ReviewKinetic studies of protein–protein interactions
Introduction
Specific, rapid association of protein complexes is essential for diverse processes such as signal transduction, cell regulation, the immune response, the assembly of cellular components, regulation of enzymatic activities and more. The rate of association of a protein complex is limited by diffusion and geometric constraints of the binding sites (diffusion control). The reaction process may be further slowed by subsequent chemical processes [1]. In this case, association is considered reaction, or partially reaction, controlled. Typical association rates are in the order of 105–106 M−1s−1, but rate constants of >109 M−1s−1 have been measured for interactions for which the speed of the process is of functional importance. In these cases, the rate of association was found to be enhanced by strong, favourable electrostatic forces.
This review highlights recent advances in the understanding and prediction of the kinetics of protein–protein interactions. It begins with a summary of the experimental methods used to perturb the rate of association and what we can learn from these studies (adding cosolvents, introducing mutations, changing the temperature or pH). It proceeds by analysing the contribution of electrostatic steering to association and includes a description of the interaction pathway. Furthermore, hot spots and the thermodynamics of the association reaction will be discussed. Experimental methods used for measuring the kinetics of protein interactions were discussed in a recent review in this journal [2]. Computational methods will be only briefly addressed, as they are the topic of a separate review in the next issue of this journal.
Section snippets
Contribution of cosolvents
The association of a protein complex in dilute solutions requires a long diffusion step for the two proteins to collide within the rigid geometrical constraints required for binding. Perturbing the diffusion step is possible using cosolvents. These include agents that increase solution viscosity, such as glycerol or sucrose (which slow diffusion); salts, which mask electrostatic attraction; and crowding agents (PEG, BSA, etc.), which are often used to simulate cellular conditions. The use of
Probing the contribution of individual residues to kon by mutation
Measuring the effect of mutation on the rate of association is a powerful tool that may be used to decipher the mechanism of association. Extensive site-directed mutagenesis of the surface residues of TEM1–BLIP, barnase–barstar, interferon–receptor, growth hormone–receptor and interleukin-4–receptor has demonstrated that only mutations involving charged residues significantly affect the rate of association (over twofold), whereas mutations of uncharged residues are neutral 13., 14••., 18., 19.,
Hot spots for association
Hot spot residues in protein–protein interactions are defined as residues that, upon mutation, cause a large shift in binding affinity. Most often, these changes reflect an increasing koff, but large shifts in kon (>10-fold) have been observed as well 14••., 25., 26••.. Theoretical calculations of the contribution of charged residues to kon provide an interesting insight regarding the nature of hot spot residues for association. Hot spot residues seem to be located within, or in the vicinity
Thermodynamics of protein–protein association
The activation enthalpy (ΔH‡) is determined from an Eyring plot of the temperature dependence of kon (or koff), from which the activation entropy (ΔS‡) at a 1 M standard state can be calculated. Small values of ΔS‡ have been reported for the interactions between barnase–barstar, HyHEL-5–HEL and HyHEL-10–HEL 7., 28.. Moreover, for the interaction between barnase and barstar, low activation entropies were determined for a large number of mutations, with the measured change in ΔH‡ following
Describing the pathway for protein complex formation
In general terms, association of a protein complex (AB) from the unbound components (A+B) can be best described using a four-state model (Scheme 1 and Fig. 1):
In this scheme, A and B are two proteins in solution that form an initial, unstable encounter complex by diffusion (AB*), which tends to redissociate (with k−1≫k2). The protein complex AB* evolves into an intermediate (AB**) that is already committed to form the final complex (thus k3≫k−2). Describing the
The nature of the transition state along the association reaction
The most unstable species along a reaction pathway is the transition state, which occurs at the peak of a reaction coordinate diagram. In the transition state, chemical bonds are in the process of being made and broken. Transition state theory was developed for unimolecular reactions; however, it is applicable to a bimolecular protein–protein interaction if we consider only the relative change in the transition state as caused by perturbing the rate of association by mutation or by altering
Calculations versus experimental data
The rates of association of a number of protein–protein interactions have been simulated in recent years using both Brownian dynamic simulations and transition state theory (reviews in [40•] and in the next issue of this journal). The simulations were most successful in predicting the relative change in kon upon change in ionic strength or mutation, whereas the calculation of absolute values continues to be problematic 11., 14••., 41., 42••., 43.. Most of the Brownian dynamic simulations
Biological significance of binding kinetics
Is binding affinity the major factor that dictates biological activity or are the independent contributions of the rates of association and dissociation important as well? A number of studies from recent years have actually indicated that the individual kinetic constants are important. A good example is the kinetics of the cytokine–receptor interaction, whereby binding initiates the signal transduction cascade. For the interactions of interleukin-4, human growth hormone and interferon with
Conclusions
This review summarises the progress made in understanding the pathway of protein–protein association, emphasising the new experimental evidence of this process. The emerging association pathway includes the formation of an unstable diffusion encounter complex, which may evolve to form either the final complex directly or a second intermediate complex, but one that is already committed to evolve into the final complex. These precomplexes are often difficult to track experimentally; thus, it is
Acknowledgements
I wish to thank S Albeck, D Tawfik, JY Trosset and R Wade for their valuable comments on the manuscript. GS is the incumbent of the Dewey David Stone and Harry Levine career development chair.
