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
CypScore is an in silico approach for predicting the likely sites of cytochrome P450-mediated metabolism of druglike organic molecules. It consists of multiple models for the most important P450 oxidation reactions such as aliphatic hydroxylation, N-dealkylation, O-dealkylation, aromatic hydroxylation, double-bond oxidation, N-oxidation, and S-oxidation. Each of these models is based on atomic reactivity descriptors derived from surface-based properties calculated with ParaSurf and based on AM1 semiempirical molecular orbital theory. The models were trained with data derived from Bayer Schering Pharma's in-house MajorMetabolite Database with more than 2300 transformations and more than 800 molecules collected from the primary literature. The models have been balanced to allow the treatment of relative intramolecular, intra-chemotype, and inter-chemotype reactivities of the labile sites toward oxidation. The models were evaluated with promising hit rates on three public datasets of varying quality in the annotation of the experimental positions. For 39 well-characterized compounds from 14 in-house lead optimization programs, we could detect at least one major metabolite for the three highest-ranked positions in 87 % of the compounds and overall more than 62 % of all major metabolites, with promising true- to false-positive ratios of 0.9.
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Source |
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http://dx.doi.org/10.1002/cmdc.200800384 | DOI Listing |
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