This title appears in the Scientific Report :
2021
Please use the identifier:
http://hdl.handle.net/2128/29496 in citations.
Please use the identifier: http://dx.doi.org/10.1021/acs.jctc.1c00649 in citations.
An Enhanced Sampling Approach to the Induced Fit Docking Problem in Protein-Ligand Binding: the case of mono-ADPribosylationhydrolases inhibitors
An Enhanced Sampling Approach to the Induced Fit Docking Problem in Protein-Ligand Binding: the case of mono-ADPribosylationhydrolases inhibitors
Enhanced sampling methods can predict free-energy landscapes associated with protein/ligand binding, characterizing the involved intermolecular interactions in a precise way. However, these in silico approaches can be challenged by induced-fit effects. Here, we present a variant of volume-based meta...
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Personal Name(s): | Rossetti, Giulia (Corresponding author) |
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Capelli, Riccardo / Li, Jinyu / Carloni, Paolo / Zhao, Qianqian | |
Contributing Institute: |
Computational Biomedicine; IAS-5 Jülich Supercomputing Center; JSC Computational Biomedicine; INM-9 |
Published in: | Journal of chemical theory and computation, 17 (2021) 12, S. 7899–7911 |
Imprint: |
Washington, DC
2021
|
DOI: |
10.1021/acs.jctc.1c00649 |
Document Type: |
Journal Article |
Research Program: |
Molecular Information Processing in Cellular Systems Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups |
Link: |
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Publikationsportal JuSER |
Please use the identifier: http://dx.doi.org/10.1021/acs.jctc.1c00649 in citations.
Enhanced sampling methods can predict free-energy landscapes associated with protein/ligand binding, characterizing the involved intermolecular interactions in a precise way. However, these in silico approaches can be challenged by induced-fit effects. Here, we present a variant of volume-based metadynamics tailored to tackle this problem in a general and efficient way. The validity of the approach is established by applying it to substrate/enzyme complexes of pharmacological relevance: mono-ADP-ribose (ADPr) in complex with mono-ADP-ribosylation hydrolases (MacroD1 and MacroD2), where induced-fit phenomena are known to be significant. The calculated binding free energies are consistent with experiments, with an absolute error smaller than 0.5 kcal/mol. Our simulations reveal that in all circumstances, the active loops, delimiting the boundaries of the binding site, undergo significant conformation rearrangements upon ligand binding. The calculations further provide, for the first time, the molecular basis of ADPr specificity and the relative changes in its experimental binding affinity on passing from MacroD1 to MacroD2 and all its mutants. Our study paves the way to the quantitative description of induced-fit events in molecular recognition. |