Assessment due this thursday

End of course summary

Type: Report
Learning Objectives Assessed: 1, 2, 3, 4, 5
Due Date:
5 Nov 09
Weight: 20%
Task Description: Each students will present a 10-20 page written summary of what they learnt in the course.
This will be broken down into 5-10 key ideas and will include a relevant figure for each
Criteria & Marking: Summary will be marked based on clarity and accuracy.

Course profile

I had problem accessing the course profile on the UQ website and so have uploaded it here.

Tuesday Meeting?

Hi all,

Ross says that 20th November should be possible for the exam - he says he can start us off at 10 (and have the exam run 10am - 12pm). Is this still ok for everyone?

Also - do we still want to have a session on Tuesday? If so, maybe we should do any of the marking and peer evaluation things that we still have left to do and bring them on Tuesday so we can get all the rest of the assessment except for the exam all finished up and finalised.

Kristen

Late post for presenting topic...

Hi guys, sorry I am posting this so late... I forgot last night :S Am really really tired, so we'll see how the presentation goes. Nevertheless, the topic is a cool G-protein, which has been biophysically analysed. Its awesome. The paper is "Biophysical Analysis of the Interaction of Rab6a GTPase with Its Effector Domains."

Also, sorry I haven't found a paper for discussion time this week yet... so, to be continued I guess.

Alex.

The rules of disorder or why disorder rules

Hi everyone,

Apologies for not posting this sooner. The paper I have chosen for this week is called "The rules of disorder or why disorder rules". It focuses on a group of proteins found in eukaryotic cells that don't have a unique three-dimensional structure, but are still functional. These proteins adopt different folds when they interact with different partners - so in essence, their function defines the structure of the protein.

I'd never heard of these kind of proteins before, so was interested to learn something more. The paper itself doesn't focus on just one protein, but gives a few different examples.

See you all at the session!

(Also - at Tomas, who I'm assuming has done up the poll that has appeared - I can't possibly answer a question that asks two questions in one with only one poll option! Have two polls for two questions :P )

Structure, Property and Function, Relationships

Hey all,

I got some exciting news on the weekend. I have been offered a rural scholar ship at Griffith gold coast ^_^ which was my first preference. I'm quite pleased but not have 101 little practical details to work out.

For this weeks discussion topic I wasn't particularly clear on what direction we were taking the "structure, property, function relationships" topic (although our discussions often seem to choose their own direction on the day anyway :P). I cant remember if we were thinking proteins in particular or anything that fits under that heading such as cell shape and structure and their specific function.

Either way the paper I have chosen for for this week is on a protein which is a transcription inhibitor in barley but its general structure is found in many plants. Its expression in barley results in inhibition of growth of two side seed spikes which apparently makes self seeding of the plant more successfull. If this gene is removed however crop yield is tripled but the head are fatter and well likely to successfully self seed. This high yield barley is not a new thing and has been found to be used around the world in different cultures, most of which discovered it by selective breeding.

Diamagnetic levitation of biological organisms

Either nobody knows, cares or had the time to answer the question posed in the previous post, so I'll do it here:

More diamagnetic levitation movies...

The 'disproof' of magnetic levitation only applies for static charges. This video gives a quick demo of how you can test this yourself (I've never heard the audio track, so don't know if it's any good).

If you have a big enough magnetic field for its ρ/χ, you can levitate pretty much any living thing. Armed with this knowledge, biophysicists can conduct useful research like this and this.

On the Nature of the Molecular Forces which Regulate the Constitution of the Luminiferous Ether

What is photophysics without light, and how would light propagate without the luminiferous ether? Yes indeed, I finally was able to find a copy of this most excellent publication.

Ten points awarded if you can link the below to something we were discussing last week; twenty if you find a video of it and link it here.

Assessment

Does anybody know when exactly all of our outstanding/in progress assessment is due? Or what it is exactly? The online course profile doesn't seem to match with the notes I've taken down. Here's what me may (or may not) have left, not counting the exam and attendance next week:

• Report : According to the course profile, due on the 5th of November 2009
  
• Weblog : When do posts cease to 'count'? Next Tuesday, SwotVac, when the report is due or when the exam is held (for revision posts)? Anything after that is probably just for old time's sake..
  
• Peer evaluation : Will we be doing this next week during our usual meeting?
  

To me, it seems like some of the fine chronological detail have been lost in the background noise towards back end of semester (though this could be bias from looking at the video on this site while trying to get slides today), or my note-taking during the first couple of weeks wasn't so good. Can anybody confirm any deadlines for me please?

