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BCHM 270 Use the Excel file BCHM 270 Graphing Kinetics Data to easily generate your graphs and see the calculated Vmax and Km for your data sets
BCHM 270 Use the Excel file BCHM 270 Graphing Kinetics Data to easily generate your graphs and see the calculated Vmax and Km for your data sets. It works in Office 365 online as well as in excel on your computer. There is a video demonstrating how to use this spreadsheet posted in OnQ.
After completing your analysis of the different bacterial methyltransferases at MethylTranspharmiX, you are off to learn more about inhibition in their Drug Discovery Group. The company is starting a high throughput screen of potential drug targets against ecoDam I, a DNA adenine methyltransferase. This is a bacterially-expressed enzyme that adds a methyl group to adenine in the bacterial genome. Humans do not have this enzyme, so it is an excellent potential target for new antibiotics. Even more exciting, it might also be able to inhibit antibiotic resistant bacteria.(1)
After the first round of screening, you and your supervisors have identified several potential targets. Your group went back to the lab to do more detailed enzyme kinetic inhibition analysis. You are going to need to analyze your enzyme kinetic data to see which of these inhibitors is best. Specifically, you need to see which of them inhibits at the lowest concentration, and determine their inhibition mechanism. After that, you will test them against the mammalian cytosine methyltransferase, Dnmt1, and see if it is significantly inhibited, which would limit its use as a therapeutic target.
The inhibitors are: MTX-A, MTX-B, MTX-C, MTX-D, MTX-E, and MTX-F. You may refer to them by their final letter for simplicity's sake in your discussion.
For your first post, analyze 2 or more of the data sets with the provided excel template. Use the “Calculator from Raw Data” worksheet. The template will take your numbers and generate an X-Y graph of your data. It will allow you to see the Lineweaver-Burke plot, and determine the Vmax, Km, and determine the type of enzyme inhibition.)
Be sure to explain what type of inhibition is observed (competitive, noncompetitive, uncompetitive, mixed), and how well it is inhibiting by stating what inhibitor concentration reduces the velocity below 50 at a substrate [S] of 10 nM. Then, as a group you will work to rank your inhibitors by how well they are inhibiting the ecoDam enzyme from best to worst.
Additional information will be posted by Dr. Pruss to help further your discussions, and you may use this to guide your reply posts and reach a lead drug candidate.
Note: Each of these plots is V (reaction velocity) vs. [S] (substrate concentration) for each inhibitor listed. The concentrations listed in the column headers are the Inhibitor Concentrations (in micromolar). All assays were run with the same amount of Dam I enzyme and substrate values. The I=0/ data is the enzyme alone without inhibitor. Note that the colours may be different than the excel sheet. You should be able to copy the table and paste directly into Excel.
*Be sure your language is set to English and not French, due to number formatting.
Table Note: [S] substrate concentration is in nanomolar nM, V is in % of Vmax of Enzyme alone (I=0) = (100). [I] Inhibitor concentration is in micromolar μM, I = 0 is the enzyme alone without inhibitor present.
