures created to quantify their degree of similarity in chemical space. The results reveal the chemical space that has been explored for metabolic targets, where successful drugs have been found, and what novel territory remains. To aid other researchers in their drug discovery efforts, we have created an online resource of interactive maps linking drugs to metabolism. These maps predict the "effect space" comprising likely target enzymes for each of the 246 MDDR drug classes in humans. The online resource also provides species-specific interactive drug-metabolism maps for each of the 385 model organisms and pathogens in the BioCyc database collection. Chemical similarity links between drugs and metabolites predict potential toxicity, suggest routes of metabolism, and reveal drug polypharmacology. The metabolic maps enable interactive navigation of the vast biological data on potential metabolic drug targets and the drug chemistry currently available to prosecute those targets. Thus, this work provides a large-scale approach to ligand-based prediction of drug action in small molecule metabolism.
引用
收藏
页数:12
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