Edit: cut mention of canned assessment item

Photophysics and coral reefs

This is the paper that I brought in today:
Wild, FJ; Jones, AC; Tudhope, AW:Investigation of luminescent banding in solid coral: the contribution of phosphorescence (2000).Coral Reefs 19:2, pp132—140.

I tried to find a good picture to answer Kristen's question about what the bands actually are (sorry for not getting around to it before we all left!), and I came across this excellent page from the Australian Antarctic Division's website. Look at the third picture on the page!

Ack: Try searching for trees rings photophysics, and see if it's as cool as coral..

The "Brainbow Mouse" - Don't cut the green fluorescent wire!

I can't resist tying this week to last. Follow the link and find out what the "Brainbow Mouse" is: http://www.nature.com/nature/journal/v450/n7166/full/nature06293.html

Ever see those old action TV shows where the hero has to diffuse a bomb? He calls his friend and his friend says something like "whatever you do, don't cut the green wire!". Well, what if the wires were all the same color? Poor hero!

This is exactly the problem that neuroscientists have had for years - how to figure out what connects to what when everything looks the same. This problem was addressed in the article by combinatorially expressing fluorescent proteins in mouse neural tissue. There are just a few FPs used, but each cell expresses the set in different proportion, allowing (I think) more than a hundred visually identifiable colors! Check out some of the pictures - they're more colorful than a hippie van...

"Killer Red" - The Fluorescent Protein that BURNS

This was going to be a comment on Alex's post about photosensitizers, but I thought I'd elevate it to a full post because its interesting...

Like photodynamic therapy AND fluorescent proteins, and want to put them together? Well, now you can!

Killer Red is a variant of a red FP from coral (maybe sea anenome?). It has been optimized specifically to spew out reactive oxygen species upon irradiation. Any organism which expresses this protein is born to BURN, BABY BURN!

Here's the link: http://www.nature.com/nbt/journal/v24/n1/abs/nbt1175.html Check it out!

PE surfaces & photophysics

Just a quick video I found. I wish I knew how to download it to bring it to class to discuss.
It's a graphic representation of radiationless decay. It shows a molecule switching seemingly effortlessly from an excited state to the ground state at the conical intersection of the two relevant potential energy surfaces for that molecule.
hopefully the link works! If not, here's the url: http://wavepacket.sourceforge.net/Demos/ConicalInter/Linear/2/surface.mpg

Photodynamic Therapy - Light for Treatment of Disease

I am personally fond of the fluorescent proteins and their applications to biological investigation, including FRET, however I decided that other papers for tomorrow had this area pretty well covered. So I embarked on a search for further photophysical applications in biology with relevance. I found many interesting papers, however many I felt were too specific in their study of obscure molecules to perhaps be relevant for a broad discussion, or results felt incomplete as investigation continues in the field.

Finally, I found what I consider to be a well rounded review of a topic with very important medical applications, Photodynamic Therapy (PDT). You may be familiar with the concept however it is new to me, and this paper ("Photophysics and photochemistry of photodynamic therapy: fundamental aspects") presents a clear photophysical description of the process.

If you are not familiar with PDT, it is used as a treatment for cancer and other diseases by specifically targeting and destroying unwanted/harmful cells. A light sensitive drug is administered that, upon absorption of light at the appropriate wavelength, essentially oxidises intracellular molecules, thereby destroying the targeted cells. An optical window for PDT in tissue is defined by the absorption spectra of the most important chromophores: water, hemoglobin, melanin, and cytochromes.

I look forward to a discussion of photophysics tomorrow. On another note however, I will be unable to attend for the second half of our meeting so perhaps the presentations (Ack and Tomas) could be in the first half? As a result I may have limited input in the following discussion. Regardless, see you all tomorrow. Cheers, Alex.

FRET efficiency between a mutant of whttp://www.blogger.com/img/blank.gtGFP (donor) & a newish red fluorescing derivative of DsRed, mCherry (acceptor)

hello.
My photophysics reading for this week has been "Quantitative FRET Analysis With the E⁰GFP-mCherry Fluorescent Protein Pair", published in August '08 in Photochemistry and Photobiology 85(1). I had trouble accessing the pdf via the library site, but the html option worked just fine.

In this article, some scientists from various institutions within the Scuola Normale Superiore in Pisa propose a new fluorescent protein pair (E0GFP-mCherry) which they argue is particularly useful for FRET experiments in living cells.

