BabcockHall

With respect to Q7, both RUBISCO and hexokinase can be eliminated from consideration because there is no net oxidation or reduction of carbon atoms and no photochemistry.  They are clearly not part of photosynthesis.  RUBISCO is obviously a key player in the Calvin-Benson cycle.

"Reactions catalysed by enzymes follow saturation kinetics."  The way I read this, it means that the Michaelis-Menten/Briggs-Haldane equation is followed.  This is often true, but it is clearly false for many regulated enzymes (phosphofructokinase-1, for example), which follow sigmoidal kinetics.  With respect to 4 if K_M becomes smaller, then V/K becomes larger (keeping V_max constant).  V/K is the apparent second order rate constant for the rate when S << K_M.  It is also proportional to k_cat/K_M, one measure of catalytic efficiency.  I agree with the answer in the key.

What do you mean buy shorter reaction?

You might give some thought to volatility.

One of the reasons I am asking is because R² is a little bit like electronegativity in chemistry; one teaches students about it, and they want to use it for everything, even when there are better tools.  In this instance R² is not ideal, because it is indifferent to the direction of the residual, only to its magnitude.

I thank you both for some helpful comments.  In our case we were plotting a straight line for gel electrophoresis data on proteins.  The standard curve, which is mobility versus logarithm of molecular weight for the standards, had noticeable curvature.  I am still looking into the biophysics, but the information that I have presently is that a slight deviation at high molecular weights is expected.  I am not looking to explain the results, so much as to describe it, in the sense of making a more formal statement to the effect that a linear fit leads to non-random residuals.

It has been suggested to me that Pearson's R is a good statistic for this situation.  Thoughts?

https://en.wikipedia.org/wiki/Anscombe's_quartet

I would like to know whether or not there is a statistic that can differentiate between the case at the top left versus the top right.  Clearly R² does not do so.  One could plot the residuals, and the non-random distribution sometimes becomes apparent.  However, what I was hoping to find is some number, preferably one that would be calculated by a statistics program, that could be compared in the two situations.  I am reading Motulsky's book Intuitive Biostatistics (that is where I first saw the Anscombe quartet, but I have not found anything in his book yet.  I am presently using ProStat, which has both a calculation of COD (which I am pretty sure is R²), as well as a calculation of "Corrl" which is said by the user manual to indicate "how closely the two variables approximate a linear relationship to each other."  I note the presence of squared differences in the numerator of COD, which are not found in Corrl.

The APS was fresh, but the first bis that I used was old.  There is also a chance that I made a gross error in weighing it out.

Ordinarily the polyacrylamide gels are rubbery, but the ones I poured last week were very stick, and the stacking gel did not seem to solidify.  I was able to run a pre-stained standard, and it looked almost normal.  However, the gel stuck strongly to the glass plates and was unusable.  I made new acrylamide using a different manufacturer's bis-acrylamide, and the new gel behaved normally.  Either it was the bis, or I made some other mistake in making the acrylamide solution.  Has anyone ever seen something similar?  Any guesses about what could cause a gel to become sticky and less of a solid?

This is a very broad series of questions, and at least for question 2, I see several possibly answers.  For example coezyme A is converted into acetyl CoA during beta-oxidation of fatty acids but also as you imply by the enzyme acetyl CoA synthetase.  My advice is to start with a good biochemistry textbook, and you may be able to fine-tune your questions.

There is a little bit of information on page 92 of Biochemica Information, by Joseph Keesey.  He notes that it can catalyze transpeptidations and that the pH optimum  is between 2-4.  Offhand, I do not know of a good source, but the BRENDA compendium of information might be worth checking out.

It is my understanding that some people use a mixed quantum/classical approach when studying ligands interacting with macromolecules in silico.  This is not an area of expertise of mine; therefore, it is possible that I am mistaken.

Ninfa, Ballou, and Benore's textbook on the biochemistry and biotechnology laboratory has a good introduction to this topic.

What are your thoughts, so far?

What do you know about pepsin, and what do you hope to learn?

Why don't you start by posting your attempt?  Then we can help you.  Hint:  curved arrow notation describes the flow of electrons, not nuclei. 

Your estimates do not look bad, but it might be possible to improve them.  Ideally one would use nonlinear regression.

Provided certain assumptions are correct, pK_a values in the V_max graph pertain to the E•S complex, whereas pK_a values in the V/K graph pertain to free E or to free S.  CRC Critical Reviews in Biochemistry (Knowles JR 1976, p. 165) has a good intermediate-level discussion of this topic.  In your case the graph of V/K vs. pH has an unusual shape, which I find a bit puzzling.   It may be that the data do not span as a large range of velocities as one might like.

Hi Jonas,

Can you show us your work so far?  What equations are you using?

Have you thought about looking at V_max/K_M?  It turns out that each parameter that you examine tells a slightly different story.  

It has been a long time since I looked into this; however, I am under the impression that the hydroxyproline residues, the hydroxyl groups on the side-chains form hydrogen bonds to water.  For whatever reason the presence of hydroxyproline residues increases the thermal stability of collagen.

To a rough approximation, when one has 1 mg/mL of protein, the absorbance at 280 nm will be 1 AU.  Obviously this depends on the protein.

I am changing my mind on one thing; it may be that the value of 1.7 mg/mL refers to the final concentration of protein, meaning the concentration after dilution.  If so, then the initial concentration must be very high, possibly at or beyond the solubility limit of a particular protein.  If this is a homework exercise, then whether or not the problem is realistic from the point of view of biochemistry is secondary  to getting the mechanics of the problem correct IMO.

The volume of extract (2 mL) does not enter into the dilution calculation itself, but it is needed for another portion of the calculation.  You need to identify the initial concentration, the initial volume, and the final volume of the dilution, in order to find the final concentration, the concentration of the diluted sample.  One thing that is a little unclear from your initial post is the interpretation of 1.7 mg/mL.  I think that it refers to the initial concentration, but I could be wrong.

This is a standard dilution problem.  You  have to show your attempt at solving the problem first.