Protein–protein interaction

The bacterial nitrogenase enzyme is formed by a protein-protein interaction between two copies of two different proteins. One protein is shown in shades of green, the other in shades of blue and purple.

Protein–protein interactions are when two or more proteins bind together, often to carry out their biological function. Many of the most important molecular processes in the cell such as DNA replication are carried out by large molecular machines that are built from a large number of protein components organised by their protein-protein interactions. Protein interactions have been studied from the perspectives of biochemistry, quantum chemistry, molecular dynamics, signal transduction and other metabolic or genetic/epigenetic networks. Indeed, protein–protein interactions are at the core of the entire interactomics system of any living cell.

The interactions between proteins are important for the majority of biological functions. For example, signals from the exterior of a cell are mediated to the inside of that cell by protein–protein interactions of the signaling molecules. This process, called signal transduction, plays a fundamental role in many biological processes and in many diseases (e.g. cancers). Proteins might interact for a long time to form part of a protein complex, a protein may be carrying another protein (for example, from cytoplasm to nucleus or vice versa in the case of the nuclear pore importins), or a protein may interact briefly with another protein just to modify it (for example, a protein kinase will add a phosphate to a target protein). This modification of proteins can itself change protein–protein interactions. For example, some proteins with SH2 domains only bind to other proteins when they are phosphorylated on the amino acid tyrosine while bromodomains specifically recognise acetylated lysines. In conclusion, protein–protein interactions are of central importance for virtually every process in a living cell. Information about these interactions improves our understanding of diseases and can provide the basis for new therapeutic approaches.

Methods to investigate protein–protein interactions

Biochemical methods

As protein–protein interactions are so important there are a multitude of methods to detect them. Each of the approaches has its own strengths and weaknesses, especially with regard to the sensitivity and specificity of the method. A high sensitivity means that many of the interactions that occur in reality are detected by the screen. A high specificity indicates that most of the interactions detected by the screen are also occurring in reality.

• Co-immunoprecipitation is considered to be the gold standard assay for protein–protein interactions, especially when it is performed with endogenous (not overexpressed and not tagged) proteins. The protein of interest is isolated with a specific antibody. Interaction partners which stick to this protein are subsequently identified by western blotting. Interactions detected by this approach are considered to be real. However, this method can only verify interactions between suspected interaction partners. Thus, it is not a screening approach. A note of caution also is that immunoprecipitation experiments reveal direct and indirect interactions. Thus, positive results may indicate that two proteins interact directly or may interact via one or more bridging molecules. This could include bridging proteins, nucleic acids (DNA or RNA), or other molecules.
• Bimolecular fluorescence complementation (BiFC) is a new technique in observing the interactions of proteins. Combining with other new techniques, this method can be used to screen protein–protein interactions and their modulators^[1], DERB^[2].
• Affinity electrophoresis as used for estimation of binding constants, as for instance in lectin affinity electrophoresis or characterization of molecules with specific features like glycan content or ligand binding.
• Pull-down assays are a common variation of immunoprecipitation and immunoelectrophoresis and are used identically, although this approach is more amenable to an initial screen for interacting proteins.
• Label transfer can be used for screening or confirmation of protein interactions and can provide information about the interface where the interaction takes place. Label transfer can also detect weak or transient interactions that are difficult to capture using other in vitro detection strategies. In a label transfer reaction, a known protein is tagged with a detectable label. The label is then passed to an interacting protein, which can then be identified by the presence of the label.
• The yeast two-hybrid screen investigates the interaction between artificial fusion proteins inside the nucleus of yeast. This approach can identify binding partners of a protein in an unbiased manner.
• Phage display, used for the high-throughput screening of protein interactions
• In-vivo crosslinking of protein complexes using photo-reactive amino acid analogs was introduced in 2005 by researchers from the Max Planck Institute^[3] In this method, cells are grown with photoreactive diazirine analogs to leucine and methionine, which are incorporated into proteins. Upon exposure to ultraviolet light, the diazirines are activated and bind to interacting proteins that are within a few angstroms of the photo-reactive amino acid analog.
• Tandem affinity purification (TAP) method allows high throughput identification of protein interactions. In contrast to yeast two-hybrid approach the accuracy of the method can be compared to those of small-scale experiments^[4] and the interactions are detected within the correct cellular environment as by co-immunoprecipitation. However, the TAP tag method requires two successive steps of protein purification and consequently it can not readily detect transient protein–protein interactions. Recent genome-wide TAP experiments were performed by Krogan et al. and Gavin et al. providing updated protein interaction data for yeast organism.^[5][6]
• Chemical crosslinking is often used to "fix" protein interactions in place before trying to isolate/identify interacting proteins. Common crosslinkers for this application include the non-cleavable NHS-ester crosslinker, bissulfosuccinimidyl suberate (BS3); a cleavable version of BS3, dithiobis(sulfosuccinimidyl propionate) (DTSSP); and the imidoester crosslinker dimethyl dithiobispropionimidate (DTBP) that is popular for fixing interactions in ChIP assays.
• Chemical crosslinking followed by high mass MALDI mass spectrometry can be used to analyze intact protein interactions in place before trying to isolate/identify interacting proteins. This method detects interactions among non-tagged proteins and is available from CovalX.
• SPINE (Strep-protein interaction experiment)^[7] uses a combination of reversible crosslinking with formaldehyde and an incorporation of an affinity tag to detect interaction partners in vivo.
• Quantitative immunoprecipitation combined with knock-down (QUICK) relies on co-immunoprecipitation, quantitative mass spectrometry (SILAC) and RNA interference (RNAi). This method detects interactions among endogenous non-tagged proteins^[8]. Thus, it has the same high confidence as co-immunoprecipitation. However, this method also depends on the availability of suitable antibodies.

