کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5590297 | 1570131 | 2017 | 27 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Paralog-divergent Features May Help Reduce Off-target Effects of Drugs: Hints from Glucagon Subfamily Analysis
ترجمه فارسی عنوان
ویژگی های پاراگورو واگرا می تواند به کاهش اثر آفات هدف از مواد مخدر: نکات از تجزیه و تحلیل زیرشاخه گلوکاگون
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کلمات کلیدی
پارالوگ، واگرایی کاربردی، سایت کارکردی خاصیت دارو، حفاظت تکاملی،
موضوعات مرتبط
علوم زیستی و بیوفناوری
بیوشیمی، ژنتیک و زیست شناسی مولکولی
ژنتیک
چکیده انگلیسی
Side effects from targeted drugs remain a serious concern. One reason is the nonselective binding of a drug to unintended proteins such as its paralogs, which are highly homologous in sequences and have similar structures and drug-binding pockets. To identify targetable differences between paralogs, we analyzed two types (type-I and type-II) of functional divergence between two paralogs in the known target protein receptor family G-protein coupled receptors (GPCRs) at the amino acid level. Paralogous protein receptors in glucagon-like subfamily, glucagon receptor (GCGR) and glucagon-like peptide-1 receptor (GLP-1R), exhibit divergence in ligands and are clinically validated drug targets for type 2 diabetes. Our data showed that type-II amino acids were significantly enriched in the binding sites of antagonist MK-0893 to GCGR, which had a radical shift in physicochemical properties between GCGR and GLP-1R. We also examined the role of type-I amino acids between GCGR and GLP-1R. The divergent features between GCGR and GLP-1R paralogs may be helpful in their discrimination, thus enabling the identification of binding sites to reduce undesirable side effects and increase the target specificity of drugs.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Genomics, Proteomics & Bioinformatics - Volume 15, Issue 4, August 2017, Pages 246-254
Journal: Genomics, Proteomics & Bioinformatics - Volume 15, Issue 4, August 2017, Pages 246-254
نویسندگان
Zhining Sa, Jingqi Zhou, Yangyun Zou, Zhixi Su, Xun Gu,