Beltrao P.,European Bioinformatics Institute |
Bork P.,Structural and Computational Biology Unit |
Bork P.,Max Delbruck Center for Molecular Medicine |
Krogan N.J.,University of California at San Francisco |
And 3 more authors.
Molecular Systems Biology | Year: 2013
Protein post-translational modifications (PTMs) allow the cell to regulate protein activity and play a crucial role in the response to changes in external conditions or internal states. Advances in mass spectrometry now enable proteome wide characterization of PTMs and have revealed a broad functional role for a range of different types of modifications. Here we review advances in the study of the evolution and function of PTMs that were spurred by these technological improvements. We provide an overview of studies focusing on the origin and evolution of regulatory enzymes as well as the evolutionary dynamics of modification sites. Finally, we discuss different mechanisms of altering protein activity via post-translational regulation and progress made in the large-scale functional characterization of PTM function. © 2013 The Authors.
Springer M.,Harvard University |
Weissman J.S.,Howard Hughes Medical Institute |
Weissman J.S.,California Institute for Quantitative Biosciences |
Weissman J.S.,University of California at San Francisco |
Kirschner M.W.,Harvard University
Molecular Systems Biology | Year: 2010
Gene copy number variation has been discovered in humans, between related species, and in different cancer tissues, but it is unclear how much of this genomic-level variation leads to changes in the level of protein abundance. To address this, we eliminated one of the two genomic copies of 730 different genes in Saccharomyces cerevisiae and asked how often a 50% reduction in gene dosage leads to a 50% reduction in protein level. For at least 80% of genes tested, and under several environmental conditions, it does: protein levels in the heterozygous strain are close to 50% of wild type. For 5% of the genes tested, the protein levels in the heterozygote are maintained at nearly wild-type levels. These experiments show that protein levels are not, in general, directly monitored and adjusted to a desired level. Combined with fitness data, this implies that proteins are expressed at levels higher than necessary for survival. © 2010 EMBO and Macmillan Publishers Limited. All rights reserved.
Ideker T.,University of California at San Diego |
Krogan N.J.,University of California at San Francisco |
Krogan N.J.,California Institute for Quantitative Biosciences |
Molecular Systems Biology | Year: 2012
Protein and genetic interaction maps can reveal the overall physical and functional landscape of a biological system. To date, these interaction maps have typically been generated under a single condition, even though biological systems undergo differential change that is dependent on environment, tissue type, disease state, development or speciation. Several recent interaction mapping studies have demonstrated the power of differential analysis for elucidating fundamental biological responses, revealing that the architecture of an interactome can be massively re-wired during a cellular or adaptive response. Here, we review the technological developments and experimental designs that have enabled differential network mapping at very large scales and highlight biological insight that has been derived from this type of analysis. We argue that differential network mapping, which allows for the interrogation of previously unexplored interaction spaces, will become a standard mode of network analysis in the future, just as differential gene expression and protein phosphorylation studies are already pervasive in genomic and proteomic analysis. © 2012 EMBO and Macmillan Publishers Limited All rights reserved.
Smith C.A.,University of California at San Francisco |
Kortemme T.,University of California at San Francisco |
Kortemme T.,California Institute for Quantitative Biosciences
Journal of Molecular Biology | Year: 2010
Protein-protein recognition, frequently mediated by members of large families of interaction domains, is one of the cornerstones of biological function. Here, we present a computational, structure-based method to predict the sequence space of peptides recognized by PDZ domains, one of the largest families of recognition proteins. As a test set, we use a considerable amount of recent phage display data that describe the peptide recognition preferences for 169 naturally occurring and engineered PDZ domains. For both wild-type PDZ domains and single point mutants, we find that 70-80% of the most frequently observed amino acids by phage display are predicted within the top five ranked amino acids. Phage display frequently identified recognition preferences for amino acids different from those present in the original crystal structure. Notably, in about half of these cases, our algorithm correctly captures these preferences, indicating that it can predict mutations that increase binding affinity relative to the starting structure. We also find that we can computationally recapitulate specificity changes upon mutation, a key test for successful forward design of protein-protein interface specificity. Across all evaluated data sets, we find that incorporation backbone sampling improves accuracy substantially, irrespective of using a crystal or NMR structure as the starting conformation. Finally, we report successful prediction of several amino acid specificity changes from blind tests in the DREAM4 peptide recognition domain specificity prediction challenge. Because the foundational methods developed here are structure based, these results suggest that the approach can be more generally applied to specificity prediction and redesign of other protein-protein interfaces that have structural information but lack phage display data. © 2010 Elsevier Ltd.
Salt M.B.,University of California at San Francisco |
Bandyopadhyay S.,University of California at San Francisco |
Bandyopadhyay S.,California Institute for Quantitative Biosciences |
McCormick F.,University of California at San Francisco
Cancer Discovery | Year: 2014
Tumors showing evidence of epithelial-to-mesenchymal transition (EMT) have been associated with metastasis, drug resistance, and poor prognosis. Heterogeneity along the EMT spectrum is observed between and within tumors. To develop effective therapeutics, a mechanistic understanding of how EMT affects the molecular requirements for proliferation is needed. We found that although cells use phosphoinositide 3-kinase (PI3K) for proliferation in both the epithelial and mesenchymal states, EMT rewires the mechanism of PI3K pathway activation. In epithelial cells, autocrine ERBB3 activation maintains PI3K signaling, whereas after EMT, downregulation of ERBB3 disrupts autocrine signaling to PI3K. Loss of ERBB3 leads to reduced serum-independent proliferation after EMT that can be rescued through reactivation of PI3K by enhanced signaling from p110α, ERBB3 reexpression, or growth factor stimulation. In vivo, we demonstrate that PIK3CA expression is upregulated in mesenchymal tumors with low levels of ERBB3. This study defines how ERBB3 downregulation after EMT affects PI3K-dependent proliferation. © 2014 American Association for Cancer Research.