The link here to Kristen's paper should be obvious and, in case you're interested, I got a bit carried away trying to find a link to Michael's. I might have come up with a link that actually has some conceptual substance by Tuesday, but in the meantime here's my best effort: mCherry is a monomeric derivative of DsRed, a red fluorescing protein derived from stony coral. Michael's paper features HcRed, which is also red fluorescing and also derived from an anthozoa, but is dimeric & found in nature in an anemone, not a coral.

back on track... my article describes the quantitative determination of FRET efficiency for this pair using fluorescence lifetime imaging spectroscopy (FLIM) & acceptor photobleaching (APB). I found the format a bit "biology-esque" (with descriptions of method focussing on technique used for, say, cloning proteins) but these were all new ideas to me so it was interesting and I coped! I recommend skipping to the treatment of FLIM & APB in the Results section which was somehow more conceptual.

The authors also talk about "the recent phasor approach" to FLIM, which I had to go here to understand.

Rar-red Fluorescent Protein

Hey all, the paper I chose for this week is about the Far-red Fluorescent protein.

I came across it when looking for a paper on structural analysis of a protein (for a biochem subject) with the condition that it was co-authored by someone at UQ. Initially I looked at the first name from UQ which was Sean C. Smith and thought no idea who that is but who cares it fits the criteria. It wasn't untill today that I thought hey maybe that paper would have something interesting to talk about for biophys and had a second look at it. To my surprise the paper actually had two people listed as from UQ the second of which was "SETH OLSEN"! I'm not sure how I managed to miss that the first time.

The paper talks about both chromophores (organic molecules which can provide some of those vivid colours we see in plants and animals) and fluorescent proteins, both of which have a very similar structure with only a small conformational change providing their functional diversity.

The paper is:

The 2.1 A° Crystal Structure of the Far-red Fluorescent Protein HcRed: Inherent Conformational Flexibility of the Chromophore, J. Mol. Biol. (2005) 349, pg. 223–237.

Here is the abstract and I accessed the paper through the UQ library site.

Photophysics and GFP

Hi all,

A reminder that this week we're reading about photophysics. If everyone was able to post their reading on the blog as soon as possible that would be much appreciated - that way when we get to the tutorial we can discuss things that we found interesting about other people's papers, or things that we didn't understand.

This week I've chosen a paper about GFP (green fluorescent protein), for which the Nobel Prize in Chemistry was awarded last year for its discovery and development. The paper is titled 'Excited state reactions in fluorescent proteins' from Chem Soc. Rev., 2009, vol 38 p 2922- 2934 (If you're not at uni, you will be able to find the paper through the library or Web of Science).Whilst the paper at first glance appears to be a bit long, I think that the most interesting sections to us are the Introduction (which gives a good background) and section 3 - Photophysics and proton transfer in wtGFP. It turns out that the wild type version of GFP described in section 3 fluoresces much better than the chromophore of GFP on its own (described in section 2). Section 4 describes how things change when GFP is mutated, and section 5 is on 'second generation fluorescent proteins'. If you're running seriously short of time, I would at least recommend reading sections 1 (Introduction) and 3.

For those who aren't familiar with the terminology, 'quantum yield' essentially refers to the ratio of photons in to photons out. This is either expressed in percentages, or a decimal. A high quantum yield means that your molecule is very fluorescent and a high amount of light that goes in is converted into fluorescence. A low quantum yield means that most of the light that goes in decays non-radiatively, and most of the light energy is not re-emitted.

For those that are stuck as for where to look, some good examples of photophysics are molecules that use FRET, or the use of FRET to get information about your molecules of interest, biological molecules that fluoresce or absorb light, articles about the use of GFP (the one I have posted is mostly about energy transfer in the molecule itself) or in photosynthesis (I only discussed purple bacteria in my talk). Once you start looking, you should find lots of examples.

using neural networks to model recognition of handwriting

So after my usual bouts of indecision, here's my paper for tomorrow:
http://www.cs.utoronto.ca/~hinton/absps/ijcai05.pdf
Sorry to post it so late.

Apparently using neural networks to model handwriting recognition is not a very new thing, but:
1) it's new to me! i think this paper could make a nice link in our discussion between free energy minimisation and Michael's words on Bayesian theory.
2) this particular approach uses multiple neural networks to model the recognition of finer and finer details in handwriting. from what i understand, THIS is a bit new. also, there is a great Flash demo online. I just have to find it again and i'll post it up!

