Semi-quantitative models for identifying potent and selective transthyretin amyloidogenesis inhibitors

Abstract

Rate-limiting dissociation of the tetrameric protein transthyretin (TTR), followed by monomer misfolding and misassembly, appears to cause degenerative diseases in humans known as the transthyretin amyloidoses, based on human genetic, biochemical and pharmacologic evidence. Small molecules that bind to the generally unoccupied thyroxine binding pockets in the native TTR tetramer kinetically stabilize the tetramer, slowing subunit dissociation proportional to the extent that the molecules stabilize the native state over the dissociative transition state-thereby inhibiting amyloidogenesis. Herein, we use previously reported structure-activity relationship data to develop two semi-quantitative algorithms for identifying the structures of potent and selective transthyretin kinetic stabilizers/amyloidogenesis inhibitors. The viability of these prediction algorithms, in particular the more robust in silico docking model, is perhaps best validated by the clinical success of tafamidis, the first-in-class drug approved in Europe, Japan, South America, and elsewhere for treating transthyretin aggregation-associated familial amyloid polyneuropathy. Tafamidis is also being evaluated in a fully-enrolled placebo-controlled clinical trial for its efficacy against TTR cardiomyopathy. These prediction algorithms will be useful for identifying second generation TTR kinetic stabilizers, should these be needed to ameliorate the central nervous system or ophthalmologic pathology caused by TTR aggregation in organs not accessed by oral tafamidis administration.

Keywords: Amyloid; Familial amyloid polyneuropathy; In silico docking; Inhibitor; Prediction algorithms; Senile systemic amyloidosis; Structural biology; Structure-based drug design; TTR; Thyroid hormone receptors; Transthyretin.

Figure 1

X-ray structure of the TTR•(201)₂ complex (PDB ID 5TZL) highlights the interactions known to be important for tight binding to TTR. Compound 201 is bound in its equivalent symmetry-related binding modes (grey and green, respectively), which results from ligand binding along the crystallographic 2-fold axis. The omit F_O-F_C density (contoured at +/− 3.5σ) for 201 is shown in Figure S3 of the Supporting Information. The binding pocket is characterized by a smaller inner cavity and a larger outer cavity, throughout which are distributed three pairs of symmetric hydrophobic depressions, referred to as the halogen binding pockets (HBPs). The iodine and chlorine atoms of 201 reside within HBPs 1 and 3. Primed amino acids or HBPs refer to symmetry-related monomers of TTR comprising each T₄ binding pocket. The phenolate of 201 makes charged interactions with the Lys 15 and 15′ residues in the outer cavity; however, it is known that other kinetic stabilizers composed of phenols exhibiting a higher pK_a preferentially bind in the opposite orientation so that the phenols can hydrogen bond with the Ser-117 and 117′ residues in the inner binding cavity (details of this phenomenon have been previously reported).^–

Figure 2

Summary of the structure-activity relationships (data derived) from a trio of previous libraries designed to screen the three substructures of a typical small molecule TTR amyloidosis inhibitor (i.e., Aryl-X, Linker-Y, and Aryl-Z).^– Substructures are quantitatively ranked according to the average experimental efficacy scores (EES) as determined using Equation 1, which evaluates the ability of a substructure to afford potent aggregation inhibitors in vitro that bind selectively to TTR in human blood plasma ex vivo.

Figure 3

Examination of the correlation between Predicted Efficacy Scores (PES) of kinetic stabilizers and their Experimental Efficacy Scores (EES). EES and PES values for individual compounds were calculated using Equations 1 and 2, respectively. The dashed line at EES = 0.667 represents a scenario where an inhibitor binds with a stoichiometry of 1 molecule per TTR tetramer, which has been shown sufficient to completely inhibit TTR aggregation (i.e., 0% fibril formation). Solid black data points represent the percentage of compounds within the 0.2 PES bins that exceed the EES = 0.667 cutoff. The area shaded grey represents the PES region where significant enrichment of molecules above this cutoff occurs: that is, where the greatest proportion of highly desirable, potent and selective TTR aggregation inhibitors are predicted (PES > 1.8). Please refer to Table S1 in the Supporting Information for a complete tabulation of all values.

Figure 4

Examination of the correlation between kinetic stabilizer Predicted Efficacy Scores (PES) of the candidate kinetic stabilizers and their Relative Thyroid Hormone (TH) receptor binding. A cutoff for undesirable TH receptor binding has been selected at 0.2, represented by the dashed line. Solid black data points represent the percentage of compounds within the 0.2 PES bins that are below this threshold. The area shaded grey represents the PES region where significant enrichment of molecules below this cutoff occurs: that is, where the greatest proportion of highly desirable molecules that do not bind to the TH receptor are predicted (PES < 2.5). Please refer to Table S1 in the Supporting Information for a complete tabulation of all values.

Figure 5

Examination of the correlation between the Predicted Efficacy Scores (PES) of the candidate kinetic stabilizers and their Thyroid Hormone Receptor Experimental Efficacy Scores (THREE Scores). THREE Score values for individual compounds were calculated using Equation 3. The cutoff line at 0.667 represents 1 inhibitor bound per TTR tetramer as described in Figure 3. Solid black data points represent the percentage of compounds within the 0.2 PES bins that exceed the 0.667 cutoff. As in Figure 3, the highest proportion of potent and selective TTR aggregation inhibitors occurs at PES values >1.8; however, at PES values above 2.5, binding to the TH receptor decreases the THREE score values significantly. Thus, the most promising potent and selective TTR amyloidogenesis inhibitors that display minimal binding to the TH receptor are predicted in the PES = 1.8–2.5 range (i.e., the area shaded grey). Please refer to Table S1 in the Supporting Information for a complete tabulation of all values.

Figure 6

The lowest energy docked conformation of inhibitor 201 calculated using Autodock 4 superimposes nearly identically with the TTR•(201)₂ co-crystal structure (RMSD = 0.44 Å; calculated using the Accelrys Discovery Studio 4 crystallographic visualization program).

Figure 7

Examination of the correlations between corrected in silico docking scores of candidate kinetic stabilizers and their in vitro % inhibition of TTR aggregation (A); ex vivo plasma TTR binding stoichiometry (B); Experimental Efficacy Scores (C); Relative Thyroid Hormone receptor binding (D); and Thyroid Hormone Receptor Experimental Efficacy Scores (E). Please refer to Table S1 in the Supporting Information for a complete tabulation of all values. In panels A, B, C, and E, solid black data points represent the percentage of compounds within the 0.5 docking score bins that are above the respective thresholds (90% for inhibition of TTR aggregation for panel A; 1 molecule bound per TTR tetramer for panel B; and 0.667 for C and E, representing 100% inhibition of TTR aggregation and 1 molecule bound per tetramer). In panel D, solid black data points represent the percentage of compounds within the 0.5 docking score bins that are below the 0.2 threshold for undesirable thyroid hormone receptor binding. Areas shaded grey represent the docking score regions where significant enrichment of molecules above the respective cutoffs occur (or below with respect to thyroid hormone receptor binding). In panel E, the greatest proportion of highly desirable, potent, and selective TTR aggregation inhibitors are predicted within the −7.5 to −9.0 docking score region.