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An Enhanced Sampling Approach to the Induced Fit Docking Problem in Protein-Ligand Binding: the case of mono-ADP-ribosylation hydrolases inhibitors

Qianqian Zhao, Riccardo Capelli, Paolo Carloni, Bernhard Lüscher, Jinyu Li, View ORCID ProfileGiulia Rossetti
doi: https://doi.org/10.1101/2021.05.08.443251
Qianqian Zhao
1Institute for Advanced Simulations (IAS)-5/Institute for Neuroscience and Medicine (INM)-9, Forschungszentrum Jülich, 52428 Jülich, Germany
2College of Chemistry, Fuzhou University, Fuzhou, 350002, China
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Riccardo Capelli
1Institute for Advanced Simulations (IAS)-5/Institute for Neuroscience and Medicine (INM)-9, Forschungszentrum Jülich, 52428 Jülich, Germany
3Department of Applied Science and Technology, Politecnico di Torino, Torino, 10129, Italy
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  • For correspondence: g.rossetti@fz-juelich.de riccardo.capelli@polito.it
Paolo Carloni
1Institute for Advanced Simulations (IAS)-5/Institute for Neuroscience and Medicine (INM)-9, Forschungszentrum Jülich, 52428 Jülich, Germany
4Institute for Neuroscience and Medicine (INM)-11, Forschungszentrum Jülich, 52428 Jülich, Germany
5Faculty of Mathematics, Computer Science and Natural Sciences, RWTH Aachen, 52062 Aachen, Germany
8Department of Neurology, RWTH Aachen University, Aachen, Germany
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Bernhard Lüscher
6Institute of Biochemistry and Molecular Biology, RWTH Aachen University, Aachen, Germany
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Jinyu Li
2College of Chemistry, Fuzhou University, Fuzhou, 350002, China
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Giulia Rossetti
1Institute for Advanced Simulations (IAS)-5/Institute for Neuroscience and Medicine (INM)-9, Forschungszentrum Jülich, 52428 Jülich, Germany
7Jülich Supercomputing Center (JSC), Forschungszentrum Jülich, 52425 Jülich, Germany
8Department of Neurology, RWTH Aachen University, Aachen, Germany
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  • ORCID record for Giulia Rossetti
  • For correspondence: g.rossetti@fz-juelich.de riccardo.capelli@polito.it
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Abstract

A variety of enhanced sampling methods can predict free energy landscapes associated with protein/ligand binding events, characterizing in a precise way the intermolecular interactions involved. Unfortunately, these approaches are challenged by not uncommon induced fit mecchanisms. Here, we present a variant of the recently reported volume-based metadynamics (MetaD) method which describes ligand binding even when it affects protein structure. The validity of the approach is established by applying it to a substrate/enzyme complexes of pharmacological relevance: this is the mono-ADP-ribose (ADPr) in complex with mono-ADP-ribosylation hydrolases (MacroD1 and MacroD2), where induced-fit phenomena are known to be operative. The calculated binding free energies are consistent with experiments, with an absolute error less than 0.5 kcal/mol. Our simulations reveal that in all circumstances the active loops, delimiting the boundaries of the binding site, rearrange from an open to a closed conformation upon ligand binding. The calculations further provide, for the first time, the molecular basis of the experimentally observed affinity changes in ADPr binding on passing from MacroD1 to MacroD2 and all its mutants. Our study paves the way to investigate in a completely general manner ligand binding to proteins and receptors.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://www.plumed-nest.org/eggs/21/018/

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted May 08, 2021.
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An Enhanced Sampling Approach to the Induced Fit Docking Problem in Protein-Ligand Binding: the case of mono-ADP-ribosylation hydrolases inhibitors
Qianqian Zhao, Riccardo Capelli, Paolo Carloni, Bernhard Lüscher, Jinyu Li, Giulia Rossetti
bioRxiv 2021.05.08.443251; doi: https://doi.org/10.1101/2021.05.08.443251
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An Enhanced Sampling Approach to the Induced Fit Docking Problem in Protein-Ligand Binding: the case of mono-ADP-ribosylation hydrolases inhibitors
Qianqian Zhao, Riccardo Capelli, Paolo Carloni, Bernhard Lüscher, Jinyu Li, Giulia Rossetti
bioRxiv 2021.05.08.443251; doi: https://doi.org/10.1101/2021.05.08.443251

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