10.1002/chem.202100890
Chemistry - A European Journal
FULL PAPER
ligands in solution and bound to the receptor. The results matched
the observed trends from the relative binding energies, with
ligands 3 and 4 forming more rigid complexes with the receptor
and the substituent inside or in close contact with the cavity of the
receptor, while the complexes with ligand 5 and 6 exhibited a
more dynamic behaviour with more conformational freedom.
The obtained quantitative and qualitative experimental results
were then used to compare and evaluate different computational
methods. MM calculations were performed with three different
force fields (MM3*, MMFFs and OPLS3e) and two different
Acknowledgements
B.Sc. Susanne Henriksson and Dr Peter Michelsen, Amersham
Health R&D, Malmö are thanked for the recording of ES-mass
spectra. K.W thanks the Swedish Research Council, the Royal
Physiographic Society in Lund, the Crafoord Foundation, and the
Swedish Foundation for Strategic Research for financial support.
Keywords: host-guest systems • peptide-protein interactions •
NMR spectroscopy • NMR titrations • computational chemistry
solvent models (chloroform and water) and the resulting energies
MM
1∙x-1∙2
were used to calculated ∆∆E
values. The most acccurate
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receptor 1, both in terms of absolute values and in terms of the
ranking of the binding of the ligands to the receptor, was obtained
with the MM3* force field and a chloroform solvent model. It was
concluded that a chloroform solvent model worked better as an
approximation of the experimental conditions (CDCl3/MeOH-d4
1:1) than a water solvent model. The introduction of a Boltzmann
correction term did not improve the accuracy of the predictions.
Somewhat surprisingly, DFT calculations for the same
systems resulted in substantially less accurate relative binding
affinities than what was obtained from the best MM calculations.
We note that the non-bonded interactions determining the relative
binding strength is a composite of van der Waals interactions and
solvation. These interactions are not solely calculated by the DFT
method itself, but include contributions from add-on models for
London dispersion and continuum solvation. The balance is
heavily dependent on choice of functional and basis set. We
chose combinations that are generally considered sufficiently
accurate for applications in organic chemistry. The current results
show that the chosen combination is insufficiently accurate for
supramolecular interactions of the types found in biomolecules.
The data derived here could be a valuable addition to existing
data sets for future validation of computational methods in this
field.
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A qualitative analysis of the ability of the different force fields
(MM3*, MMFFs and OPLS3e) to predict the experimentally
determined conformation of the ligands in solution and when
bound to the receptor revealed that the MM3* force field was most
successful at predicting the conformation of the heptane
backbone of the ligands, while the OPLS3e force field most
correctly predicted the position of the substituents in relation to
the receptor cavity. The conformational analyses were further
supported by MD simulations.
The combination of techniques has allowed us to tentatively
estimate the free binding energy of a methyl group and a phenyl
group to an aromatic cavity, via CH-π (complex 1•3), and
combined aromatic-CH-π and π-π interactions (complex 1•4),
respectively. The values of −1.7 and −3.3 kJ mol−1 are in
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reasonable agreement with values of the CH-π and aromatic-CH-
[29,30]
π
interactions determined by Wilcox torsional balance,
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taking into account the additional π-π contribution added to the
latter interaction in our case, and the different contribution from
solvophobic effects in our case compared to Wilcox’s.
In conclusion, we have developed a model system to study
peptide-protein interactions and generated qualitative and
quantitative experimental data which can be used to benchmark
different computational methods.
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