Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&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
Metabolism by aldehyde oxidase (AO) has been responsible for a number of drug failures in clinical trials. The main reason is the clearance values for drugs metabolized by AO are underestimated by allometric scaling from preclinical species. Furthermore, in vitro human data also underestimates clearance. We have developed the first in silico models to predict both in vitro and in vivo human intrinsic clearance for 8 drugs with just two chemical descriptors. These models explain a large amount of the variance in the data using two computational estimates of the electronic and steric features of the reaction. The in vivo computational models for human metabolism are better than in vitro preclinical animal testing at predicting human intrinsic clearance. Thus, it appears that AO is amenable to computational prediction of rates, which may be used to guide drug discovery, and predict pharmacokinetics for clinical trials.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3615103 | PMC |
http://dx.doi.org/10.1021/mp300568r | DOI Listing |
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