Biophysical and theoretical methods

• Dual polarisation interferometry (DPI) can be used to measure protein–protein interactions. DPI provides real-time, high-resolution measurements of molecular size, density and mass. While tagging is not necessary, one of the protein species must be immobilized on the surface of a waveguide. As well as kinetics and affinity, conformational changes during interaction can also be quantified.
• Static light scattering (SLS) measures changes in the Rayleigh scattering of protein complexes in solution and can non-destructively characterize both weak and strong interactions without tagging or immobilization of the protein. The measurement consists of mixing a series of aliquots of different concentrations or compositions with the anylate, measuring the effect of the changes in light scattering as a result of the interaction, and fitting the correlated light scattering changes with concentration to a model. Weak, non-specific interactions are typically characterized via the second virial coefficient. This type of analysis can determine the equilibrium association constant for associated complexes.^[9]
• Dynamic light scattering (DLS), also known as quasielastic light scattering (QELS), or photon correlation spectroscopy, processes the time-dependent fluctuations in scattered light intensity to yield the hydrodynamic radius of particles in solution. The hydrodynamic radius is the radius of a solid sphere with the same translational diffusion coefficient as that measured for the sample particle. As proteins associate, the average hydrodynamic radius of the solution increases. Application of the Method of Continuous Variation, otherwise known as the Job plot, with the solution hydrodynamic radius as the observable, enables in vitro determination of K_d, complex stoichiometry, complex hydrodynamic radius, and the ΔH° and ΔS° of protein-protein interactions^[10]. This technique does not entail immobilization or labeling. Transient and weak interactions can be characterized. Relative to static light scattering, which is based upon the absolute intensity of scattered light, DLS is insensitive to background light from the walls of containing structures. This insensitivity permits DLS measurements from 1 µL volumes in 1536 well plates, and lowers sample requirements into the femtomolar range. This technique is also suitable for screening of buffer components and/or small molecule inhibitors/effectors.
• Surface plasmon resonance can be used to measure protein–protein interaction.^[11]
• Fluorescence polarization/anisotropy can be used to measure protein-protein or protein-ligand interactions. Typically one binding partner is labeled with a fluorescence probe (although sometimes intrinsic protein fluorescence from tryptophan can be used) and the sample is excited with polarized light. The increase in the polarization of the fluorescence upon binding of the labeled protein to its binding partner can be used to calculate the binding affinity.
• With fluorescence correlation spectroscopy, one protein is labeled with a fluorescent dye and the other is left unlabeled. The two proteins are then mixed and the data outputs the fraction of the labeled protein that is unbound and bound to the other protein, allowing you to get a measure of K_D and binding affinity. You can also take time-course measurements to characterize binding kinetics. FCS also tells you the size of the formed complexes so you can measure the stoichiometry of binding. A more powerful methods is fluorescence cross-correlation spectroscopy (FCCS) that employs double labeling techniques and cross-correlation resulting in vastly improved signal-to-noise ratios over FCS. Furthermore, the two-photon and three-photon excitation practically eliminates photobleaching effects and provide ultra-fast recording of FCCS or FCS data.
