4.7 Article

Mapping the energy landscape of PROTAC-mediated protein-protein interactions

Journal

COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
Volume 21, Issue -, Pages 1885-1892

Publisher

ELSEVIER
DOI: 10.1016/j.csbj.2023.02.049

Keywords

PROTAC; Protein-protein docking; Energy landscape

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A major challenge in computational modeling of macromolecules is the vast conformational space due to atomic degrees of freedom. Recent interest in predictive models of complexes mediated by PROTACs led to the application of advanced computational techniques. However, repurposing existing tools for protein-protein docking and linker conformer generation results in incompatible structures. In this study, a cyclic coordinate descent algorithm was used to position PROTACs into complex-bound configurations, allowing for a restricted search in protein-protein conformations that can be bridged by a PROTAC molecule with a given linker composition.
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.(c) 2023 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (http://creative-commons.org/licenses/by-nc-nd/4.0/).

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