Discrimination between conformational selection and induced fit protein-ligand binding using Integrated Global Fit analysis

Analytical and functional aspects of protein-ligand interactions: Beyond induced fit and conformational selection

Ligand-dependent changes in protein conformation are foundational to biology. Historical mechanistic models for substrate-specific proteins are induced fit (IF) and conformational selection (CS), which invoke a change in protein conformation after ligand binds or before ligand binds, respectively. These mechanisms have important, but rarely discussed, functional relevance because IF vs. CS can differentially affect a protein's substrate specificity or promiscuity, and its regulatory properties. The modern view of proteins as conformational ensembles in both ligand free and bound states, together with the realization that most proteins exhibit some substrate promiscuity, demands a deeper interpretation of the historical models and provides an opportunity to improve mechanistic analyses. Here we describe alternative analytical strategies for distinguishing the historical models, including the more complex expanded versions of IF and CS. Functional implications of the different models are described. We provide an alternative perspective based on protein ensembles interacting with ligand ensembles that clarifies how a single protein can 'apparently' exploit different mechanisms for different ligands. Mechanistic information about protein ensembles can be optimized when they are probed with multiple ligands.

Induced fit versus conformational selection: From rate constants to fluxes… and back to rate constants

Induced fit- (IF) and conformational selection (CS) binding mechanisms have long been regarded to be mutually exclusive. Yet, they are now increasingly considered to produce the final ligand-target complex alongside within a thermodynamic cycle. This viewpoint benefited from the introduction of binding fluxes as a tool for analyzing the overall behavior of such cycle. This study aims to provide more vivid and applicable insights into this emerging field. In this respect, combining differential equation- based simulations and hitherto little explored alternative modes of calculation provide concordant information about the intricate workings of such cycle. In line with previous reports, we observe that the relative contribution of IF increases with the ligand concentration at equilibrium. Yet the baseline contribution may vary from one case to another and simulations as well as calculations show that this parameter is essentially regulated by the dissociation rate of both pathways. Closer attention should be paid to how the contributions of IF and CS compare at physiologically relevant drug/ligand concentrations. To this end, a simple equation discloses how changing a limited set of "microscopic" rate constants can extend the concentration range at which CS contributes most effectively. Finally, it could also be beneficial to extend the utilization of flux- based approaches to more physiologically relevant time scales and alternative binding models.

Mechanisms of ligand binding

Many processes in chemistry and biology involve interactions of a ligand with its molecular target. Interest in the mechanism governing such interactions has dominated theoretical and experimental analysis for over a century. The interpretation of molecular recognition has evolved from a simple rigid body association of the ligand with its target to appreciation of the key role played by conformational transitions. Two conceptually distinct descriptions have had a profound impact on our understanding of mechanisms of ligand binding. The first description, referred to as induced fit, assumes that conformational changes follow the initial binding step to optimize the complex between the ligand and its target. The second description, referred to as conformational selection, assumes that the free target exists in multiple conformations in equilibrium and that the ligand selects the optimal one for binding. Both descriptions can be merged into more complex reaction schemes that better describe the functional repertoire of macromolecular systems. This review deals with basic mechanisms of ligand binding, with special emphasis on induced fit, conformational selection, and their mathematical foundations to provide rigorous context for the analysis and interpretation of experimental data. We show that conformational selection is a surprisingly versatile mechanism that includes induced fit as a mathematical special case and even captures kinetic properties of more complex reaction schemes. These features make conformational selection a dominant mechanism of molecular recognition in biology, consistent with the rich conformational landscape accessible to biological macromolecules being unraveled by structural biology.

Kinetically selective and potent inhibitors of HDAC8

Histone deacetylase 8 (HDAC8) is an established and validated target for T-cell lymphoma and childhood neuroblastoma. The active site binding pocket of HDAC8 is highly conserved among all zinc-containing representatives of the histone deacetylase (HDAC) family. This explains that most HDACs are unselectively recognized by similar inhibitors featuring a zinc binding group (ZBG), a hydrophobic linker and a head group. In the light of this difficulty, the creation of isoenzyme-selectivity is one of the major challenges in the development of HDAC inhibitors. In a series of trifluoromethylketone inhibitors of HDAC8 compound 10 shows a distinct binding mechanism and a dramatically increased residence time (RT) providing kinetic selectivity against HDAC4. Combining the binding kinetics results with computational docking and binding site flexibility analysis suggests that 10 occupies the conserved catalytic site as well as an adjacent transient sub-pocket of HDAC8.

