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NMR Data‐Driven Docking of HDM2‐Inhibitor Complexes
We present an automated NMR‐guided docking workflow that can be used to generate models of protein‐ligand complexes based on data from NOE NMR experiments. The first step is to generate a number of intermolecular distance constraints from experimental NOE data. Then, the ligand is docked on an ensem...
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Published in: | Chembiochem : a European journal of chemical biology 2022-03, Vol.23 (6), p.e202100570-n/a |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | We present an automated NMR‐guided docking workflow that can be used to generate models of protein‐ligand complexes based on data from NOE NMR experiments. The first step is to generate a number of intermolecular distance constraints from experimental NOE data. Then, the ligand is docked on an ensemble of receptor structures to account for protein flexibility, and multiple poses are generated. Finally, we use the NOE‐based constraints to filter and score docking poses based on the percentage of NOE constraints that are consistent with protein‐ligand interatomic distances. This workflow was successfully used during a lead optimization project to generate models of synthetic protein‐protein interaction (PPI) inhibitors bound to the HDM2 protein.
HDM2 lead optimization was guided by the rapid generation of protein‐ligand structures using an NMR‐data driven docking protocol. This work underscores an “integrative” approach where strengths from modeling, X‐ray crystallography and NMR spectroscopy can be leveraged to deliver more information on ligand‐protein interactions than is available from any one technique. |
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ISSN: | 1439-4227 1439-7633 |
DOI: | 10.1002/cbic.202100570 |