Supplementary data for the article: Andrić, J. M.; Misini-Ignjatović, M. Z.; Murray, J. S.; Politzer, P.; Zarić, S. D. Hydrogen Bonding between Metal-Ion Complexes and Noncoordinated Water: Electrostatic Potentials and Interaction Energies. ChemPhysChem 2016, 2035–2042. https://doi.org/10.1002/cphc.201501200

Supplementary material for: [https://doi.org/10.1002/cphc.201501200]Related to published version: [http://cherry.chem.bg.ac.rs/handle/123456789/2289

Supplementary data for the article: Andrić, J. M.; Misini-Ignjatović, M. Z.; Murray, J. S.; Politzer, P.; Zarić, S. D. Hydrogen Bonding between Metal-Ion Complexes and Noncoordinated Water: Electrostatic Potentials and Interaction Energies. ChemPhysChem 2016, 2035–2042. https://doi.org/10.1002/cphc.201501200

Supplementary material for: [https://doi.org/10.1002/cphc.201501200]Related to published version: [http://cherry.chem.bg.ac.rs/handle/123456789/2289

Binding free energies in the SAMPL6 octa-acid host–guest challenge calculated with MM and QM methods

We have estimated free energies for the binding of eight carboxylate ligands to two variants of the octa-acid deep-cavity host in the SAMPL6 blind-test challenge (with or without endo methyl groups on the four upper-rim benzoate groups, OAM and OAH, respectively). We employed free-energy perturbation (FEP) for relative binding energies at the molecular mechanics (MM) and the combined quantum mechanical (QM) and MM (QM/MM) levels, the latter obtained with the reference-potential approach with QM/MM sampling for the MM → QM/MM FEP. The semiempirical QM method PM6-DH+ was employed for the ligand in the latter calculations. Moreover, binding free energies were also estimated from QM/MM optimised structures, combined with COSMO-RS estimates of the solvation energy and thermostatistical corrections from MM frequencies. They were performed at the PM6-DH+ level of theory with the full host and guest molecule in the QM system (and also four water molecules in the geometry optimisations) for 10–20 snapshots from molecular dynamics simulations of the complex. Finally, the structure with the lowest free energy was recalculated using the dispersion-corrected density-functional theory method TPSS-D3, for both the structure and the energy. The two FEP approaches gave similar results (PM6-DH+/MM slightly better for OAM), which were among the five submissions with the best performance in the challenge and gave the best results without any fit to data from the SAMPL5 challenge, with mean absolute deviations (MAD) of 2.4–5.2 kJ/mol and a correlation coefficient (R2) of 0.77–0.93. This is the first time QM/MM approaches give binding free energies that are competitive to those obtained with MM for the octa-acid host. The QM/MM-optimised structures gave somewhat worse performance (MAD = 3–8 kJ/mol and R2 = 0.1–0.9), but the results were improved compared to previous studies of this system with similar methods

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

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

Substituted polyfluoroaryl interactions with an arginine side chain in galectin-3 are governed by steric-, desolvation and electronic conjugation effects

In the β-d-galactopyranoside-binding protein galectin-3, synthetic inhibitors substituted at the 3-position of a thiodigalactoside core cause the formation of an aglycone binding pocket through the displacement of an arginine residue (Arg144) from its position in the apoprotein. To examine in detail the role of different molecular interactions in this pocket, we have synthesized a series of nine 3-(4-(2,3,5,6-tetrafluorophenyl)-1,2,3-triazol-1-yl)-thiogalactosides with different para substituents and measured their affinities to galectin-3 using a fluorescence polarization assay. High-resolution crystal structures (<1.3 Å) have been determined for five of the ligands in complex with the C-terminal domain of galectin-3. The binding affinities are rationalised with the help of the three-dimensional structures and quantum-mechanical calculations. Three effects seem to be involved: Firstly, the binding pocket is too small for the largest ligands with ethyl and methyl. Secondly, for the other ligands, the affinity seems to be determined mainly by desolvation effects, disfavouring the polar substituents, but this is partly counteracted by the cation-π interaction with Arg144, which stacks on top of the substituted tetrafluorophenyl group in all complexes. The results provide detailed insight into interactions of fluorinated phenyl moieties with arginine-containing protein binding sites and the complex interplay of different energetic components in defining the binding affinity

Structure and Energetics of Ligand–Fluorine Interactions with Galectin-3 Backbone and Side-Chain Amides : Insight into Solvation Effects and Multipolar Interactions

