The calculation of relative free-energy differences between different compounds plays an important role in drug design to identify potent binders for a given protein target. Most rigorous methods based on molecular dynamics simulations estimate the free-energy difference between pairs of ligands. Thus, the comparison of multiple ligands requires the construction of a “state graph”, in which the compounds are connected by alchemical transformations. The computational cost can be optimized by reducing the state graph to a minimal set of transformations. However, this may require individual adaptation of the sampling strategy if a transformation process does not converge in a given simulation time. In contrast, path-free methods like replica-exchange enveloping distribution sampling (RE-EDS) allow the sampling of multiple states within a single simulation without the pre-definition of alchemical transition paths. To optimize sampling and convergence, a set of RE-EDS parameters needs to be estimated in a pre-processing step. Here, we present an automated procedure for this step that determines all required parameters, improving the robustness and ease of use of the methodology. To illustrate the performance, the relative binding free energies are calculated for a series of checkpoint kinase 1 inhibitors containing challenging transformations in ring size, opening/closing, and extension, which reflect changes observed in scaffold hopping. The simulation of such transformations with RE-EDS can be conducted with conventional force fields and, in particular, without soft bond-stretching terms.

Extracellular vesicles (EVs) are membrane-enclosed biological nanoparticles with potential as diagnostic markers and carriers for therapeutics. Characterization of EVs poses severe challenges due to their complex structure and composition, requiring the combination of orthogonal analytical techniques. Here, we demonstrate how liquid chromatography combined with multi-angle light scattering (MALS) and fluorescence detection in one single apparatus can provide multiparametric characterization of EV samples, including concentration of particles, average diameter of the particles, protein amount to particle number ratio, presence of EV surface markers and lipids, EV shape, and sample purity. The method requires a small amount of sample of approximately 10 7 EVs, limited handling of the sample and data analysis time in the order of minutes; it is fully automatable and can be applied to both crude and purified samples.

Extracellular vesicles (EVs) are membrane enclosed biological nanoparticles with potential as diagnostic markers and carriers for therapeutics. Characterization of EVs poses severe challenges due to their complex structure and composition, requiring the combination of orthogonal analytical techniques. Here, we demonstrate how liquid chromatography combined with multi-angle light scattering (MALS) and fluorescence detection can provide multi-parametric characterization of EV samples, including concentration of particles, average diameter of the particles, protein amount to particle number ratio, presence of EV surface markers and lipids, EV shape and sample purity. The method requires a small amount of sample of approximately 107 EVs, limited handling of the sample and data analysis time in the order of minutes; it is fully automatable and can be applied to both crude and purified samples.