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
Linker engineering constitutes a critical, yet frequently underestimated aspect in the construction of synthetic protein switches and sensors. Notably, systematic strategies to engineer linkers by predictive means remain largely elusive to date. This is primarily due to our insufficient understanding how the biophysical properties that underlie linker functions mediate the conformational transitions in artificially engineered protein switches and sensors. The construction of synthetic protein switches and sensors therefore heavily relies on experimental trial-and-error. Yet, methods for effectively generating linker diversity at the genetic level are scarce. Addressing this technical shortcoming, iterative functional linker cloning (iFLinkC) enables the combinatorial assembly of linker elements with functional domains from sequence verified repositories that are developed and stored in-house. The assembly process is highly scalable and given its recursive nature generates linker diversity in a combinatorial and exponential fashion based on a limited number of linker elements.
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Source |
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http://dx.doi.org/10.1016/bs.mie.2020.09.009 | DOI Listing |
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