Inhibition of fibril formation is considered a possible treatment strategy for amyloid-related diseases. Understanding the molecular nature of inhibitor action is crucial for the design of drug candidates. In the present review, we describe the common kinetic models of fibril formation and classify known inhibitors by the mechanism of their interactions with the aggregating protein and its oligomers. This mechanism determines the step or steps of the aggregation process that become inhibited and the observed changes in kinetics and equilibrium of fibril formation. The results of numerous studies indicate that possible approaches to antiamyloid inhibitor discovery include the search for the strong binders of protein monomers, cappers blocking the ends of the growing fibril, or the species absorbing on the surface of oligomers preventing nucleation. Strongly binding inhibitors stabilizing the native state can be promising for the structured proteins while designing the drug candidates targeting disordered proteins is challenging.

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A dataset containing the experimental values of the equilibrium binding constants of clinical drugs, and some other organic ligands with human and mammalian (predominantly bovine) serum albumins, is assembled. The affinity of drugs to albumin governs their pharmacokinetic properties, related to permeability through physiological barriers and distribution within the organism. The dataset contains 1755 records gathered from 346 original literature sources describing the albumin affinity of 324 different substances. The data were extracted from both articles and existing protein-binding databases applied strict data selection rules in order to exclude the values influenced by the third-party compounds. The dataset provides the details on the experimental conditions of the measurements, such as temperature; protein and ligand concentrations; buffer pH, composition and concentration; and the method and model used for the binding constant calculations. Analysis of the data reveals discrepancies between the values from different studies, as well as the significant influence of the measurement method. Averaging the values from multiple independent measurements from the dataset may help to determine the reliable values of the binding constants. The dataset can be used as the reference dataset for the development of predictive models to calculate binding constants, and as the choice for the experimental setup in the future albumin-binding studies.

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Experimental data on the affinity of various substances to albumin are essential for the development of empirical models to predict plasma binding of drug candidates. Binding of 24 substituted benzoic acid anions to bovine serum albumin was studied using spectrofluorimetric titration. The equilibrium constants of binding at 298 K were determined according to 1:1 complex formation model. The relationships between the ligand structure and albumin affinity are analyzed. The binding constant values for m- and p-monosubstituted acids show a good correlation with the Hammett constants of substituents. Two- and three-parameter quantitative structure–activity relationship (QSAR) models with theoretical molecular descriptors are able to satisfactorily describe the obtained values for the whole set of acids. It is shown that the electron-density distribution in the aromatic ring exerts crucial influence on the albumin affinity.