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10.1016/j.gpb.2017.03.004

http://scihub22266oqcxt.onion/10.1016/j.gpb.2017.03.004
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C5582795!5582795!28642113
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suck abstract from ncbi


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pmid28642113      Genomics+Proteomics+Bioinformatics 2017 ; 15 (4): 246-54
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  • Paralog-divergent Features May Help Reduce Off-target Effects of Drugs: Hints from Glucagon Subfamily Analysis #MMPMID28642113
  • Sa Z; Zhou J; Zou Y; Su Z; Gu X
  • Genomics Proteomics Bioinformatics 2017[Aug]; 15 (4): 246-54 PMID28642113show ga
  • 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.
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