Enzymatic Specificity

Introduction

The active sites of every enzyme are composed of a particular array of amino acids, with amino side-chains (R groups). These amino acid side chains form chemical interactions with the substrate of the enzyme. Th

active site exhibits specificity for the substrate of the enzyme. This means that the enzyme should bind and catalyze the reaction for a specific substrate better than with any other substrate. The following experiment will test the ability of lactase to specifically bind and interact with lactose compared to maltose, a similarly shaped disaccharide.

Materials and Methods: Specificity Experiment

1. Label one microfuge tube for “Lactose” and another tube for “Maltose”
2. Using a color-coded plastic pipette, add milk to the 0.5 line (500 µL) of the “Lactose” tube
3. Using a different color-coded pipette, add the maltose solution to the 0.5 line of the “Maltose” tube
4. Using another pipette, add lactase solution to both tubes, until the level of mixture in each tube reaches the 1.0 line

a. Each tube now contains 1.0 mL of mixture: 500 µL of lactase and 500 µL of either milk or maltose

b. Invert each closed tube to mix

1. Place both tubes in the 40° C water bath and incubate for 10 minutes
2. Quickly place a glucose test strip in the tube for 1 second, then remove it and allow it to sit on your bench top for 30 seconds.

a. After 30 seconds, compare the color to the chart provided to determine the amount of glucose in mg/dL
b. The color will change over time, so interpret immediately at 30 seconds

Substrate Lactose Maltose

Glucose
mg/dL 500

Scientific Method

1. What is the substrate in the above experiment? ___lactose___________________
2. What is the enzyme? __________lactase_______________
3. What is the substrate source? _____milk ____________________
4. What is the independent variable in this experiment? _________________________
5. What is the dependent variable in this experiment? _______glucose __________________
6. What are the products in this experiment? _________________________

Conclusion

1. Is lactase specific to lactose? __________________yes_______

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Statistical Analysis

Before making a claim that they have discovered a new cure for a disease, or submitting a paper for publication in a scientific journal, scientists must validate their claims. Statistical analysis uses mathematic

formulas and techniques to analyze the significance of a set of data and therefore the validity of conclusions made based on that data. Using this analysis allows scientists to determine if individual data sets are similar or demonstrate significant differences. Below are some terms that you will need to know in order to interpret the results from the specificity cofactors experiments.

1. Probability: A probability is a numerical indication of likelihood, similar to a percent chance. All probabilities are between 0 and 1, with probability “0” (0% chance) indicating an event that is impossible, and a probability of “1” (100% chance) indicating an event that is certain to occur. Thus, very small probabilities indicate rare or unlikely events, while very large probabilities indicate highly likely events.
2. Null Hypothesis (A=B): A null hypothesis states that there will be no difference between the results of two separate variables, A and B. In regards to the enzyme experiment, the null hypothesis states that lactase will not bind more specifically to maltose or lactose, that it will interact with both equally. All calculations in a hypothesis test are made with the assumption that the null hypothesis is true. If the null hypothesis is true, then we will not witness a great difference between the amounts of product (glucose) produced when the substrate is varied. Some difference is expected due to random factors, so before a null hypothesis can be rejected, there must be a significantly large difference between glucose produced from maltose vs. lactose.
3. Alternate Hypothesis (A≠B): The alternate hypothesis states that there will be a difference between the results of two separate variables, A and B. In regards to the enzyme experiment, the

alternate hypothesis states that lactase will bind more to either maltose or lactose. Before supporting an alternate hypothesis, there must be a significantly large difference between the glucose measurements.

1. t-Test: A t-test is a statistical test used to test the validity of the null hypotheses (A=B) for two different sets of data. We use this to calculate a t-value, which is then used used to calculate a p-value, but the t-value is not in itself useful.

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1. p-value: The p-value is a probability used to determine whether or not the null hypothesis can be

rejected, or if the alternate hypothesis can be supported. Since in a hypothesis test, we always assume that the null hypothesis is true, we expect little difference in glucose production from maltose vs. lactose. We calculate the p-value as the probability of obtaining experimental data with a difference between A and B as large as that witnessed in the experimental data.
a. Large p-values: High probability indicates that the difference observed is small and could be due to random chance. When a p-value is large, we have witnessed only a small difference which is what is most likely to happen when the null hypothesis is true. Thus,

when a p-value is large, we do not have evidence of a statistically significant difference, and we should not reject the null hypothesis.
b. Small p-values: A low p-value indicates that the difference is not likely to be due to random chance, but is instead due to an actual difference between the two data sets. When a p-value is small, we have witnessed a large difference that would be unlikely to occur if the null hypothesis was true. This leaves a lingering question: what is an acceptably small p-

value that could be used to reject the null hypothesis? The scientific community generally settles on a p-value of less than 0.05 (5%) as an acceptable probability with which to reject the null hypothesis.

c. The “probability” or p-value of a statistical hypothesis test tells the percent chance that the difference in results obtained from the experiment were due only to random chance (not a real or significant difference), but the conclusion we draw (that the difference is real and significant) is in error. The lower the p-value, the less likely it is that the results are due to error or chance.

You will use the data obtained in this lab along with data from the other lab sections. An MS Excel spreadsheet will calculate statistical results, and you will use this information to write a formal lab report. We will go over the results in the next lab period.

Sample Solution