Journal Article FZJ-2020-01963

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Coevolutionary Data-based Interaction Networks Approach Highlighting Key Residues across Protein Families: the Case of the G-protein Coupled Receptors

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2020
Research Network of Computational and Structural Biotechnology (RNCSB) Gotenburg

Computational and structural biotechnology journal 18, 1153-1159 () [10.1016/j.csbj.2020.05.003]

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Abstract: 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.

Classification:

Contributing Institute(s):
  1. Computational Biomedicine (IAS-5)
  2. Computational Biomedicine (INM-9)
Research Program(s):
  1. 574 - Theory, modelling and simulation (POF3-574) (POF3-574)

Appears in the scientific report 2020
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Medline ; Creative Commons Attribution-NonCommercial-NoDerivs CC BY-NC-ND 4.0 ; DOAJ ; OpenAccess ; Clarivate Analytics Master Journal List ; DOAJ Seal ; IF < 5 ; JCR ; NCBI Molecular Biology Database ; PubMed Central ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
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 Record created 2020-05-12, last modified 2024-06-25