This title appears in the Scientific Report :
2020
Please use the identifier:
http://hdl.handle.net/2128/25475 in citations.
Please use the identifier: http://dx.doi.org/10.1016/j.csbj.2020.05.003 in citations.
Coevolutionary Data-based Interaction Networks Approach Highlighting Key Residues across Protein Families: the Case of the G-protein Coupled Receptors
Coevolutionary Data-based Interaction Networks Approach Highlighting Key Residues across Protein Families: the Case of the G-protein Coupled Receptors
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 recepto...
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Personal Name(s): | Baldessari, Filippo |
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Capelli, Riccardo (Corresponding author) / Carloni, Paolo / Giorgetti, Alejandro | |
Contributing Institute: |
Computational Biomedicine; INM-9 Computational Biomedicine; IAS-5 |
Published in: | Computational and structural biotechnology journal, 18 (2020) S. 1153-1159 |
Imprint: |
Gotenburg
Research Network of Computational and Structural Biotechnology (RNCSB)
2020
|
PubMed ID: |
32489528 |
DOI: |
10.1016/j.csbj.2020.05.003 |
Document Type: |
Journal Article |
Research Program: |
Theory, modelling and simulation |
Link: |
Get full text OpenAccess Get full text OpenAccess |
Publikationsportal JuSER |
Please use the identifier: http://dx.doi.org/10.1016/j.csbj.2020.05.003 in citations.
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. |