Protein-Protein Interactions Lecture Notes

Why Measure Protein Interactions?

  • Proteins are the primary executors of biological processes in living systems.
  • Protein interactions are essential for various biological functions.
  • Understanding protein interactions is crucial for understanding biological processes and drug discovery.

Types of Protein Interactions:

  • Protein-Nucleic Acid Interactions:

    • Fundamental for processes like DNA replication, transcription, and translation.

  • Protein-Protein Interactions:

    • Form the basis of cellular signaling pathways (e.g., the JAK-STAT pathway).
    • Involved in apoptosis (programmed cell death) and the cell cycle.

  • Protein-Lipid Interactions:

    • Critical for modulating membrane processes, cell and organelle biogenesis, innate immunity, and defense.

  • Protein-Carbohydrate Interactions:

    • Essential for cell-cell interactions, innate defense, growth factor signaling, and other crucial processes.

Examples of Protein Interactions:

  • Ribosome:

    • A large protein-nucleic acid complex (2 megaDalton).
    • Important for translation of nucleic acids.

  • Nitrogen G2 Domain & Pearlyan IG16 Domain:

    • Protein-protein complex.
    • Core interaction for basement membrane stability, crucial for tissue architecture maintenance.

  • NAD1 & PIP2:

    • Protein-lipid interaction.
    • NAD1 (an inner defense molecule) binds to PIP2 (a phospholipid) in fungal membranes.
    • Triggers formation of oligomer complexes that disrupt fungal membranes, providing innate immune defense for plants.

  • Isolectin 4 & Lewis B Antigen:

    • Carbohydrate-protein interaction.
    • Isolectin 4 binds to the Lewis B antigen, defining blood type.
    • Forms a tight network of hydrogen bonds for specific recognition.

Qualitative Measurements of Protein Interactions

  • Qualitative measurements include Yeast Two-Hybrid Systems and Pull-Down Assays.

Yeast Two-Hybrid System

  • A rapid way to screen for unknown protein-protein interactions in an unbiased manner.
  • Provides a yes/no answer regarding interaction but doesn't quantify interaction strength.
  • Allows screening of a substantial number of interactions simultaneously using libraries.
  • Can identify unknown interactors, assess their significance, and later determine affinity.
  • How it Works:
    • One molecule is bound to a DNA-binding domain, which binds upstream of the promoter region of a reporter gene.
    • If an interaction occurs between the bait protein and a potential interactor (prey), the activating domain is brought into proximity with the promoter.
    • This recruits RNA polymerase II, transcribing the reporter gene and indicating a positive interaction.
  • Developed in 1989 by Fields and Song.
  • Various modifications exist to improve its effectiveness for specific problems, such as split ubiquitin systems, membrane recruitment strategies, and split protein systems.

Pull-Down Assays

  • Requires a heterologous expression system:
    • E. coli bacterial expression system
    • Yeast-based systems (Saccharomyces cerevisiae, Pichia pastoris)
    • Insect cells (Baculovirus-dependent systems using SF9 or HI5 cells)
    • Mammalian cell lines (HEK 293 cells, COS cells)
  • Requires at least one affinity tag attached to the protein to be studied:
    • Glutathione S-transferase (GST) binds to reduced glutathione.
    • Polyhistidine tag (6-10 histidines) binds to nickel or cobalt chelate complexes.
    • Biotin-streptavidin interaction.
  • How it Works:
    • Immobilize a fusion tag bait protein from the lysate using agarose beads covalently attached with an affinity ligand.
    • The bait protein binds via the appropriate affinity tag.
    • Wash away unbound proteins.
    • Introduce a solution containing prey proteins.
    • Interaction between bait and prey traps the prey protein on the beads.
    • Wash again and elute the bait protein, resolving on an SDS-PAGE gel.
    • A successful entrapment shows two bands (bait and prey), while just the bait protein will lead to seeing only one band.
  • Requires specific expression vectors, media, incubators, and sometimes specific tweaks.

Quantitative Measurements of Protein Interactions

  • ITC (Isothermal Titration Calorimetry), SPR (Surface Plasmon Resonance), MST (Microscale Thermophoresis), and FP (Fluorescence Polarization) are popular quantitative methods.
  • Determine binding affinities.
  • May provide additional data such as on/off rates, entropy, or protein quality.
  • Methods are highly complementary and offer cross-validation.

Dissociation Constant (KDK_D)

  • The dissociation constant (KDK_D) has a molar unit and it is the concentration of the ligand L at which the binding site on a particular protein is half occupied.
  • The smaller the KDK_D, the tighter the ligand is bound and the higher the affinity between the ligand and the protein.

Isothermal Titration Calorimetry (ITC)

  • The principle is simple: any biomolecular interaction results in a change in heat.

    • Exothermic: heat released, reaction vessel gets warmer.
    • Endothermic: heat absorbed, reaction vessel gets cooler.

