Binding-affinity predictions of HSP90 in the D3R Grand Challenge 2015 with docking, MM/GBSA, QM/MM, and free-energy simulations

Majda Misini Ignjatović,Ulf Ryde,Geng Dong,Octav Caldararu,Camila Muñoz-Gutierrez,Francisco Adasme-Carreño

doi:10.1007/s10822-016-9942-z

Majda Misini Ignjatović, Ulf Ryde + Show 4 more

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https://doi.org/10.1007/s10822-016-9942-z

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Abstract

We have estimated the binding affinity of three sets of ligands of the heat-shock protein 90 in the D3R grand challenge blind test competition. We have employed four different methods, based on five different crystal structures: first, we docked the ligands to the proteins with induced-fit docking with the Glide software and calculated binding affinities with three energy functions. Second, the docked structures were minimised in a continuum solvent and binding affinities were calculated with the MM/GBSA method (molecular mechanics combined with generalised Born and solvent-accessible surface area solvation). Third, the docked structures were re-optimised by combined quantum mechanics and molecular mechanics (QM/MM) calculations. Then, interaction energies were calculated with quantum mechanical calculations employing 970–1160 atoms in a continuum solvent, combined with energy corrections for dispersion, zero-point energy and entropy, ligand distortion, ligand solvation, and an increase of the basis set to quadruple-zeta quality. Fourth, relative binding affinities were estimated by free-energy simulations, using the multi-state Bennett acceptance-ratio approach. Unfortunately, the results were varying and rather poor, with only one calculation giving a correlation to the experimental affinities larger than 0.7, and with no consistent difference in the quality of the predictions from the various methods. For one set of ligands, the results could be strongly improved (after experimental data were revealed) if it was recognised that one of the ligands displaced one or two water molecules. For the other two sets, the problem is probably that the ligands bind in different modes than in the crystal structures employed or that the conformation of the ligand-binding site or the whole protein changes.Electronic supplementary materialThe online version of this article (doi:10.1007/s10822-016-9942-z) contains supplementary material, which is available to authorized users.

Highlights

One of the prime challenges of computational chemistry is to predict the free energy for the binding of small molecules to biomacromolecules
The docked structures were minimised in a continuum solvent and binding affinities were calculated with the MM/GBSA method
J Comput Aided Mol Des (2016) 30:707–730 methods, such as MM/GBSA and linear interaction energies (LIE), to strict free-energy simulation (FES) methods [1,2,3,4]

Summary

Introduction

One of the prime challenges of computational chemistry is to predict the free energy for the binding of small molecules to biomacromolecules. The conclusion has typically been that docking methods can rapidly find the correct binding pose among several other poses, but that they have problems to correctly rank the affinities of a set of ligands to the same protein. MM/GBSA calculations typically give a better ranking of the ligands and an understanding of energy terms involved in the binding, but often vastly overestimate energy differences and the results strongly depend on the employed continuum-solvation model [2, 12]. Large-scale tests of FES calculations have given rather impressive results for relative binding affinities of similar ligands to the same protein, with mean absolute deviations (MAD) of 4–6 kJ/mol [9,10,11]. The comparisons have been primarily directed to small changes in the ligands and the performance is uneven, with very good results for some proteins, but quite poor performance for other proteins, occasionally with errors of over 20 kJ/mol

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