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Glucagon Receptor Antagonists (glucagon + receptor_antagonist)

Distribution by Scientific Domains
Chemistry100%

Selected Abstracts

Insight into the Bioactivity and Metabolism of Human Glucagon Receptor Antagonists from 3D-QSAR Analyses

MOLECULAR INFORMATICS, Issue 8 2004
HaiFeng Chen
Abstract Descriptors, such as logP, the number of hydrogen bond donors, the number of hydrogen bond acceptors, highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) combined with fields of CoMFA and CoMSIA to construct models for hyperglycemia decrease activity and metabolism of human glucagon receptor antagonists. The results reveal that including logP, HOMO and LUMO energies is meaningful for QSAR/QSMR model. The models were validated by using a test set of structural diverse compounds that had not been included in the CoMFA and CoMSIA models. Support Vector Machines (SVM) have been used to select the suitable additional descriptors to construct 3D-QSAR/QSMR models. A key factor to mention is that activity and metabolism models simultaneously. These in silico ADME models are helpful in making quantitative prediction of inhibitory activities and rates of metabolism before resorting in vitro and in vivo experimentation. [source]

Integration of Optimized Substituent Patterns to Produce Highly Potent 4-Aryl-pyridine Glucagon Receptor Antagonists.

CHEMINFORM, Issue 12 2003
Gaetan H. Ladouceur
Abstract For Abstract see ChemInform Abstract in Full Text. [source]

ChemInform Abstract: Discovery of 5-Hydroxyalkyl-4-phenylpyridines as a New Class of Glucagon Receptor Antagonists.

CHEMINFORM, Issue 24 2002
Gaetan H. Ladouceur
Abstract ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a "Full Text" option. The original article is trackable via the "References" option. [source]

Insight into the Bioactivity and Metabolism of Human Glucagon Receptor Antagonists from 3D-QSAR Analyses

MOLECULAR INFORMATICS, Issue 8 2004
HaiFeng Chen
Abstract Descriptors, such as logP, the number of hydrogen bond donors, the number of hydrogen bond acceptors, highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) combined with fields of CoMFA and CoMSIA to construct models for hyperglycemia decrease activity and metabolism of human glucagon receptor antagonists. The results reveal that including logP, HOMO and LUMO energies is meaningful for QSAR/QSMR model. The models were validated by using a test set of structural diverse compounds that had not been included in the CoMFA and CoMSIA models. Support Vector Machines (SVM) have been used to select the suitable additional descriptors to construct 3D-QSAR/QSMR models. A key factor to mention is that activity and metabolism models simultaneously. These in silico ADME models are helpful in making quantitative prediction of inhibitory activities and rates of metabolism before resorting in vitro and in vivo experimentation. [source]