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  • 标题:Coevolutionary data-based interaction networks approach highlighting key residues across protein families: The case of the G-protein coupled receptors
  • 本地全文:下载
  • 作者:Filippo Baldessari ; Riccardo Capelli ; Paolo Carloni
  • 期刊名称:Computational and Structural Biotechnology Journal
  • 印刷版ISSN:2001-0370
  • 出版年度:2020
  • 卷号:18
  • 页码:1153-1159
  • DOI:10.1016/j.csbj.2020.05.003
  • 出版社:Computational and Structural Biotechnology Journal
  • 摘要:We present an approach that, by integrating structural data with Direct Coupling Analysis, is able to pinpoint most of the interaction hotspots (i.e. key residues for the biological activity) across very sparse protein families in a single run. An application to the Class A G-protein coupled receptors (GPCRs), both in their active and inactive states, demonstrates the predictive power of our approach. The latter can be easily extended to any other kind of protein family, where it is expected to highlight most key sites involved in their functional activity.
  • 关键词:GPCRs ; Coevolution ; Interaction network ; Conformational states ; Functionally relevant residues
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