Linked Life Data

20412040

Source:http://linkedlifedata.com/resource/pubmed/id/20412040

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2010-7-28
pubmed:abstractText
As crucial members of the G-protein coupled receptor (GPCR) superfamily, alpha (1)-adrenergic receptors (alpha(1)-ARs) are recognized to intervene the actions of endogenous catecholamines such as norepinephrine and epinephrine. So far three distinct alpha(1)-AR subtypes, alpha(1A), alpha(1B) and alpha(1D), have been characterized by functional analysis, radio-ligand binding and molecular biology studies. The alpha(1)-ARs are of therapeutic interest because of their distinct and critical roles in many physiological processes, containing hypertension, benign prostatic hyperplasia, smooth muscle contraction, myocardial inotropy and chronotropy, and hepatic glucose metabolism. Accordingly, designing subtype-selective antagonists for each of the three alpha(1)-AR subtypes has been an enthusiastic region of medicinal research. Even though a large number of studies on GPCRs have been conducted, understanding of how known antagonists bind to alpha(1)-ARs still remains sketchy and has been a serious impediment to search for potent and subtype-selective alpha(1)-AR antagonists because of the lack of detailed experimental structural knowledge. This review deliberates the simulation of alpha(1)-ARs and their interactions with antagonists by using ligand-based (pharmacophore identification and QSAR modeling) and structure-based (comparative modeling and molecular docking) approaches. Combined with experimental data, these computational attempts could improve our understanding of the structural basis of antagonist binding and the molecular basis of receptor activation, thus offering a more reasonable approach in the design of drugs targeting alpha(1)-ARs.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
1875-6697
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
6
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
165-78
pubmed:dateRevised
2010-11-18
pubmed:meshHeading
pubmed-meshheading:20412040-Adrenergic alpha-1 Receptor Antagonists, pubmed-meshheading:20412040-Adrenergic alpha-Antagonists, pubmed-meshheading:20412040-Amino Acid Sequence, pubmed-meshheading:20412040-Animals, pubmed-meshheading:20412040-Computer Simulation, pubmed-meshheading:20412040-Computer-Aided Design, pubmed-meshheading:20412040-Drug Design, pubmed-meshheading:20412040-Humans, pubmed-meshheading:20412040-Ligands, pubmed-meshheading:20412040-Models, Molecular, pubmed-meshheading:20412040-Molecular Sequence Data, pubmed-meshheading:20412040-Molecular Structure, pubmed-meshheading:20412040-Protein Binding, pubmed-meshheading:20412040-Protein Conformation, pubmed-meshheading:20412040-Quantitative Structure-Activity Relationship, pubmed-meshheading:20412040-Receptors, Adrenergic, alpha-1
pubmed:year
2010
pubmed:articleTitle
Modeling the interactions between alpha(1)-adrenergic receptors and their antagonists.
pubmed:affiliation
Department of Medicinal Chemistry, School of Pharmacy, Shandong University, Jinan, Shandong, China.
pubmed:publicationType
Journal Article, Review, Research Support, Non-U.S. Gov't