Coevolutionary data-based interaction networks approach highlighting key residues across protein families : The case of the G-protein coupled receptors
© 2020 The Author(s)..
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.
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2020 |
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Erschienen: |
2020 |
Enthalten in: |
Zur Gesamtaufnahme - volume:18 |
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Enthalten in: |
Computational and structural biotechnology journal - 18(2020) vom: 01., Seite 1153-1159 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Baldessari, Filippo [VerfasserIn] |
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Links: |
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Themen: |
Coevolution |
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Anmerkungen: |
Date Revised 28.03.2024 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
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doi: |
10.1016/j.csbj.2020.05.003 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
NLM310697484 |
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520 | |a 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 | ||
650 | 4 | |a Journal Article | |
650 | 4 | |a Coevolution | |
650 | 4 | |a Conformational states | |
650 | 4 | |a Functionally relevant residues | |
650 | 4 | |a GPCRs | |
650 | 4 | |a Interaction network | |
700 | 1 | |a Capelli, Riccardo |e verfasserin |4 aut | |
700 | 1 | |a Carloni, Paolo |e verfasserin |4 aut | |
700 | 1 | |a Giorgetti, Alejandro |e verfasserin |4 aut | |
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