Induced fit, conformational selection and independent dynamic segments: an extended view of binding events

Abstract

Single molecule and NMR measurements of protein dynamics increasingly uncover the complexity of binding scenarios. Here, we describe an extended conformational selection model that embraces a repertoire of selection and adjustment processes. Induced fit can be viewed as a subset of this repertoire, whose contribution is affected by the bond types stabilizing the interaction and the differences between the interacting partners. We argue that protein segments whose dynamics are distinct from the rest of the protein ('discrete breathers') can govern conformational transitions and allosteric propagation that accompany binding processes and, as such, might be more sensitive to mutational events. Additionally, we highlight the dynamic complexity of binding scenarios as they relate to events such as aggregation and signalling, and the crowded cellular environment.

Figure 1

The extended conformational selection model. The ‘native state’ at the bottom of the two illustrative energy landscapes (folding funnels) of the two binding partners usually can be described as an assembly of conformers, which are visualized as secondary minima at the magnified bottom sections of the energy landscape in the circles and at the upper part of the figure. The top segment of the figure contains our proposed extended conformational selection model. For simplicity, we restrict our treatment to the encounter of two partners, because the probability for a simultaneous binding of more than two partners is extremely small. The actual conformation of partner A and B is described as their position on the energy landscape marked by red and yellow dots, respectively. Conformational selection is marked by the double headed arrows. As the two partners approach each other, the probability of occurrence of their conformers is changing, and so does the shape of their energy landscape. The actual sequence of these mutual conformational selection and preceding or subsequent conformational adjustment steps forms the ‘binding trajectory’ (marked with arrows) covered by partners A and B. For the sake of simplicity we restricted the number of binding trajectories to two. This number is several magnitudes higher in real situations. This general scenario is obviously much less complex, if the conformational ensemble of one of the partners is negligible compared to that of the other partner, e.g. in the case of binding of small substrates or allosteric modifiers to a protein as shown on the 4 panels. The lower part of the figure contains four scenarios of the extended conformational selection model, where binding trajectories are less complex. A) the classical lock and key model, where both partners are either rigid, or have exactly matching binding surfaces. B) the classical induced fit model, where Partner B first binds to the single available conformation of Partner A, and then induces a conformational change of Partner A. C) the original conformational selection model, where Partner B binds one of the several fluctuating conformations of Partner A and no further conformational rearrangement occurs. D) Partner B first binds one of the several fluctuating conformations of Partner A, and induces a subsequent conformational rearrangement of Partner B. As a discriminating feature of all scenarios of Panels A through D from the extended conformational selection model shown at the top centre, on all Panels Partner B has a single conformational status instead of a conformational ensemble. For the sake of simplicity its energy landscape is not shown. This approximation works well, if Partner B is small and/or rigid, like a small molecule or DNA. As a further simplification, Partner A’s conformational landscape is not changed by Partner B on Panels A through D.

Figure 2

Inter-modular regions might act as key structural contributors of conformational changes in proteins. The two examples highlight amino acids located in the overlapping regions of residue-network modules. These inter-modular segments regulate the coordination of motion of the two modules they connect. Panel A: key inter-modular links and their end-point residues of Glu-tRNA synthase at the centre of the majority of shortest paths connecting nodes in different communities of the residue-network are marked with red lines and spheres [39]. Residue network communities are marked with different colours. (The image is a courtesy of Zaida Luthey-Shulten and John Eargle). Panel B: inter-modular regions of clusters of the ribosome-bound termination factor RF2 are marked with arrows. Clusters of correlated motions were determined from EMBD (Electron Microscopy Data Bank) data using normal mode analysis and were marked with different colours and numbers [66,67]. The asterisk denotes the peptidyl-transferase centre. The region between clusters 7 and 5, as well as clusters 1 and 2 connect clusters 7 (blue) and 6 (red) with the rest of the RF2 structure, respectively. Clusters 7 and 6 are the most distinctively moving segments of RF2 (The image is a courtesy of Mark Bathe and Do-Nyun Kim).