Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Protein interaction networks play a key role in signal processing. Despite the progress in identifying the interactions, the quantification of their strengths lags behind. Here we present an approach to quantify the in vivo binding of proteins to their binding partners in signaling-transcriptional networks, by the pairwise genetic isolation of each interaction and by varying the concentration of the interacting components over time. The absolute quantification of the protein concentrations was performed with targeted mass spectrometry. The strengths of the interactions, as defined by the apparent dissociation constants, ranged from subnanomolar to micromolar values in the yeast galactose signaling network. The weak homodimerization of the Gal4 activator amplifies the signal elicited by glucose. Furthermore, combining the binding constants in a feedback loop correctly predicted cellular memory, a characteristic network behavior. Thus, this genetic-proteomic binding assay can be used to faithfully quantify how strongly proteins interact with proteins, DNA and metabolites.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1021/acssynbio.6b00282 | DOI Listing |
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