Cosolvent Dimethyl Sulfoxide Influences Protein-Ligand Binding Kinetics via Solvent Viscosity Effects: Revealing the Success Rate of Complex Formation Following Diffusive Protein-Ligand Encounter

Ligand-induced protein transition state stabilization switches the binding pathway from conformational selection to induced fit

Protein-ligand complex formation is fundamental to biological function. A central question is whether proteins spontaneously adopt binding-competent conformations to which ligands bind conformational selection (CS) or whether ligands induce the binding-competent conformation induced fit (IF). Here, we resolve the CS and IF binding pathways by characterizing protein conformational dynamics over a wide range of ligand concentrations using NMR relaxation dispersion. We determined the relative flux through the two pathways using a four-state binding model that includes both CS and IF. Experiments conducted without ligand show that galectin-3 exchanges between the ground-state conformation and a high-energy conformation similar to the ligand-bound conformation, demonstrating that CS is a plausible pathway. Near-identical crystal structures of the apo and ligand-bound states suggest that the high-energy conformation in solution corresponds to the apo crystal structure. Stepwise additions of the ligand lactose induce progressive changes in the relaxation dispersions that we fit collectively to the four-state model, yielding all microscopic rate constants and binding affinities. The ligand affinity is higher for the bound-like conformation than for the ground state, as expected for CS. Nonetheless, the IF pathway contributes greater than 70% of the total flux even at low ligand concentrations. The higher flux through the IF pathway is explained by considerably higher rates of exchange between the two protein conformations in the ligand-associated state. Thus, the ligand acts to decrease the activation barrier between protein conformations in a manner reciprocal to enzymatic transition-state stabilization of reactions involving ligand transformation.

Conformational energies of biomolecules in solution: Extending the MPCONF196 benchmark with explicit water molecules

A prerequisite for the computational prediction of molecular properties like conformational energies of biomolecules is a reliable, robust, and computationally affordable method usually selected according to its performance for relevant benchmark sets. However, most of these sets comprise molecules in the gas phase and do not cover interactions with a solvent, even though biomolecules typically occur in aqueous solution. To address this issue, we introduce a with explicit water molecules solvated version of a gas-phase benchmark set containing 196 conformers of 13 peptides and other relevant macrocycles, namely MPCONF196 [J. Řezáč et al., JCTC 2018, 14, 1254-1266], and provide very accurate PNO-LCCSD(T)-F12b/AVQZ' reference values. The novel solvMPCONF196 benchmark set features two additional challenges beyond the description of conformers in the gas phase: conformer-water and water-water interactions. The overall best performing method for this set is the double hybrid revDSDPBEP86-D4/def2-QZVPP yielding conformational energies of almost coupled cluster quality. Furthermore, some (meta-)GGAs and hybrid functionals like B97M-V and ω B97M-D with a large basis set reproduce the coupled cluster reference with an MAD below 1 kcal mol- 1  . If more efficient methods are required, the composite DFT-method r2 SCAN-3c (MAD of 1.2 kcal mol- 1 ) is a good alternative, and when conformational energies of polypeptides or macrocycles with more than 500-1000 atoms are in the focus, the semi-empirical GFN2-xTB or the MMFF94 force field (for very large systems) are recommended.

DMSO-Related Effects on Ligand-Binding Properties of Lysine Methyltransferases G9a and SETD8

Being the standard solvent for preparing stock solutions of compounds for drug discovery, DMSO is always present in assay buffers in concentrations ranging from 0.1 % to 5 % (v/v). Even at the lowest concentrations, DMSO-containing solutions can have significant effects on individual proteins and possible pitfalls cannot be eliminated. Herein, we used two protein systems, the lysine methyltransferases G9a/KMT1 C and SETD8/KMT5 A, to study the effects of DMSO on protein stability and on the binding of the corresponding inhibitors, using different biophysical methods such as nano Differential Scanning Fluorimetry (nanoDSF), Differential Scanning Fluorimetry (DSF), microscale thermophoresis (MST), and surface plasmon resonance (SPR), all widely used in drug discovery screening campaigns. We demonstrated that the effects of DMSO are protein- and technique-dependent and cannot be predicted or extrapolated on the basis of previous studies using different proteins and/or different assays. Moreover, we showed that the application of orthogonal biophysical methods can lead to different binding affinity data, thus confirming the importance of using at least two different orthogonal assays in screening campaigns. This variability should be taken into account in the selection and characterization of hit compounds, in order to avoid data misinterpretation.

Solubility and Thermodynamic Analysis of Isotretinoin in Different (DMSO + Water) Mixtures

The solubility and solution thermodynamics of isotretinoin (ITN) (3) in numerous {dimethyl sulfoxide (DMSO) (1) + water (H2O) (2)} combinations were studied at 298.2-318.2 K under fixed atmospheric pressure of 101.1 kPa. A shake flask methodology was used to determine ITN solubility, and correlations were made using the "van't Hoff, Apelblat, Buchowski-Ksiazczak λh, Yalkowsky-Roseman, Jouyban-Acree, and Jouyban-Acree-van't Hoff models". In mixtures of {(DMSO (1) + H2O (2)}, the solubility of ITN in mole fractions was enhanced with the temperature and DMSO mass fraction. The mole fraction solubility of ITN was highest in neat DMSO (1.02 × 10-1 at 318.2 K) and lowest in pure H2O (3.14 × 10-7 at 298.2 K). The output of computational models revealed good relationships between the solubility data from the experiments. The dissolution of ITN was "endothermic and entropy-driven" in all of the {(DMSO (1) + H2O (2)} mixtures examined, according to the positive values of measured thermodynamic parameters. Enthalpy was discovered to be the driving force behind ITN solvation in {(DMSO (1) + H2O (2)} combinations. ITN-DMSO displayed the highest molecular interactions when compared to ITN-H2O. The outcomes of this study suggest that DMSO has a great potential for solubilizing ITN in H2O.