Chaotic Neural Networks = Thoughts and Actions

Hi all,

This week I found a paper that comes back to the idea of biological disorder leading to order. This is found in the sense that a novel system of mathematical/computational learning produces a systematic and coherent response from an initially chaotic state. The system is modeled with variables that represent neurons and synapses.

The title of the paper is "Generating Coherent Patterns of Activity from Chaotic Neural Networks"and I have posted a link to the paper (using Ross's method) here. The procedure is called FORCE learning and as expected there are a couple of large math equations, however I find the concept in general rather interesting and thought provoking.

See you all tomorrow.

Alex.

The Baffling Bayesian Brain

Hey I'm not sure if you guys covered this topic when you did mathematical biology, but Idid a section on how the brain is thought function according to Bayesian theory. If you havn't heard of Bayesian theory before don't stress its pretty easy and I'll do my best to summarise it tomorrow.

My neural networks reading for this week (which is a little bit of a tangent but I find it really cool so that justifies it in my mind :P) is an experimental paper I first saw in mathematical biology, which suggests that the brain may function on basic Bayesian theory.

The paper is: Bayesian integration in sensorimotor learning - Nature 427, 244-247 doi:10.1038/nature02169;

See you all tomorrow.

P.S I think my med interview went really well but its hard to know for sure.

This week's reading

Hi all,

Just a reminder to everyone that we're supposed to be posting our reading for the week on the blog so everyone else can have a look at it and so we have something to discuss at our meeting tomorrow. If someone else could post something before late tonight so that I have a chance to look at it before tomorrow that would be great.

Kristen

Micheal's Presentation

Hey all sorry this is a bit late. My presentation is planned for this Tuesday and the paper I'm reviewing is "Folding at the Speed Limit", a letter to nature from: Nature 423, 193-197 (8 May 2003) | doi:10.1038/nature01609. It's about the speeds at which proteins fold with time scales dependent on the size of the proteins in question.

This all said I am rather stressed at the moment as am trying to complete a computational physics assignment before tonight as well as preparing myself for my medical entry interview tomorrow and somewhere in the gaps preparing my presentation. I sadly I forgot I had all these things on when I agreed to do my presentation this week. Ross and Seth I was wondering if I needed to could I postpone my presentation to the last week where there is currently still a slot open? At the moment I would still like to do it this week and could probably do the finishing touches after my interview but I'm not really sure what sort of working state I will be in Monday night.

I will check the comments on this post for you responses and if need be I can make my presentation happen this week, I'm just worried I may not be able to put my best effort into it.

Kristen's Presentation

Hi all,

My presentation this Tuesday will be on "How Nature Harvests Sunlight", looking in particular at the light-harvesting apparatus of purple bacteria. The main article I have focused on is Hu, X. and Schulten, K (1997) 'How Nature Harvests Sunlight', Physics Today, August 1997, p28 - 34. The UQ library has access, so this can be found by doing a quick search of Web of Science (or similar), or I have posted a link here.

I don't want to get too focused on the tiny details, especially since I know that there are those of you who aren't altogether comfortable with lots of quantum mechanics, so I'll be sticking mostly to concepts (in other words, don't get freaked out).

Kristen

Neural Networks Introduction

I had a flick through the Biophysics textbook by Cotterill, which had a section on neural networks. Since we probably don't all have access to that particular book, I've done a summary of it and uploaded my summary here. It's pretty basic, but I thought it would be good background reading to get us started. Let me know if you have any problems with the file.

I tried to look for some of Steinbuch's original papers. Unfortunately, the UQ library doesn't seem to have access to a lot of them, and the ones that I did manage to view were all in German.

If I get the time, I'll try to post a relevant paper.

If there is anything confusing or that doesn't make sense in the summary, feel free to comment.

Advertising: PAIN Lab Tour

If you want a look-in at some of the labs in Physics and the IMB, consider coming along to PAIN this Friday for a quick lab tour. All interested will be meeting up at 5pm in the physics tearoom.

2 micron polystyrene spheres arranged to form the word `hi' using optical tweezers (Laser micromanipulation lab, Physics)

900 MHz (21.1 T) NMR Spectrometer (Institute for Molecular Biosciences)

Thermodynamics of Computation

This site provides a good, fairly accessable introduction to the thermodynamics of computation with links to other sources.