• Fluorescence resonance energy transfer (FRET) is a common technique when observing the interactions of only two different proteins^[12].
• Protein activity determination by NMR multi-nuclear relaxation measurements, or 2D-FT NMR spectroscopy in solutions, combined with nonlinear regression analysis of NMR relaxation or 2D-FT spectroscopy data sets. Whereas the concept of water activity is widely known and utilized in the applied biosciences, its complement—the protein activity which quantitates protein–protein interactions—is much less familiar to bioscientists as it is more difficult to determine in dilute solutions of proteins; protein activity is also much harder to determine for concentrated protein solutions when protein aggregation, not merely transient protein association, is often the dominant process^[13].
• Theoretical modeling of protein–protein interactions involves a detailed physical chemistry/thermodynamic understanding of several effects involved, such as intermolecular forces, ion-binding, proton fluctuations and proton exchange. The theory of thermodynamically linked functions is one such example in which ion-binding and protein–protein interactions are treated as linked processes;^[14] this treatment is especially important for proteins that have enzymatic activity which depends on cofactor ions dynamically bound at the enzyme active site, as for example, in the case of oxygen-evolving enzyme system (OES) in photosynthetic biosystems where the oxygen molecule binding is linked to the chloride anion binding as well as the linked state transition of the manganese ions present at the active site in Photosystem II (PSII). Another example of thermodynamically linked functions of ions and protein activity is that of divalent calcium and magnesium cations to myosin in mechanical energy transduction in muscle. Last-but-not least, chloride ion and oxygen binding to hemoglobin (from several mammalian sources, including human) is a very well-known example of such thermodynamically linked functions for which a detailed and precise theory has been already developed.
• Molecular dynamics (MD) computations of protein–protein interactions.
• Protein-protein docking, the prediction of protein–protein interactions based only on the three-dimensional protein structures from X-ray diffraction of protein crystals might not be satisfactory.^[15][16]
• Isothermal Titration Calorimetry (ITC) can be used to measure protein–protein interactions. ITC provides information regarding the stoichiometry, enthalpy, entropy, and binding kinetics between two interacting proteins.

Network visualization of protein–protein interactions

Network visualisation of the human interactome where each point represents a protein and each blue line between them is an interaction.

Visualization of protein–protein interaction networks is a popular application of scientific visualization techniques. Although protein interaction diagrams are common in textbooks, diagrams of whole cell protein interaction networks were not as common since the level of complexity made them difficult to generate. One example of a manually produced molecular interaction map is Kurt Kohn's 1999 map of cell cycle control.^[17] Drawing on Kohn's map, in 2000 Schwikowski, Uetz, and Fields published a paper on protein–protein interactions in yeast, linking together 1,548 interacting proteins determined by two-hybrid testing. They used a force-directed (Sugiyama) graph drawing algorithm to automatically generate an image of their network.^[18][19][20] (see also external links below).

