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Instructions: Submit your answers as a Word document. Incorporate into the document the requested graphs. Make sure to include a short legend for each graph explaining what is plotted. (Similar to what you would see in a publication.) I strongly suggest using Prism for the plots and analysis. When carrying out a statistical test. Include the details of your analysis. Test chosen, Model chosen, Alpha level chosen, relevant parameter settings chosen (Shared or not shared parameters for example). Include a summary table of the results of the test. Select the relevant information. Do not just dump the data from Prism. Part 1 Linear regression Mary and Joe are interested in UM603, a new ligand for the D2 dopamine receptor. They want to characterize the optical properties of this compound. The drug has significant optical absorbance at 425 nm and they both decide to determine the extinction coefficient of the compound at 425 nm. According to Beer’ s Law, Absorbance = Extinction coefficient x Concentration (M) X Pathlength (cm) They both make standard curves and measure the absorbance (O.D.) of their samples using a standard 1 cm Cuvette in the same spectrophotometer. Mary makes three samples at each concentration and measures the OD of each. She obtains the following data Concentration (micromolar) Absorbance (290 nm) 2.50 0.09 0.10 0.08 5.00 0.18 0.18 0.20 7.50 0.27 0.26 0.28 10.00 0.34 0.36 0.37 12.50 0.46 0.50 0.48 15.00 0.53 0.51 0.47 Joe makes a obtains the following data: single sample at each concentration and measures the absorbance of the sample 3 times. He Concentration (micromolar) Absorbance (290 nm) 10.00 0.38 0.37 0.37 11.00 0.37 0.37 0.38 12.00 0.47 0.47 0.46 13.00 0.44 0.43 0.45 14.00 0.44 0.46 0.41 15.00 0.56 0.62 0.61 For both Mary and Joe’s data: 1) Plot the data (again make sure to include a figure legend) (1 graph each) (10 points) 2) Using linear regression, estimate the molar extinction coefficient of the compound a. specify exactly how you carried out the analysis (What steps did you follow) (5 points) b. Express the results in the following units: Molar-1 cm-1 and provide a measure of the spread for the value you obtained (10 points) 3) Are the values obtained from Mary’s data and Joe’s data different? (5 points) 4) If so, is the difference statistically significant? (10 points) 5) Which data do you trust more? Why? (10 points) Part 2 Non- linear regression Angiotensin II is a peptide hormone that increases blood pressure mainly by causing contraction of the smooth muscle in arterioles (Vasoconstriction). You are interested in developing drugs to treat hypertension that operate by counteracting Angiotensin II mediated vasoconstriction. Your medicinal chemist colleague has synthesized a novel compound UM-603 he thinks is an orthosteric antagonist for the AT1 Angiotensin receptor. To characterize its effects, you use a preparation consisting of ~3mm rings cut from the aorta (a major artery) of the rabbit. These rings can be mounted in an apparatus to measure tension in response to drugs. The tension generated is proportional to the size of the ring, which can be estimated by weighing each ring. You carry out a cumulative dose-response to angiotensin II in the absence and presence of different concentrations of UM603. Tension is measured in micro Newtons (μN) You get the following tension data: Each replicate data set is derived from one ring exposed to increasing concentrations of Angiotensin II. The weight of each ring is also determined. No UM-603 [Angiotensin II] 1 pM 10 pM 100 pM 1 nM 10 nM 100 nM 1 μM Repl. 1 0.8 8.1 59.9 231.3 365.1 381.4 333.6 Repl. 2 0.6 6.9 47.7 252.9 298.8 377.0 422.4 Repl.3 0.7 7.3 75.1 240.0 451.3 419.3 457.5 Ring weight (mg) 13.1 12.5 12.8 1 nM UM-603 [Angiotensin II] 1 pM 10 pM 100 pM 1 nM 10 nM 100 nM 1 μM 10 nM UM-603 [Angiotensin II] 1 pM 10 pM 100 pM 1 nM 10 nM 100 nM 1 μM 100 nM UM-603 [Angiotensin II] 1 pM 10 pM 100 pM 1 nM 10 nM 100 nM 1 μM Repl. 1 0.4 3.1 25.3 170.8 351.4 443.9 403.9 11.5 Repl. 1 0.1 0.7 7.2 60.8 231.3 411.5 388.5 11.5 Repl. 1 0.1 0.3 3.0 21.5 146.8 360.6 440.0 12.2 Repl. 2 Repl.3 0.4 0.4 3.0 3.3 29.1 33.6 156.0 187.6 351.3 484.3 330.2 463.8 329.2 442.2 Ring weight (mg) 10.2 13.2 Repl. 2 Repl.3 0.1 0.1 0.6 0.8 6.8 9.1 51.4 62.3 248.9 305.6 347.7 442.8 321.3 506.9 Ring weight (mg) 10.8 13.1 Repl. 2 Repl.3 0.1 0.1 0.3 0.4 2.2 3.3 24.3 29.0 142.9 161.6 354.5 345.2 338.4 475.2 Ring weight (mg) 10.7 10.2 1) Process the data to allow for comparisons between rings and plot the data. Be sure to include a legend. (5 points) 2) Does the data support the contention that UM-603 is a AT1 receptor orthosteric competitive antagonist? (20 points) Please describe your approach to come to this conclusion. Show your work. (Hint: Use global fitting to extract parameters for this mechanism of action) 3) Propose an alternative mechanism that could explain the data (Still at the AT1 receptor). (5 points) 4) Does the data provide sufficient evidence for you to reject the competitive mechanism in favor of your alternative mechanism? (20 points) Please describe your approach to come to this conclusion. Show your work. Bonus question: Would it be advisable to apply a weighing scheme to the data? If yes, what kind of weighing would you suggest? If you choose to use a weighing scheme, are the confidence intervals improved using your weighing scheme? (5 points).

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