Multipolar fluorine–amide interactions with backbone and side-chain amides have been described as important for protein–ligand interactions and have been used to improve the potency of synthetic inhibitors. In this study, fluorine interactions within a well-defined binding pocket on galectin-3 were investigated systematically using phenyltriazolyl-thiogalactosides fluorinated singly or multiply at various positions on the phenyl ring. X-ray structures of the C-terminal domain of galectin-3 in complex with eight of these ligands revealed potential orthogonal fluorine–amide interactions with backbone amides and one with a side-chain amide. The two interactions involving main-chain amides seem to have a strong influence on affinity as determined by fluorescence anisotropy. In contrast, the interaction with the side-chain amide did not influence affinity. Quantum mechanics calculations were used to analyze the relative contributions of these interactions to the binding energies. No clear correlation could be found between the relative energies of the fluorine–main-chain amide interactions and the overall binding energy. Instead, dispersion and desolvation effects play a larger role. The results confirm that the contribution of fluorine–amide interactions to protein–ligand interactions cannot simply be predicted, on geometrical considerations alone, but require careful consideration of the energetic components

Interplay between Conformational Entropy and Solvation Entropy in Protein-Ligand Binding

Understanding the driving forces underlying molecular recognition is of fundamental importance in chemistry and biology. The challenge is to unravel the binding thermodynamics into separate contributions and to interpret these in molecular terms. Entropic contributions to the free energy of binding are particularly difficult to assess in this regard. Here we pinpoint the molecular determinants underlying differences in ligand affinity to the carbohydrate recognition domain of galectin-3, using a combination of isothermal titration calorimetry, X-ray crystallography, NMR relaxation, and molecular dynamics simulations followed by conformational entropy and grid inhomogeneous solvation theory (GIST) analyses. Using a pair of diastereomeric ligands that have essentially identical chemical potential in the unbound state, we reduced the problem of dissecting the thermodynamics to a comparison of the two protein-ligand complexes. While the free energies of binding are nearly equal for the R and S diastereomers, greater differences are observed for the enthalpy and entropy, which consequently exhibit compensatory behavior, Δ ΔH°(R - S) = -5 ± 1 kJ/mol and -T Δ ΔS°(R - S) = 3 ± 1 kJ/mol. NMR relaxation experiments and molecular dynamics simulations indicate that the protein in complex with the S-stereoisomer has greater conformational entropy than in the R-complex. GIST calculations reveal additional, but smaller, contributions from solvation entropy, again in favor of the S-complex. Thus, conformational entropy apparently dominates over solvation entropy in dictating the difference in the overall entropy of binding. This case highlights an interplay between conformational entropy and solvation entropy, pointing to both opportunities and challenges in drug design

Entropy–Entropy Compensation between the Protein, Ligand, and Solvent Degrees of Freedom Fine-Tunes Affinity in Ligand Binding to Galectin-3C

Molecular recognition is fundamental to biological signaling. A central question is how individual interactions between molecular moieties affect the thermodynamics of ligand binding to proteins and how these effects might propagate beyond the immediate neighborhood of the binding site. Here, we investigate this question by introducing minor changes in ligand structure and characterizing the effects of these on ligand affinity to the carbohydrate recognition domain of galectin-3, using a combination of isothermal titration calorimetry, X-ray crystallography, NMR relaxation, and computational approaches including molecular dynamics (MD) simulations and grid inhomogeneous solvation theory (GIST). We studied a congeneric series of ligands with a fluorophenyl-triazole moiety, where the fluorine substituent varies between the ortho, meta, and para positions (denoted O, M, and P). The M and P ligands have similar affinities, whereas the O ligand has 3-fold lower affinity, reflecting differences in binding enthalpy and entropy. The results reveal surprising differences in conformational and solvation entropy among the three complexes. NMR backbone order parameters show that the O-bound protein has reduced conformational entropy compared to the M and P complexes. By contrast, the bound ligand is more flexible in the O complex, as determined by 19F NMR relaxation, ensemble-refined X-ray diffraction data, and MD simulations. Furthermore, GIST calculations indicate that the O-bound complex has less unfavorable solvation entropy compared to the other two complexes. Thus, the results indicate compensatory effects from ligand conformational entropy and water entropy, on the one hand, and protein conformational entropy, on the other hand. Taken together, these different contributions amount to entropy–entropy compensation among the system components involved in ligand binding to a target protein