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: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
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
Efforts to detect binding modes of general anesthetics (GAs) for pentameric ligand-gated ion channels (pLGICs) are often complicated by a large number of indicated sites, as well as the challenges of ranking sites by affinity and determining which sites are occupied at clinical concentrations. Physics-based computational methods offer a powerful route for determining affinities of ligands to isolated binding sites, but preserving accuracy is essential. This chapter describes a step-by-step approach to multiple methods for identifying candidate sites and quantifying binding affinities and also discusses limitations and common pitfalls.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1016/bs.mie.2018.02.001 | DOI Listing |
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