Thermodynamics and kinetics of protein−ligand binding are both important aspects for the design of novel drug molecules. Presently, thermodynamic data are collected with isothermal titration calorimetry, while kinetic data are mostly derived from surface plasmon resonance. The new method of kinITC provides both thermodynamic and kinetic data from calorimetric titration measurements. The present study demonstrates the convenient collection of calorimetric data suitable for both thermodynamic and kinetic analysis for two series of congeneric ligands of human carbonic anhydrase II and correlates these findings with structural data obtained by macromolecular crystallography to shed light on the importance of shape complementarity for thermodynamics and kinetics governing a protein−ligand binding event. The study shows how minute chemical alterations change preferred ligand conformation and can be used to manipulate thermodynamic and kinetic signatures of binding. They give rise to the observation that analogous n-alkyl and nalkyloxy derivatives of identical chain length swap their binding kinetic properties at unchanged binding affinity.

In drug design, the importance of molecular solvation and desolvation is increasingly appreciated and water molecules are recognized as active contributors to protein–ligand binding. However, despite a number of theoretical approaches, computational tools are still far from routinely integrating solvation features into rational structure–affinity relationships (SARs). In this contribution, we present a set of solvent functional-based models, which calculate the relative binding free energy contributions resulting from solvation for a diverse set of 53 thrombin protein–ligand complexes. These protein–ligand complexes were further matched into chemically similar pairs of ligand molecules. Our solvent functionals are based on molecular dynamics simulations in conjunction with grid inhomogeneous solvation theory (GIST) processing, and they are calibrated using accurate experimental data from isothermal titration calorimetry (ITC) measurements. We found that excellent agreement with experimental measurements can be achieved by considering either the desolvation of the protein-binding pocket or the ligand in solution prior to binding. The incorporation of contributions from the protein–ligand complexes generally results in good agreement with experimental measurements but require additional adjustment of spatial cutoff parameters. In addition, we investigated the transfer of the trained solvent functionals to another protein target, which revealed deviating performance results, indicating a target-specific treatment of solvation features within the model. Together with our tool GIST-based processing of solvent functionals (Gips), we provide a way to automatically generate solvent functional parameters from GIST data and allow for the design of compounds with favorable solvation properties given the chemical similarity and affinity range of the matching pairs in the training set. Finally, we reflect on the resemblance with the popular three-dimensional quantitative SAR (3D-QSAR) method, as our study allows for (retrospective) insights on the high predictive power of this well-established method.

Structural fixation of a ligand in its bioactive conformation may, due to entropic reasons, improve affinity. We present a congeneric series of thrombin ligands with a variety of functional groups triggering preorganization prior to binding. Fixation in solution and complex formation have been characterized by crystallography, isothermal titration calorimetry (ITC), and molecular dynamics (MD) simulations. First, we show why these preorganizing modifications do not affect the overall binding mode and how key interactions are preserved. Next, we demonstrate how preorganization thermodynamics can be largely dominated by enthalpy rather than entropy because of the significant population of low-energy conformations. Furthermore, a salt bridge is shielded by actively reducing its surface exposure, thus leading to an enhanced enthalpic binding profile. Our results suggest that the consideration of the ligand solution ensemble by MD simulation is necessary to predict preorganizing modifications that enhance the binding behavior of already promising binders.

The mechanism by which water molecules modulate biomolecular interactions and the time scale of microscopic solvation processes are usually not known. This is particularly problematic as it prevents the incorporation of effects of water molecules into the design of drug molecules with optimal binding kinetics and selectivity. We investigated this crucial problem of drug discovery using trypsin and thrombin in complex with benzamidine and N-amidinopiperidine. For these systems, we studied the mechanism and time scale of solvation using molecular dynamics and umbrella sampling calculations. In thrombin, water molecules are seemingly stable in the apo binding pocket and have an exchange rate on the nanosecond time scale. On the contrary, water molecules in apo trypsin exchange approximately one order of magnitude faster than in thrombin. This difference in the exchange rate is due to internal water channels that are only found in thrombin linking the interior of the binding pocket with bulk solvent. These cause the exchange rate of water molecules to be independent of the ligand molecule. However, in the case of trypsin, the solvent exchange rate greatly varies between the two complexes, indicating a strong dependence on the ligand molecule. Furthermore, the binding mechanism of the ligand molecules critically depends on water molecules that intercalate between key amino acids and the ligand, leading to enhanced water residence times in intermediate dissociation steps. Our findings strongly indicate a selectivity discriminating role of water molecules for these two proteins and underline the functional interplay between water channels and binding affinity of ligand molecules.

Water molecules and their impact on the enthalpy and entropy of protein–ligand binding are of considerable interest in drug discovery. In this contribution, we use multiobjective optimization to fit the solvent enthalpy and entropy scoring terms of grid inhomogeneous solvation theory (GIST)-based solvent functionals to measured isothermal titration calorimetry (ITC) data of protein–ligand-binding reactions for ligand pairs of the protein thrombin. For the investigated ligand pairs, the overwhelming contribution to the relative binding affinity difference is assumed to be attributed to the contribution of water molecules. We present different implementations of the solvent functionals and then proceed by analyzing the most successful one in more detail through error assessment and presentation of the scoring regions in the binding pocket and the unbound ligands of selected examples. We find overall good agreement between calculated and experimental data and, although physically not fully justified, the ligand-desolvation score increases binding affinity, thus suggesting that the solvent molecules on the surface of the unbound ligand constitute a proxy for interactions gained through the protein. Furthermore, we find limited transferability of the parameters even between similar protein targets, thus suggesting refitting for each new protein target. Possible reasons for the limited transferability may arise through the initial assumption of dominating water contributions to binding affinity. Nonetheless, overall our study demonstrates a consistent approach to assign thermodynamic quantities to water molecules that is sensible to measured thermodynamic signatures and enables bridging the gap between experimentally determined water positions in protein–ligand complexes and measured thermodynamic data.