MTX-A:
|
[S] |
I = 0 |
I = 0.2 |
I = 1 |
I = 5 |
I = 25 |
I = 125 |
|
0.5 |
9.1 |
9.0 |
8.5 |
6.59 |
3.142 |
0.868 |
|
1 |
16.7 |
16.2 |
14.6 |
9.83 |
3.727 |
0.907 |
|
2 |
28.6 |
27.3 |
23.1 |
13.04 |
4.110 |
0.928 |
|
4 |
44.4 |
41.4 |
32.4 |
15.58 |
4.333 |
0.939 |
|
6 |
54.5 |
50.0 |
37.5 |
16.66 |
4.412 |
0.943 |
|
10 |
66.7 |
60.0 |
42.9 |
17.65 |
4.478 |
0.946 |
|
20 |
80.0 |
70.6 |
48.0 |
18.46 |
4.529 |
0.948 |
|
30 |
85.7 |
75.0 |
50.0 |
18.75 |
4.546 |
0.949 |
|
50 |
90.9 |
78.9 |
51.7 |
18.99 |
4.560 |
0.950 |
|
100 |
95.2 |
82.2 |
53.1 |
19.17 |
4.570 |
0.950 |
|
1000 |
99.5 |
85.3 |
54.4 |
19.33 |
4.580 |
0.951 |
|
10000 |
100.0 |
85.7 |
54.5 |
19.35 |
4.581 |
0.951 |
MTX-B:
|
[S] |
I = 0 |
I = 0.2 |
I = 1 |
I = 5 |
I = 25 |
I = 125 |
|
0.5 |
9.09 |
9.09 |
9.08 |
9.05 |
8.87 |
8.08 |
|
1 |
16.67 |
16.66 |
16.64 |
16.52 |
15.93 |
13.56 |
|
2 |
28.6 |
28.6 |
28.5 |
28.1 |
26.5 |
20.5 |
|
4 |
44.4 |
44.4 |
44.2 |
43.4 |
39.6 |
27.6 |
|
6 |
54.5 |
54.5 |
54.2 |
53.0 |
47.4 |
31.2 |
|
10 |
66.7 |
66.6 |
66.2 |
64.3 |
56.3 |
34.8 |
|
20 |
80.0 |
79.9 |
79.3 |
76.6 |
65.6 |
38.1 |
|
30 |
85.7 |
85.6 |
84.9 |
81.9 |
69.4 |
39.4 |
|
50 |
90.9 |
90.7 |
90.0 |
86.6 |
72.7 |
40.4 |
|
100 |
95.2 |
95.1 |
94.3 |
90.5 |
75.5 |
41.3 |
|
1000 |
99.5 |
99.3 |
98.4 |
94.3 |
78.1 |
42.0 |
|
10000 |
100.0 |
99.8 |
98.9 |
94.7 |
78.4 |
42.1 |
MTX-C:
|
[S] |
I = 0 |
I = 0.2 |
I = 1 |
I = 5 |
I = 25 |
I = 125 |
|
0.5 |
9.1 |
9.1 |
9.1 |
9.0 |
8.7 |
7.6 |
|
1 |
16.7 |
16.6 |
16.6 |
16.4 |
15.5 |
12.1 |
|
2 |
28.6 |
28.5 |
28.4 |
27.9 |
25.3 |
17.4 |
|
4 |
44.4 |
44.4 |
44.1 |
42.8 |
37.1 |
22.3 |
|
6 |
54.5 |
54.4 |
54.0 |
52.0 |
43.9 |
24.6 |
|
10 |
66.7 |
66.5 |
65.9 |
62.9 |
51.4 |
26.8 |
|
20 |
80.0 |
79.7 |
78.9 |
74.7 |
59.0 |
28.7 |
|
30 |
85.7 |
85.4 |
84.4 |
79.6 |
62.0 |
29.4 |
|
50 |
90.9 |
90.6 |
89.4 |
84.1 |
64.7 |
30.0 |
|
100 |
95.2 |
94.9 |
93.6 |
87.8 |
66.8 |
30.5 |
|
1000 |
99.5 |
99.1 |
97.8 |
91.4 |
68.9 |
30.9 |
|
10000 |
100.0 |
99.6 |
98.2 |
91.8 |
69.1 |
30.9 |
MTX-D:
|
[S] |
I = 0 |
I = 0.2 |
I = 1 |
I = 5 |
I = 25 |
I = 125 |
|
0.5 |
9.1 |
9.1 |
9.0 |
8.8 |
7.7 |
4.7 |
