Biochemistry Online: An Approach Based on Chemical Logic

Biochemistry Online

CHAPTER 5 - BINDING

A:  INTRODUCTION TO REVERSIBLE BINDING

BIOCHEMISTRY - DR. JAKUBOWSKI

Last Update:  3/25/16

  • Learning Goals/Objectives for Chapter 5A:  After class and this reading, students will be able to

    • write equations for the dissociation constant (KD), mass balance of total macromolecule (M0), total ligand (L0), and [ML]  as a function of L or Lo ([ML] = [M0][L]/(KD+ [L])  (when Lo >> Mo or when free [L] is known) and Y = fractional saturation =  Y = ([ML]/[M0] = [L]/(KD+ [L])
    • decide which of two given equations for [ML] should be used under conditions when the above conditions for L0 and L are given
    • based on the equation ([ML] = [M0][L]/(KD+ [L]) draw qualitative graphs for different given L0, L, and Kd values
    • determine fraction saturation given relatives values of Kd and L, assuming L0 >> M0
    • compare relative % bound for covalent binding of protons to an acid and noncovalent binding of a ligand to a macromolecule given pka/pH and Kd/L values
    • describe differences in binding curves for binding of a ligand to a macromolecule and the dimerization of a macromolecule
    • derive an equation which shows the relationships between the rate constant for binding (kon), dissociation (koff) and the thermodynamic dissociation (Kd) or equilibrium constant (Keq).
    • describe the structural and mathematic differences between specific and nonspecific binding
    • given a Kd, estimate t1/2 values for the lifetime of the ML complex.
    • describe techniques used to determine ML for given L or L0 values, including those that do and do not require separation of ML from M , so that Kd values for a M and L interaction can be determined
    • List advantages of isothermal titration calorimetry and surface plasmon resonance in determination of binding interaction parameters
     

    A6.  Extreme Binding Affinities

    An incredibly tight binding interaction has recently been reported for the binding of Cu1+ to the CueR protein from E. Coli.  Cu1+ ions are usually kept to a very low concentration in cells as a mechanism to prevent toxicity.  Yet some enzymes require Cu.  Free copper ions must be present in the cell to allow binding to appropriate sites in proteins.  How are these competing concerns regulated in the cell? The total Cu concentration in E. Coli is about 10 μM (10,000 nM), which, given the small size of the bacterium, represents about 10,000 copper ions per cell. 

    Cells have evolved many mechanisms to control and deliver Cu ions.  Copper ions can be delivered to target proteins by copper chaperones (analogs of the chaperone proteins which guide protein folding).  CueR in E. Coli appears to regulate the copper-induced expression of genes involved in copper biochemistry (including an enzyme that oxidizes Cu1+ to Cu2+ which is less toxic).  One particular gene that is up-regulated is copA.  CueR increases transcription of copA in the presence of Cu, Ag, and Au (coinage metal) ions. Changela et al. developed an in vitro assay which determined the extent of expression of CueR regulated genes, under a variety of ion types and concentrations.  In the assay, purified CueR was added to a gene construct containing the promoter (a section of DNA immediately upstream of a gene start site where RNA polymerase binds) for copA.  Initially they found that transcription was always on even in the presence of a ligand, glutathione, which binds Cu1+ avidly and should keep free Cu1+ levels very low.  They switched to an even tighter binding Cu1+ coordinator, cyanide (CN-), to reduce the free Cu1+ levels to even lower levels.  Extremely high levels of CN- (millimolar) stopped transcriptional activation, but if additional Cu1+ was added, activation ensued, suggesting that copper binding to the protein was reversible.  At 1 mM CN-, transcription increased with addition of copper ions up to a TOTAL Cu1+ concentration of 60 μm.  Under these condition, the free Cu1+ concentrations were much less.  Given the presence of CN- concentrations used, half-maximal activation occurred at a TOTAL Cu1+ concentration of  0.7 μM.  Similar activation was observed by Ag1+ and Au1+, but not by Zn and Hg  ions, showing the specificity for monovalent cations over divalent cations. 

    Knowing the pKa of HCN, stability constants for Cu1+:CN- complexes, and CN- concentrations, Changela et al produced a series of solutions buffered in FREE Cu1+ that extended from 10-18 to 10-23 M (pH 8.0).  (For example, the log of the binding constant β, logβ, for the Cu1+ + 2CN- <==> [Cu(CN)2]- is 21.7.  You solved problems such as this involving linked equilibrium if you have taken analytical chemistry.)  The free Cu1+ concentration at half-maximal activation of gene reporter transcription, a measure of the dissociation constant, Kd, was approximately 1 x 10-21 M (zeptomolar)!  Now assume that the volume of the contents of an E. Coli cell is 1.5 x 10-15 L.  If there were only one ion of Cu1+ in the cell, it would have a concentration of 10-9 M.  The values suggest that there is no free Cu1+ ions in the cell, and that only 1 Cu+1 ion in the cell is enough to ensure its binding to CueR and subsequent transcriptional activation of copA.

     Jmol: Updated  Cu(I) Form Of E. Coli Cuer, A Copper Efflux Regulator  Jmol14 (Java) |  JSMol  (HTML5)    

    It is essential for survival that bacterial cells get the right metal to metalloproteins. A recent review by Waldron and Robinson illustrates how.   The cell has many mechanisms of restricting specific binding sites so metals are able to get to the right proteins.  In addition, the natural order of stability for transition metals complexes must be considered in understanding metal affinities.    That stability is given by the Irving – William series which is shown below (along with Group 2A metal ions).  The trend parallels the size of the cation (going from largest to smallest):

      Mn2+ < Fe2+ < Co2+ < Ni2+ < Cu2+ > Zn2+ (tightest binding)

    • The ability for a protein to change shape on ligand binding allows different metals to bind.  For example, cyanobacterium has a high demand for copper and manganese.  Manganese is allowed to bind first and then the protein is folded and manganese becomes trapped inside the protein.  This very unstable metal now cannot be replaced by copper, which would ordinarily out compete Mn2+ for the site.
    • Metal transporters help regulate how many ions of each metal are in the cell.  Metal sensors are under the control of these metal transporters, regulating gene expression.  Once a specific metal has a sufficient concentration for binding, the metal sensors target mRNA to repress certain genes and halt transcription
    • Another enzyme can also be activated for the metal’s export.  By restricting the concentrations of the competing metals, weaker metal-binding sites remain available
    • Metal sensors can also help to regulate what protein some metals use based on what is available.  For example, E. coli switches metabolism to minimize the number of iron-requiring proteins that are expressed when iron is less abundant
    • Metals are supplied by multiple pathways (in case a specific enzyme is not present), and are “trafficked” to the correct protein through many ligand-exchange reactions.
    • Certain enzymes bind specific metals that cause preferential conformational changes.  Hence, if a metal comes along that binds more tightly but is not preferred by the enzyme, it will not trigger the enzyme because it binds in a different manner

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