  • ITC directly measures the heat generated or absorbed when molecules interact, giving a direct readout of the interaction.

  • Sample data yields a sigmoidal curve plotting energy released/absorbed over the interaction.

  • Setup:

    • Reference cell: contains sample protein.
    • Inject interactor of choice.
    • Compare temperature in the reference cell with the sample cell.
    • Plot the microcalories per second required to equilibrate the sample cell to the reference cell temperature.

  • Measures: Protein-small molecule, enzyme inhibitors, protein-protein, protein-DNA/lipid/carbohydrate interactions.

  • Affinity Range: Usually 1 nanomolar to 1 millimolar.

  • Advantages:

    • High experimental biological relevance (in-solution method).
    • Label-free.
    • No molecular weight limitations.
    • Optical clarity is unimportant.
    • Minimal assay development.

  • Disadvantages:

    • Cannot measure affinities below 1 nanomolar easily.
    • Protein-hungry (0.05 mg protein for single interaction).
    • Highly sensitive to buffer differences between protein and interactor.

  • How to Run an ITC Experiment:

    • Measure the temperature difference between the sample and reference cell (DP).
    • This DP is the measured power differential between the cells, necessary to maintain a temperature difference close to 0.
    • ITC instruments provides ΔT and allows calculation of entalphy and entropy.
    • Put ligand/interactor in a syringe and macromolecule in the sample cell.
    • Titrate the interactor into the sample cell in discrete steps while measuring heat of interaction.

  • Parameters Derived:

    • Affinity or KDK_D. The dissociation constant
    • Enthalpy (ΔH).
    • Number of binding sites (n).
    • The height under the curve indicates the maximal microcalories per second required to equilibrate the reference and the sample cell. This value decreases as the reaction continues, eventually plateauing.

  • Association constant (K<em>BK<em>B): inverse of the K</em>DK</em>D.

  • Different instruments have varying sample requirements and throughput.

  • Older instruments (e.g., Microcal VP) required a large sample volume (1.4 mL) and had low throughput (5 samples/day).

  • Modern instruments (e.g., Microcal ITC200) are more sensitive, faster, and require less sample volume (200 μL) with a high throughput with Automated versions .

  • From K<em>BK<em>B one can obtain the Gibbs free energy (ΔG\Delta G) which relates the enthalpy (ΔH\Delta H) and entropy (ΔS\Delta S). i.e. ΔG=−RTln⁡K</em>B=ΔH−TΔS\Delta G = -RT \ln K</em>B = \Delta H - T \Delta S
    Where

  • R is the ideal gas constant

  • T absolute temperature in Kelvin.

  • The stogeometry tells the ratio of ligand to macromolecule binding.

  • ΔG changes below zero are spontaneous, the more negative The delta G the higher usually the affinity.

  • Entropy (ΔS) is usually positive for entropically driven reactions, which often rely on hydrophobic interactions. Solvation entropy, due to the release of water, is a highly positive entropy factor that can dominate interactions.

  • Negative entropy changes relate to loss of translational and internal degrees of freedom.
    Enthalpy is a measure of the energy content of the bonds broken and created.
    Solvents Play Key Role as These Interactions Don't Occur in a Vacuum. They all Occur in Solution Which Is As It Should Be for Biological System

ITC can measure the Gipps Free Energy, Enthalpy and Entropy via Bar Graphs.

  • Enthalpy versus entropy:

    • Good hydrogen bonding with unfavorable conformational changes results in poor entropy but high entalphy (ΔH).
    • Binding dominated by hydrophobic interactions is reflected in larger minus delta

  • Key points to bear in mind about entalphy and entropy:

    • When you think of Enthalpy think of strengths of hydrogen bond formation, Electrostatic and ionic bond formation and favorable hydrophobic interactions
    • Entropy is Really Driven by salvation, entropy changes, unfavorable hydrophobic interactions, the partitioning of the solute (Water) and The Loss of translation and internal Degrees of Freedom and Change in side chain or peptide back Mobility.

  • Sample quality can be estimated using the stoichiometry (n) value. Deviations from expected n values indicate inactive protein in the sample.

  • e.g. A well studied interaction can estimate the sample quality using the calculated n value. (for the interaction shown here in blue. We know that n equals 1. However, when we measure another batch of protein, we get an N of only 0.235 (aprox 0.24). THis really tells us that about 76% of batch B consists of inactive protein and THEREFORE we may not want to use THIS batch of protein for screenin purposes OR for determining structures because it might JUST be very FUTILE.

  • ITC is very good at determining binding sites
    *At the halfway point for molecular interactions we can see that we are dealing with an n that equals 2 with two different binding sites one higher affinity versus one lower affinity one.
    *ITC is one of the few that gives very accurate numbers for the number of binding sites, which makes it very very useful