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Mapping the energy landscape of PROTAC-mediated protein-protein interactions.
Villegas, José A; Vaid, Tasneem M; Johnson, Michael E; Moore, Terry W.
Affiliation
  • Villegas JA; Department of Pharmaceutical Sciences, College of Pharmacy, University of Illinois Chicago, Chicago, IL 60612, USA.
  • Vaid TM; Department of Pharmaceutical Sciences, College of Pharmacy, University of Illinois Chicago, Chicago, IL 60612, USA.
  • Johnson ME; Department of Pharmaceutical Sciences, College of Pharmacy, University of Illinois Chicago, Chicago, IL 60612, USA.
  • Moore TW; Center for Biomolecular Sciences, College of Pharmacy, University of Illinois Chicago, Chicago, IL 60606, USA.
Comput Struct Biotechnol J ; 21: 1885-1892, 2023.
Article in En | MEDLINE | ID: mdl-36923472
ABSTRACT
A principal challenge in computational modeling of macromolecules is the vast conformational space that arises out of large numbers of atomic degrees of freedom. Recently, growing interest in building predictive models of complexes mediated by Proteolysis Targeting Chimeras (PROTACs) has led to the application of state-of-the-art computational techniques to tackle this problem. However, repurposing existing tools to carry out protein-protein docking and linker conformer generation independently results in extensive sampling of structures incompatible with PROTAC-mediated complex formation. Here we show that it is possible to restrict the search to the space of protein-protein conformations that can be bridged by a PROTAC molecule with a given linker composition by using a cyclic coordinate descent algorithm to position PROTACs into complex-bound configurations. We use this methodology to construct potential energy and solvation energy landscapes of PROTAC-mediated interactions. Our results suggest that desolvation of amino acids at interfaces could play a dominant role in PROTAC-mediated complex formation.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Comput Struct Biotechnol J Year: 2023 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Comput Struct Biotechnol J Year: 2023 Document type: Article Affiliation country:
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