Abstract

In this study, the automated fragmentation quantum mechanics/molecular mechanics (AF-QM/MM) method was applied for NMR chemical shift calculations of protein-ligand complexes. In the AF-QM/MM approach, the protein binding pocket is automatically divided into capped fragments (within ~200 atoms) for density functional theory (DFT) calculations of NMR chemical shifts. Meanwhile, the solvent effect was also included using the Poission-Boltzmann (PB) model, which properly accounts for the electrostatic polarization effect from the solvent for protein-ligand complexes. The NMR chemical shifts of neocarzinostatin (NCS)-chromophore binding complex calculated by AF-QM/MM accurately reproduce the large-sized system results. The 1H chemical shift perturbations (CSP) between apo-NCS and holo-NCS predicted by AF-QM/MM are also in excellent agreement with experimental results. Furthermore, the DFT calculated chemical shifts of the chromophore and residues in the NCS binding pocket can be utilized as molecular probes to identify the correct ligand binding conformation. By combining the CSP of the atoms in the binding pocket with the Glide scoring function, the new scoring function can accurately distinguish the native ligand pose from decoy structures. Therefore, the AF-QM/MM approach provides an accurate and efficient platform for protein-ligand binding structure prediction based on NMR derived information.

Highlights

  • Structure-based computational methods are useful tools for analyzing the binding modes and affinities for protein-ligand complexes (Grinter and Zou, 2014)

  • The results show that large chemical shift perturbations between apo and holo protein-ligand systems could be accurately predicted by the AF-quantum mechanical (QM)/molecular mechanics (MM) approach

  • In the AF-QM/MM approach, the atomic nuclear magnetic resonance (NMR) chemical shifts were obtained by dividing the protein automatically into residue-centric fragments

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Summary

Introduction

Structure-based computational methods are useful tools for analyzing the binding modes and affinities for protein-ligand complexes (Grinter and Zou, 2014). By comparing the AF-QM/MM calculated chemical shifts with experiment data, a chemical shift based scoring function was developed to rank the native and predicted protein-ligand binding poses.

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