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For this assignment, you will be working with electrophoretic mobility shift assays
(EMSAs). You will plot binding curves and calculate Kd values for the given data using
the disappearance of unbound radiolabelled probe. Given a tab delimited .txt file, which
contains percent DNA bound and unbound, you will extract the values you need from the
file (column 10, ratio (%)). There are two rows for each lane, the first is DNA bound and
second is DNA unbound. We need the value for the unbound DNA.
Then you will normalize the data to the first lane (divide all values by the value in the
first lane to make this 100% unbound and all others relative to this.) and take the inverse
to get % bound (decimals will be best). Your script will also take the maximum
concentration in nM as well as the dilution factor (e.g. if the max is 625 and the dilution
factor is 4, the concentrations will be 625, 625/4, 625/16, etc). The minimum protein
concentration will always be 0.
Next, you will use the curve_fit module from scipy to plot this data along with a
Sigmoidal curve fit using the following equation.
Y=Bmax*X^h/(Kd^h + X^h)
Where Bmax is the maximum DNA bound (by definition should be ~1), h is the hill
coefficient, and Kd is the concentration where 50% of the DNA is bound.
Finally, you will plot the data and fit, adjusting the titles and axes to match the example.
Be sure to print the Kd and hill coefficient in the legend. Note: the x axis is in log scale
(pylab.xscale(‘log’))
The title of the graph will be taken from the protein used (always IntLong) and the oligo
used (from the title of the .txt file. Hint: regular expressions work well here).
lunt:Desktop brycelunt$ ./assign13.py 10.30.15attB39.txt 625 4
lunt:Desktop brycelunt$ ./assign13.py 11.4.15attBR6SDM15.txt 625 4
lunt:Desktop brycelunt$ ./assign13.py 11.30.15attB345.txt 625 4