Using Small Molecules and Chemical Genetics To Interrogate Signaling Networks

被引:20
作者
Carlson, Scott M.
White, Forest M. [1 ]
机构
[1] MIT, Dept Biol Engn, Cambridge, MA 02139 USA
关键词
Affinity enrichment; Analogue-sensitive kinase; Chemical genetics; Chemical proteomics; Kinase substrate; Phosphoproteomics; Signaling network; Stable isotopic labeling; UNNATURAL NUCLEOTIDE SPECIFICITY; CELL LUNG-CANCER; KINASE INHIBITORS; MASS-SPECTROMETRY; TYROSINE KINASE; SACCHAROMYCES-CEREVISIAE; AFFINITY PURIFICATION; TARGETED THERAPY; PROTEIN-KINASES; PROTEOMICS;
D O I
10.1021/cb1002834
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 limited clinical success of therapeutics targeting cellular signaling processes is due to multiple factors, including off-target effects and complex feedback regulation encoded within the signaling network. To understand these effects, chemical proteomics and chemical genetics tools have been developed to map the direct targets of kinase inhibitors, determine the network-level response to inhibitor treatment, and to infer network topology. Here we provide an overview of chemical phosphoproteomic and chemical genetic methods, including specific examples where these methods have been applied to yield biological insight regarding network structure and the system-wide effects of targeted therapeutics. The challenges and caveats associated with each method are described, along with approaches being used to resolve some of these issues. With the broad array of available techniques the next decade should see a rapid improvement in our understanding of signaling networks regulation and response to targeted perturbations, leading to more efficacious therapeutic strategies.
引用
收藏
页码:75 / 85
页数:11
相关论文
共 90 条
[41]   TRANSFORMING GENE-PRODUCT OF ROUS-SARCOMA VIRUS PHOSPHORYLATES TYROSINE [J].
HUNTER, T ;
SEFTON, BM .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA-BIOLOGICAL SCIENCES, 1980, 77 (03) :1311-1315
[42]   Innovation - Mapping normal and cancer cell signalling networks: towards single-cell proteomics [J].
Irish, JM ;
Kotecha, N ;
Nolan, GP .
NATURE REVIEWS CANCER, 2006, 6 (02) :146-155
[43]   A biological approach to computational models of proteomic networks [J].
Janes, KA ;
Lauffenburger, DA .
CURRENT OPINION IN CHEMICAL BIOLOGY, 2006, 10 (01) :73-80
[44]   Systems model of signaling identifies a molecular basis set for cytokine-induced apoptosis [J].
Janes, KA ;
Albeck, JG ;
Gaudet, S ;
Sorger, PK ;
Lauffenburger, DA ;
Yaffe, MB .
SCIENCE, 2005, 310 (5754) :1646-1653
[45]   A high-throughput quantitative multiplex kinase assay for monitoring information flow in signaling networks - Application to sepsis-apoptosis [J].
Janes, KA ;
Albeck, JG ;
Peng, LLX ;
Sorger, PK ;
Lauffenburger, DA ;
Yaffe, MB .
MOLECULAR & CELLULAR PROTEOMICS, 2003, 2 (07) :463-473
[46]   CELLULAR INFORMATION IN THE GENOME OF RECOVERED AVIAN-SARCOMA VIRUS DIRECTS THE SYNTHESIS OF TRANSFORMING PROTEIN [J].
KARESS, RE ;
HAYWARD, WS ;
HANAFUSA, H .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 1979, 76 (07) :3154-3158
[47]   Substrate and functional diversity of lysine acetylation revealed by a proteomics survey [J].
Kim, Sung Chan ;
Sprung, Robert ;
Chen, Yue ;
Xu, Yingda ;
Ball, Haydn ;
Pei, Jimin ;
Cheng, Tzuling ;
Kho, Yoonjung ;
Xiao, Hao ;
Xiao, Lin ;
Grishin, Nick V. ;
White, Michael ;
Yang, Xiang-Jiao ;
Zhao, Yingming .
MOLECULAR CELL, 2006, 23 (04) :607-618
[48]   EGFR mutation and resistance of non-small-cell lung cancer to gefitinib [J].
Kobayashi, S ;
Boggon, TJ ;
Dayaram, T ;
Janne, PA ;
Kocher, O ;
Meyerson, M ;
Johnson, BE ;
Eck, MJ ;
Tenen, DG ;
Halmos, B .
NEW ENGLAND JOURNAL OF MEDICINE, 2005, 352 (08) :786-792
[49]   High-content single-cell drug screening with phosphospecific flow cytometry [J].
Krutzik, Peter O. ;
Crane, Janelle M. ;
Clutter, Matthew R. ;
Nolan, Garry P. .
NATURE CHEMICAL BIOLOGY, 2008, 4 (02) :132-142
[50]   Modeling HER2 effects on cell behavior from mass Spectrometry phosphotyrosine data [J].
Kumar, Neil ;
Wolf-Yadlin, Alejandro ;
White, Forest M. ;
Lauffenburger, Douglas A. .
PLOS COMPUTATIONAL BIOLOGY, 2007, 3 (01) :35-48