Database collections

The above methods for identifying interacting proteins have defined hundreds of thousands of interactions. These interactions are collected together in specialised biological databases that allow the interactions to be assembled and studied further. The first of these databases was DIP, the database of interacting proteins.^[21] Since that time a large number of further database collections have been created such as:

• BioGRID [1] A General Repository for Interaction Datasets
• STRING [2] STRING is a database of known and predicted protein-protein interactions.
• Database of Interacting Proteins [3] DIP Database of Interacting Proteins
• INTACT is a database system and set of analysis tools for protein interaction data.
• BIND Biomolecular Interaction Network Database
• CORUM is a collection of verified mammalian protein complexes
• PDZbase is a collection of interactions involving PDZ domains
• PSIbase is a collection of predicted interactions inferred from protein structures

See also

References

Further reading

1. Gadella TW Jr., FRET and FLIM techniques, 33. Imprint: Elsevier, ISBN 978-0-08-054958-3. (2008) 560 pages
2. Langel FD, et al., Multiple protein domains mediate interaction between Bcl10 and Malt1, J. Biol. Chem., (2008) 283(47):32419-31
3. Clayton AH. , The polarized AB plot for the frequency-domain analysis and representation of fluorophore rotation and resonance energy homotransfer. J Microscopy. (2008) 232(2):306-12
4. Jameson, D.M. and Ross, J.A. Fluorescence Polarization/Anisotropy in Clinical Diagnostics and Imaging. (2010) Chem. Rev. 110:2685-2708.
5. Clayton AH, et al., Predominance of activated EGFR higher-order oligomers on the cell surface. Growth Factors (2008) 20:1
6. Plowman et al., Electrostatic Interactions Positively Regulate K-Ras Nanocluster Formation and Function. Molecular and Cellular Biology (2008) 4377–4385
7. Belanis L, et al., Galectin-1 Is a Novel Structural Component and a Major Regulator of H-Ras Nanoclusters. Molecular Biology of the Cell (2008) 19:1404–1414
8. Van Manen HJ, Refractive index sensing of green fluorescent proteins in living cells using fluorescence lifetime imaging microscopy. Biophys J. (2008) 94(8):L67-9
9. Van der Krogt GNM, et al., A Comparison of Donor-Acceptor Pairs for Genetically Encoded FRET Sensors: Application to the Epac cAMP Sensor as an Example, PLoS ONE, (2008) 3(4):e1916
10. Dai X, et al., Fluorescence intensity and lifetime imaging of free and micellar-encapsulated doxorubicin in living cells. Nanomedicine. (2008) 4(1):49-56.
11. Rigler R. and Widengren J. (1990). Ultrasensitive detection of single molecules by fluorescence correlation spectroscopy, BioScience (Ed. Klinge & Owman) p. 180.
12. Near Infrared Microspectroscopy, Fluorescence Microspectroscopy, Infrared Chemical Imaging and High Resolution Nuclear Magnetic Resonance Analysis of Soybean Seeds, Somatic Embryos and Single Cells., Baianu, I.C. et al. 2004., In Oil Extraction and Analysis., D. Luthria, Editor pp. 241–273, AOCS Press., Champaign, IL
13. Richard R. Ernst. 1992. Nuclear Magnetic Resonance Fourier Transform (2D-FT) Spectroscopy. Nobel Lecture, on December 9, 1992.
14. Baianu, I.C.; Kumosinski, Thomas (August 1993). "NMR Principles and Applications to Protein Structure, Activity and Hydration.,". Ch.9 in Physical Chemistry of Food Processes: Advanced Techniques and Applications. (New York: Van Nostrand-Reinhold) 2: 338–420. ISBN 0-442-00582-2. 
15. Kurt Wüthrich in 1982-1986 : 2D-FT NMR of solutions
16. Charles P. Slichter.1996. Principles of Magnetic Resonance., Springer: Berlin and New York, Third Edition., 651pp. ISBN 0-387-50157-6.
17. Kurt Wüthrich. Protein structure determination in solution by NMR spectroscopy . J Biol Chem. 1990, December 25;265(36):22059-62.

External links

• Proteins and Enzymes at the Open Directory Project
• Arabidopsis thaliana protein interaction network
• An experimental view of Kurt Kohn's 1999 map gmap Image was merged via gimp 2.2.17 and then uploaded to maplib.net.
• An academic platform to study protein-protein interactions and design drug-like modulators (www.CDithem.com)