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
Molecular docking and dynamics studies are of considerable importance in a range of disciplines including molecular biology, drug design, environmental studies, psychology, etc. Using in silico tools to support or even to substitute wet laboratory work could help better focusing the laboratory experiments resulting not only in considerable saving of resources but also increasing the number of molecules and scenarios investigated. There are several software packages that support in silico modeling. However, these tools require lot of compute resources and special technical knowledge. As a result, many bio-scientists cannot use them. The paper describes a science gateway based solution which provides access to Distributed Computing Infrastructures such as clouds, desktop and service grids. This environment enables bio-scientists to execute simple molecular modeling scenarios or build more complex use-cases from existing building blocks while hiding the technical details of the infrastructure. Four scenarios have been defined and deconstructed in order to identify common building blocks supporting a large number of complex use-cases. A reference implementation for the first scenario regarding the impact on indicator species of pharmaceuticals released into water courses has been implemented on the EDGI infrastructure, demonstrating the feasibility of the approach.
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