References and recommended reading
Papers of particular interest, published within the annual period of review, have been highlighted as:
• of special interest
•• of outstanding interest
References (52)
- et al.
Measuring protein-protein interactions
Curr Opin Struct Biol
(1998) Macromolecular crowding: an important but neglected aspect of the intracellular environment
Curr Opin Struct Biol
(2001)Brownian motion in a field of force and the diffusion model of chemical reactions
Physica
(1940)- et al.
Electrostatic aspects of protein protein interactions
Curr Opin Struct Biol
(2000) - et al.
Predicting the rate enhancement of protein complex formation from the electrostatic energy of interaction
J Mol Biol
(1999) - et al.
Electrostatic enhancement of diffusion-controlled protein–protein association: Comparison of theory and experiment on barnase and barstar
J Mol Biol
(1998) - et al.
Biophysical analysis of the interaction of human Ifnar2 expressed in E. coli with IFNα2
J Mol Biol
(1999) - et al.
Energetics of protein–protein interactions: analysis of the barnase-barstar interface by single mutations and double mutant cycles
J Mol Biol
(1995) - et al.
Evaluation of direct and cooperative contributions towards the strength of buried hydrogen bonds and salt bridges
J Mol Biol
(2000) - et al.
Structural and functional analysis of the 1:1 growth hormone:receptor complex reveals the molecular basis for receptor affinity
J Mol Biol
(1998)
Mutational and structural analysis of the binding interface between type I interferons and their receptor ifnar2
J Mol Biol
New structural and functional aspects of the IFN-receptor interaction revealed by comprehensive mutational analysis of the binding interface
J Biol Chem
Experimental assignment of the structure of the transition state for the association of barnase and barstar
J Mol Biol
Mutations in the complementarity-determining regions do not cause differences in free energy during the process of formation of the activated complex between an antibody and the corresponding protein antigen
J Mol Biol
Detailed mechanism of interaction of bovine-trypsin with soybean trypsin inhibitor (Kunitz). I. Stopped flow measurements
J Biol Chem
Electrostatic dependence of the thrombin-thrombomodulin interaction
J Mol Biol
Electrostatic influence of the kinetic of ligand binding to acetylcholinesterase
J Biol Chem
Kinetics of association of anti-lysozyme monoclonal antibody D44.1 and hen-egg lysozyme
Biophys J
Computer simulation of protein–protein association kinetics: acetylcholinesterase-fasciculin
J Mol Biol
Protein–protein association: investigation of factors influencing association rates by brownian dynamics simulations
J Mol Biol
Kinetics of desolvation mediated protein–protein binding
Biophys J
Affinity dependence of the B cell response to antigen: a threshold, a ceiling, and the importance of off-rate
Immunity
Stability versus function: two competing forces in the evolution of barstar
Structure
Diffusion-controlled macromolecular interactions
Annu Rev Biophys Chem
Diffusion-limited rates for monoclonal antibody binding to cytochrome c
Biochemistry
Inhibitory mechanism of serpins. Interaction of thrombin with antithrombin and protease nexin 1
Biochemistry
Cited by (282)
Applying thermodynamics as an applicable approach to cancer diagnosis, evaluation, and therapy: A review
2023, Journal of Drug Delivery Science and TechnologyStopped-flow-time-resolved SAXS for studies of ligand-driven protein dimerization
2022, Methods in EnzymologyCosolute modulation of protein oligomerization reactions in the homeostatic timescale
2021, Biophysical JournalAdsorption of Pb<sup>2+</sup> using biosynthesized ZnO nanoparticles derived using Azadirachta indica (neem) leaf extract
2024, Biomass Conversion and BiorefineryKinetics and Timescales in Bio–Nano Interactions
2023, PhyschemInterpretable neural architecture search and transfer learning for understanding CRISPR–Cas9 off-target enzymatic reactions
2023, Nature Computational Science