Determination of the binding mechanism of histone deacetylase inhibitors

This article places its focus on methods and tools enabling the elucidation of the mechanism by which ligands, small-molecule inhibitors, or substrates interact with zinc-containing bacterial or human members of the histone deacetylase family (HDACs). These methods include biochemical and biophysical approaches and can be subdivided into equilibrium and kinetic methods. More information about the exact mode of action can be obtained by combining these methods with specific mutant variants of the enzymes and/or series of structural similar ligands. All available equilibrium and kinetic data including additional information from 3D structures of HDAC-ligand complexes can be beneficially combined in a data analysis procedure called Integrated Global-Fit analysis eventually providing the most likely binding mechanism.

"Multiple partial recognitions in dynamic equilibrium" in the binding sites of proteins form the molecular basis of promiscuous recognition of structurally diverse ligands

Promiscuous recognition of ligands by proteins is as important as strict recognition in numerous biological processes. In living cells, many short, linear amino acid motifs function as targeting signals in proteins to specify the final destination of the protein transport. In general, the target signal is defined by a consensus sequence containing wild-characters, and hence represented by diverse amino acid sequences. The classical lock-and-key or induced-fit/conformational selection mechanism may not cover all aspects of the promiscuous recognition. On the basis of our crystallographic and NMR studies on the mitochondrial Tom20 protein-presequence interaction, we proposed a new hypothetical mechanism based on "a rapid equilibrium of multiple states with partial recognitions". This dynamic, multiple recognition mode enables the Tom20 receptor to recognize diverse mitochondrial presequences with nearly equal affinities. The plant Tom20 is evolutionally unrelated to the animal Tom20 in our study, but is a functional homolog of the animal/fungal Tom20. NMR studies by another research group revealed that the presequence binding by the plant Tom20 was not fully explained by simple interaction modes, suggesting the presence of a similar dynamic, multiple recognition mode. Circumstantial evidence also suggested that similar dynamic mechanisms may be applicable to other promiscuous recognitions of signal peptides by the SRP54/Ffh and SecA proteins.

Impact of binding mechanism on selective inhibition of histone deacetylase isoforms

Industrialized drug screening campaigns usually deliver hundreds of compounds that are active on a particular pharmaceutical target. In light of high failure rates of drug candidates due to unforeseeable off-target toxicity, the early identification of the most promising compounds with high potential for target selectivity is an urgent need to improve the quality of lead compounds and lower attrition rates in the drug development process. The reliable prediction of the selectivity of active substances for a target protein is a challenging task. A comprehensive study of the binding kinetics, thermodynamics, and selectivity of chemically related ligands of histone deacetylase (HDAC) like amidohydrolase from Pseudomonas aeruginosa (HDAH_pa ) reveals one general binding mechanism for all analyzed compounds consisting of a preceding conformational selection step followed by an optional subsequent induced fit. Depending on the chemical structure, the ligands bind to one or two of at least three protein conformations with different rate constants. Although these kinetic and mechanistic differences hamper the predictability of selectivity for the HDAC inhibitors, we demonstrate that the enthalpy-weighted binding constant KdΔH is a useful metric to predict isoform selectivity of inhibitors against HDAC enzymes and relatively robust toward different but related binding mechanisms.

Induced Fit Is a Special Case of Conformational Selection

Conformational selection (CS) and induced fit (IF) are two widely used interpretations of binding of a ligand to biological macromolecules. Both mechanisms envision a two-step reaction in which a conformational transition either precedes (CS) or follows (IF) the binding step. Under pseudo-first-order conditions where the ligand is in excess compared to the macromolecule, both mechanisms produce two relaxations. A fast one eventually increases linearly with ligand concentration and reflects the binding interaction. A slow one saturates to a constant value after decreasing or increasing hyperbolically with ligand concentration. This relaxation is the one most often accessible to experimental measurements and is potentially diagnostic of the mechanism involved. A relaxation that decreases unequivocally identifies CS, but a hyperbolic increase is compatible with both CS and IF. The potential ambiguity between the two mechanisms is more than qualitative. Here we show that the entire kinetic repertoire of IF is nothing but a mathematical special case of CS as revealed by a simple transformation of the rate constants, which emphasizes the need for independent support of either mechanism from additional experimental evidence. We discuss a simple strategy for distinguishing between IF and CS under the most common conditions encountered in practice, i.e., when the ligand is in excess compared to the macromolecule and a single relaxation is accessible to experimental measurements.

Rate Constants and Mechanisms of Protein-Ligand Binding

Whereas protein-ligand binding affinities have long-established prominence, binding rate constants and binding mechanisms have gained increasing attention in recent years. Both new computational methods and new experimental techniques have been developed to characterize the latter properties. It is now realized that binding mechanisms, like binding rate constants, can and should be quantitatively determined. In this review, we summarize studies and synthesize ideas on several topics in the hope of providing a coherent picture of and physical insight into binding kinetics. The topics include microscopic formulation of the kinetic problem and its reduction to simple rate equations; computation of binding rate constants; quantitative determination of binding mechanisms; and elucidation of physical factors that control binding rate constants and mechanisms.