ScienceDaily (June 21, 2010) — A surprising discovery about the complex make-up of our cells could lead to the development of new types of medicines, a study suggests.
The findings suggest that medicines would be more effective if they were designed differently. Drugs could have a greater effect on cell function by targeting groups of proteins working together, rather than individual proteins.
Results were obtained by studying yeast, which has many corresponding proteins in human cells. Researchers, including scientists from the University of Edinburgh, used advanced technology to identify hundreds of different proteins, and then used statistical analysis to identify the more important links between them, mapping almost 2000 connections in all.
Scientists expected to find simple links between individual proteins but were surprised to find that proteins were inter-connected in a complex web.
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Read more here/Leia mais aqui: Science Daily
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Vol. 328. no. 5981, pp. 1043 - 1046
DOI: 10.1126/science.1176495
A Global Protein Kinase and Phosphatase Interaction Network in Yeast
Ashton Breitkreutz,1,* Hyungwon Choi,2,* Jeffrey R. Sharom,1,3,* Lorrie Boucher,1,* Victor Neduva,4,*Brett Larsen,1 Zhen-Yuan Lin,1 Bobby-Joe Breitkreutz,1 Chris Stark,1 Guomin Liu,1 Jessica Ahn,1Danielle Dewar-Darch,1 Teresa Reguly,1 Xiaojing Tang,1 Ricardo Almeida,4 Zhaohui Steve Qin,5Tony Pawson,1,3 Anne-Claude Gingras,1,3, Alexey I. Nesvizhskii,2,6, Mike Tyers1,3,4,
The interactions of protein kinases and phosphatases with their regulatory subunits and substrates underpin cellular regulation. We identified a kinase and phosphatase interaction (KPI) network of 1844 interactions in budding yeast by mass spectrometric analysis of protein complexes. The KPI network contained many dense local regions of interactions that suggested new functions. Notably, the cell cycle phosphatase Cdc14 associated with multiple kinases that revealed roles for Cdc14 in mitogen-activated protein kinase signaling, the DNA damage response, and metabolism, whereas interactions of the target of rapamycin complex 1 (TORC1) uncovered new effector kinases in nitrogen and carbon metabolism. An extensive backbone of kinase-kinase interactions cross-connects the proteome and may serve to coordinate diverse cellular responses.
1 Centre for Systems Biology, Samuel Lunenfeld Research Institute, 600 University Avenue, Toronto, Ontario, M5G 1X5, Canada.
2 Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA.
3 Department of Molecular Genetics, University of Toronto, 1 Kings College Circle, Toronto, Ontario, M5S 1A8, Canada.
4 Wellcome Trust Centre for Cell Biology and School of Biological Sciences, University of Edinburgh, Mayfield Road, Edinburgh, EH9 3JR Scotland, UK.
5 Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA.
6 Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
* These authors contributed equally to this work.
To whom correspondence should be addressed. E-mail: gingras@lunenfeld.ca (A.C.G.), nesvi@med.umich.edu(A.I.N.), tyers@lunenfeld.ca, m.tyers@ed.ac.uk (M.T.)
The interactions of protein kinases and phosphatases with their regulatory subunits and substrates underpin cellular regulation. We identified a kinase and phosphatase interaction (KPI) network of 1844 interactions in budding yeast by mass spectrometric analysis of protein complexes. The KPI network contained many dense local regions of interactions that suggested new functions. Notably, the cell cycle phosphatase Cdc14 associated with multiple kinases that revealed roles for Cdc14 in mitogen-activated protein kinase signaling, the DNA damage response, and metabolism, whereas interactions of the target of rapamycin complex 1 (TORC1) uncovered new effector kinases in nitrogen and carbon metabolism. An extensive backbone of kinase-kinase interactions cross-connects the proteome and may serve to coordinate diverse cellular responses.
1 Centre for Systems Biology, Samuel Lunenfeld Research Institute, 600 University Avenue, Toronto, Ontario, M5G 1X5, Canada.
2 Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA.
3 Department of Molecular Genetics, University of Toronto, 1 Kings College Circle, Toronto, Ontario, M5S 1A8, Canada.
4 Wellcome Trust Centre for Cell Biology and School of Biological Sciences, University of Edinburgh, Mayfield Road, Edinburgh, EH9 3JR Scotland, UK.
5 Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA.
6 Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
* These authors contributed equally to this work.
To whom correspondence should be addressed. E-mail: gingras@lunenfeld.ca (A.C.G.), nesvi@med.umich.edu(A.I.N.), tyers@lunenfeld.ca, m.tyers@ed.ac.uk (M.T.)
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NOTA CAUSTICANTE DESTE BLOGGER:
Sob o paradigma reducionista neodarwinista os cientistas sempre ficarão surpresos de encontrar complexidade nas coisas vivas. E comunicação não é um sinal de inteligência? Diferente deste modelo reducionista, debaixo do referencial teórico do Design Inteligente é justamente o contrário: mais e mais complexidade e informação os cientistas irão encontrar.
E ainda dizem que o Design Inteligente impede o avanço da ciência. Qual ciência, cara-pálida? Quem atravanca a ciência?
Ah, ia me esquecendo -- informação também faz parte do referencial teórico do Design Inteligente -- a informação complexa especificada que a turma de Down não sabe explicar a origem. E a teoria da evolução através da seleção natural é tida como a maior ideia que toda a humanidade já teve. Isso deve ser gozação epistêmica, não é mesmo???
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