|
1 |
16.7 |
16.6 |
16.6 |
16.1 |
14.2 |
9.0 |
|
2 |
28.6 |
28.5 |
28.4 |
27.8 |
24.9 |
16.4 |
|
4 |
44.4 |
44.4 |
44.2 |
43.5 |
39.9 |
28.2 |
|
6 |
54.5 |
54.5 |
54.3 |
53.5 |
49.9 |
37.1 |
|
10 |
66.7 |
66.6 |
66.5 |
65.8 |
62.4 |
49.6 |
|
20 |
80.0 |
80.0 |
79.9 |
79.3 |
76.8 |
66.3 |
|
30 |
85.7 |
85.7 |
85.6 |
85.2 |
83.3 |
74.7 |
|
50 |
90.9 |
90.9 |
90.8 |
90.6 |
89.2 |
83.1 |
|
100 |
95.2 |
95.2 |
95.2 |
95.1 |
94.3 |
90.8 |
|
1000 |
99.5 |
99.5 |
99.5 |
99.5 |
99.4 |
99.0 |
|
10000 |
100.0 |
99.9 |
99.9 |
99.9 |
99.9 |
99.9 |
MTX-E:
|
[S] |
I = 0 |
I = 0.2 |
I = 1 |
I = 5 |
I = 25 |
I = 125 |
|
0.5 |
9.09 |
9.08 |
9.06 |
8.97 |
8.54 |
6.90 |
|
1 |
16.67 |
16.65 |
16.62 |
16.45 |
15.66 |
12.65 |
|
2 |
28.6 |
28.5 |
28.5 |
28.2 |
26.9 |
21.7 |
|
4 |
44.4 |
44.4 |
44.3 |
43.9 |
41.8 |
33.7 |
|
6 |
54.5 |
54.5 |
54.4 |
53.8 |
51.3 |
41.4 |
|
10 |
66.7 |
66.6 |
66.5 |
65.8 |
62.7 |
50.6 |
|
20 |
80.0 |
79.9 |
79.8 |
79.0 |
75.2 |
60.7 |
|
30 |
85.7 |
85.6 |
85.5 |
84.6 |
80.6 |
65.0 |
|
50 |
90.9 |
90.8 |
90.6 |
89.7 |
85.4 |
69.0 |
|
100 |
95.2 |
95.1 |
95.0 |
94.0 |
89.5 |
72.3 |
|
1000 |
99.5 |
99.4 |
99.2 |
98.2 |
93.5 |
75.5 |
|
10000 |
100.0 |
99.9 |
99.7 |
98.7 |
93.9 |
75.8 |
MTX-F:
|
[S] |
I = 0 |
I = 0.2 |
I = 1 |
I = 5 |
I = 25 |
I = 125 |
|
0.5 |
9.1 |
7.1 |
3.8 |
1.2 |
0.26 |
0.053 |
|
1 |
16.7 |
13.3 |
7.4 |
2.3 |
0.52 |
0.106 |
|
2 |
28.6 |
23.5 |
13.8 |
4.5 |
1.03 |
0.212 |
|
4 |
44.4 |
38.1 |
24.2 |
8.6 |
2.04 |
0.423 |
|
6 |
54.5 |
48.0 |
32.4 |
12.4 |
3.02 |
0.633 |
|
10 |
66.7 |
60.6 |
44.4 |
19.0 |
4.94 |
1.050 |
|
20 |
80.0 |
75.5 |
61.5 |
32.0 |
9.41 |
2.078 |
|
30 |
85.7 |
82.2 |
70.6 |
41.4 |
13.48 |
3.085 |
|
50 |
90.9 |
88.5 |
80.0 |
54.1 |
20.62 |
5.038 |
|
100 |
95.2 |
93.9 |
88.9 |
70.2 |
34.19 |
9.592 |
|
1000 |
99.5 |
99.4 |
98.8 |
95.9 |
83.86 |
51.480 |
|
10000 |
100.0 |
99.9 |
99.9 |
99.6 |
98.11 |
91.387 |
1. Mashhoon N, Carroll M, Pruss C, et al. Functional characterization of Escherichia coli DNA adenine methyltransferase, a novel target for antibiotics. J Biol Chem. 2004;279(50):52075-52081.
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