Solubility Advantage of Amorphous Ketoprofen. Thermodynamic and Kinetic Aspects by Molecular Dynamics and Free Energy Approaches

Regularized Bennett and Zwanzig free energy estimators

We consider the problem of free energy estimation from the general perspective of regularization and Bayes estimation theory. We try to take advantage of an assumed a priori knowledge of the free energy. We reformulate the original Bennett acceptance ratio method, in this perspective, devise a numerical algorithm to solve it, and give a closed formula to estimate the confidence in the prior. Finally, we test the derived estimators by applying them to a toy model.

Improved Solubility and Dissolution Rate of Ketoprofen by the Formation of Multicomponent Crystals with Tromethamine

This study aims to improve the dissolution rate of ketoprofen by preparing multicomponent crystals with tromethamine. The multicomponent crystals (equimolar ratio) of ketoprofen and tromethamine were prepared by the solvent co-evaporation method. The solid-state properties of the resulting powder were characterized by powder X-ray diffraction, DSC thermal analysis, FT–IR spectroscopy, solubility, and in vitro dissolution rate. The crystal structure of the multicomponent crystal was determined by single-crystal X-ray diffraction analysis. The results showed that the powder X-ray diffraction pattern of the ketoprofen–tromethamine binary system was different from that of the starting materials. This difference indicates the formation of a new crystalline phase between ketoprofen and tromethamine (equimolar ratio). The DSC thermogram of the ketoprofen–tromethamine binary system exhibited a single and sharp endothermic peak at 128.67 °C, attributed to the melting point of a multicomponent crystal of ketoprofen–tromethamine. A single-crystal X-ray analysis revealed that ketoprofen–tromethamine formed a layered structure, salt-type multicomponent crystal. The solubility and dissolution rate of the multicomponent crystal were notably enhanced compared to the intact ketoprofen. The ketoprofen–tromethamine binary system forms salt-type multicomponent crystals, which can significantly increase the solubility and dissolution rate.

Machine Learning and Enhanced Sampling Simulations for Computing the Potential of Mean Force and Standard Binding Free Energy

Computational capabilities are rapidly increasing, primarily because of the availability of GPU-based architectures. This creates unprecedented simulative possibilities for the systematic and robust computation of thermodynamic observables, including the free energy of a drug binding to a target. In contrast to calculations of relative binding free energy, which are nowadays widely exploited for drug discovery, we here push the boundary of computing the binding free energy and the potential of mean force. We introduce a novel protocol that leverages enhanced sampling, machine learning, and ad hoc algorithms to limit human intervention, computing time, and free parameters in free energy calculations. We first validate the method on a host-guest system, and then we apply the protocol to glycogen synthase kinase 3 beta, a protein kinase of pharmacological interest. Overall, we obtain a good correlation with experimental values in relative and absolute terms. While we focus on protein-ligand binding, the strategy is of broad applicability to any complex event that can be described with a path collective variable. We systematically discuss key details that influence the final result. The parameters and simulation settings are available at PLUMED-NEST to allow full reproducibility.