Allostery and population shift in drug discovery

Abstract

Proteins can exist in a large number of conformations around their native states that can be characterized by an energy landscape. The landscape illustrates individual valleys, which are the conformational substates. From the functional standpoint, there are two key points: first, all functionally relevant substates pre-exist; and second, the landscape is dynamic and the relative populations of the substates will change following allosteric events. Allosteric events perturb the structure, and the energetic strain propagates and shifts the population. This can lead to changes in the shapes and properties of target binding sites. Here we present an overview of dynamic conformational ensembles focusing on allosteric events in signaling. We propose that combining equilibrium fluctuation concepts with genomic screens could help drug discovery.

Figure 1

Schematic representation of a dynamic energy landscape and population shift following a binding event, in this case involving a transcription factor (TF) protein. The dynamic landscape is reflected by the changes in the relative depths of the wells. TF (in blue) binds to DNA response elements (REs) (in pink, yellow or green). The different RE colors reflect differences in the RE sequences. The REs are allosteric effectors. Since each sequence is different, this leads allosterically to different TF surface conformations (different shapes at the top of TF in the figure). The most stable complex is TF bound to yellow RE (left-hand side). On the right-hand side, a cofactor protein (in red) now binds to the most complementary conformation of TF (TF in complex with RE, in pink) that shifts the free energy landscape. The complex of TF bound to RE (in pink) becomes the most stable complex; thus deepest minima. Similar scenarios will take place with allosteric drugs.

Figure 2

Illustration of the conformational changes in allosteric proteins. Known inactive and active structures for four signaling proteins (CheY, Rap2a, Cdc42, and IRK) are obtained from the PDB. Inactive (in pink color) structures are superimposed onto active (cyan) structures. The superposition is based on matched residues with the distance between superimposed C^α atoms ≤2 Å. The conformational changes (unmatched residues) are highlighted in red and blue, respectively, for the inactive and active structures. The classification of the conformational changes is based on Tsai et al. [^•]. (a) CheY (PDB IDs: 3chyA and 1fqwA) is classified as showing no conformational change; (b) Rap2a (PDB IDs: 1kaoA and 2rapA) subtle conformational change; (c) Cdc42 (PDB IDs: 1an0A and 1nf3A) minor conformational change (d) IRK (PDB IDs: 1irkA and 1ir3A) large conformational change.

Figure 3

Allosteric Ras protein in MAPK signaling pathway. (a) Visualization of the conformational change in Ras protein upon activation by Sos. Inactive and active allosteric Ras protein structures (obtained from the PDB) are shown in pink and cyan color, respectively. The superposition is based on matched residues with the distance between superimposed C^α atoms ≤2 Å. The conformational changes (unmatched residues) are highlighted in red and blue, respectively, for inactive and active Ras. Conformational changes correspond mostly to residues from switch I (residues 30–38) and switch II (residues 60–76) Ras regions. (b) The interaction between activated Ras (PDB code: 1bkdR) and Ras binding domain of B-Raf (3ny5A) is predicted by Prism [41]. Binding site corresponds to switch I and switch II regions. B-Raf can bind to activated Ras favorably whereas it cannot bind to the inactive structure.

Figure 4

Allosteric mechanism of inhibition. (a) A model illustrating allosteric inhibition of HGFA via antibody Fab40 based on Ganesan et al. [^••]. In the functionally active state, HGFA can interact with substrates through a small hydrophobic pocket (in green color). Upon Fab40 binding, the equilibrium is shifted to the inactive state (right-hand side). The hydrophobic contact between Trp96 of Fab40 and Val96 of HGFA and the movement of 99-loop residues (allosteric switch, in red) of HGFA lead to partial collapse of the substrate binding site on HGFA inhibiting enzyme activity. Removing a key interaction at the HGFA/Fab40 interface in the Trp96H-deletion mutant Fab40.ΔTrp, there is no movement of 99-loop (left-hand side). The HGFA-Fab40.ΔTrp interaction has negligible effects on the substrate binding site and does not inhibit enzyme activity [^••]. In the figure, the HGFA with no inhibitor is in gray. On the right-hand side, HGFA is in gray and Fab40 in yellow. On the left-hand side, HGFA is in gray and Fab40.ΔTrp in orange. The PDB codes are 1ybw, 3k2u, and 2wub, respectively. (b) Different conformations of Abl-kinase pre-exist in equilibrium. Three key Abl kinase domain conformations are shown: (i) inactive Abl in which the Asp-Phe-Gly (DFG) motif in the activation loop is flipped out; (ii) inactive Src-like Abl in which the DFG motif is in and helix αC swings out of the active site; (iii) active Abl in which the DFG motif is in and the activation loop displays an open and extended conformation. The PDB codes are 1iep, 2g1t, and 1m52, respectively. The DFG motif and the activaton loop are colored red, helix αC magenta, and the catalytic loop green. In many kinases, the DFG-out conformation is less stable than the DFG-in conformation [71]. The cancer drug imatinib selectively targets the DGF-out inactive Abl conformation [^••] and shifts the equilibrium toward this conformation, thereby blocking the Abl kinase activity. The illustrated free energy landscape of Abl is hypothetical and the energy barriers separating the conformations are not known.