Thermodynamics-based drug design: strategies for inhibiting protein-protein interactions

Abstract

The inhibition of protein-protein interactions and their ensuing signaling processes play an increasingly important role in modern medicine. Small molecular-weight inhibitors that can be administered orally are the preferred approach but efficient strategies for developing them are not yet generally available. Due to the large size difference between the protein-protein interface and the small molecule, inhibitor interactions are expected to extend to only a small region of the interface. If this is the case, classical competitive inhibition may be hard to achieve. In addition, competitive inhibition wastes binding energy that can be effectively used to inhibit signaling. The best and most energy-efficient approach would be the development of small molecules that bind at the protein-protein interface and inhibit the signaling process without displacing the protein ligand. This approach seems feasible knowing that the binding energy is not evenly distributed within the binding interface but concentrated in discrete hotspots, and that the initiation of signaling may not overlap with those hotspots. We outline a general protein-protein inhibition model that extends from competitive to noncompetitive scenarios and apply it to the development of HIV-1 gp120-CD4 inhibitors. This rigorous model can be easily applied to the analysis of protein-protein inhibition data and used as a tool in the optimization of inhibitor molecules.

Figure 1. Continuum model for the inhibition of protein–protein interactions

The binding energy between two proteins is not evenly distributed throughout the binding interface. Since the protein-binding surface is larger than the surface of a small molecular-weight (500-Da) compound, the possibility exists that it will only perturb a binding spot and still allow the two proteins to bind, albeit with lower affinity. Depending on the exact binding location and the interactions of the small molecule, a variable effect may be obtained. The effect of the small molecule is given by the parameter β. If β = 0 the classical all-or-none competitive situation is obtained. If β = 1 the inhibitor does not affect the protein-binding affinity. Intermediate effects are obtained by different β values.

Figure 2. Fraction of inhibitor bound for different degrees of competitiveness

This shows the fraction of a protein receptor bound to inhibitor as function of inhibitor concentration for β values of 0, 0.1, 0.2, 0.3, 0.5, 0.7 and 1.0. The curves were calculated by using a binding affinity for the inhibitor of 100 nM and at constant [L]/K_d ratio of 10. To facilitate reader visualization, the inhibitor concentration is expressed in µg/mL by assuming a molecular weight of 500 g/mol.

Figure 3. The inhibitor concentration at which 95% protein saturation is obtained for different β values

The values have been plotted for a wide range of [L]/K_d values. For these simulations, the inhibitor affinity has been assumed to be 10 nM and its molecular weight 500 g/mol.

Figure 4. Chemical structures of some HIV-1 cell entry inhibitors: (A) NBD-556, (B) Compound 14 and (C) BMS-806

Figure 5. The structure of gp120 (blue) in complex with CD4 (green) and with the inhibitor NBD-556 (red) docked into the structure of gp120 (PDB entry 1G9M)

NBD-556 binds within the large interaction surface. The figure clearly illustrates the size difference between the CD4 binding footprint and the small-molecule inhibitor. The arrows indicate the location of important amino acid polymorphisms between gp120 from subtype B and subtype A.

Figure 6. The concentration of NBD-556, compound 14 and BMS-806 required for 99% saturation, [I]₉₉, of subtype B gp120 as a function of the [sCD4]/K_d ratio

NBD-556 and compound 14 have similar affinities, however, NBD-556 is the most competitive and the concentration required for saturation of gp120 is much higher for NBD-556 than for compound 14.

Figure 7. Comparison of the [I]₉₉ values for inhibition of gp120 from subtypes A and B with NBD-556 and BMS-806

NBD-556 is a much less competitive inhibitor of CD4 binding to subtype A than subtype B gp120 and saturation is reached at lower concentration despite the somewhat weaker affinity.