(Disclaimer: if you go to the about page, you'll find out why I know about this. And also why another of us may find this familiar..)

housekeeping from yesterday

Just the updated schedule we came up with yesterday:

week11: Neural Networks (everyone to find an article/site, post it on the blog and come to the tute prepared to explain it to/discuss it with others) / Kristen & Michael present

week12: Photophysics / Ack & Tomas present

week13: Structure, property, function relationships / Alex presents

And Ross's hot tips for inserting links to papers in our posts:

Type " dx.doi.org/10.10xx " , where 10.10xx is the digital object identifier number. Every paper has one, and you can find it written on the paper usually wherever the other citation details are (along the bottom of the page, or up top right).

2009 Nobel Prize in Medicine or Physiology

Today's prize announcement is worth reading since it involves some cool chemistry and biology.

Hey all i'm sure we are all thrilled to be back from our, not so "mid" semester, "break" from lectures (at a cost of doubling our workload for the week).

That said I was able to catch up on a little bit of sleep and fit in a small social life.

Sadly this post is not going to be filled with to much content from out text as I managed to leave at home when scrambling out the door for my 8am lecture. This means I wont be able to finish the last part of my reading before the discussion (even google couldn't find a pdf copy for me) but has meant I have time free to do some blogging.

I find the content in this chapter interesting but have come across the majority of the concepts before. This leaves me with calculations and proofs for the concepts for new material which I personally, don't find very stimulating. Ironically most of the applications which I often find more interesting are in the second half of the chapter.

I'm not sure if this is covered in the chapter but I'm a bit confused as to the relation between energy and so called "calculation". By this I mean is there a direct measurable energy cost for our brain creating/calculating information. Of course the process itself is taking energy but in a physical sense is this all being dispersed as an increase in the kinetic energy of the ions traveling across the membrane and a decrease in entropy as the gradient across the membrane is reduced. Does this come back to our earlier discussion of so called "high quality energy"?

Tried to google these ideas but was getting nowhere quick so I will probably have to refine my search. Anyway I just noticed the time so even though none or you will read this before it happens see u in 2 minutes! =P

Micheal.

This week

Welcome back!
I trust you had a good week with a break from lectures (n.b., I did not say holiday).
Tomorrow we will discuss the last chapter of Nelson. It is a great one.

Biological question: How can a leaky cable (e.g., a neuron) carry a sharp electrical signal over long distances?

Physical idea: Nonlinearity in the cell membrane's conductance turns the membrane into an excitable mdedium, which can transmit waves by continuously regenerating them.

On more mundane matters on tuesday I want to
-give you a TEVAL to complete
-pin you down on paper presentation topics
-remind you of the assessment details

Also, I will be away for the following 3 weeks, but Seth will attend the tuesday tutorials and talks.

ack abstracts some highlights from the chapter on electricity generation

So.. chapter 11 is exciting to me, not just because it begins to address my persistent questions about HOW molecular motors do what they do. I understand its focus to be free energy transduction: biology creating electricity “out of nothing”!

At first when I read the Benjamin Franklin quote at the start, I scoffed and thought that so many other things in science are better than plain old electricity at making “ a vain man [sic] humble”!! But then I decided that Nelson hadn’t put that quote there to remind us that electricity in and of itself is a marvel- rather, that the marvel is the super efficient generation of electricity by (/in/through?) biological systems. And this, I think, really is a great example of “natural” biophysical reality doing a much greater job than humans at something humans value.

I also like the way this chapter talked about structure, function AND property, but connected those three things in a different way to the standard “structure THEN property THEN function” narrative we tend to use when talking about investigating proteins. For example, Nelson talks about the function of “some busbar” connecting respiration pathways and ATP synthesis machinery before he identifies the busbar structure as a mitochondrial inner membrane. (Have I managed to make sense? If not, someone pull me up about this is class please.)

Last but not least!: I’d like to mention oxygen as another reason I liked ch 11. It’s possibly something human movement students learn early on, but I’d never thought much about anaerobic vs. aerobic energy production. I think it’s fair to say I now have a greater appreciation for the significance of O2 on earth (hooray for being able to couple the energetically “uphill” phosphorylation of ADP to the energetically favourable oxidation of the product of glucose glycolosis! [which I've learnt is called pyruvate]). Is there an analagous "environmental factor" that helps boost energy production in anaerobic organisms?

Neural correlates of interspecies perspective taking in the post-mortem Atlantic Salmon

Because not all of us are members of physics-all :
"Neural correlates of interspecies perspective taking in the post-mortem Atlantic Salmon"

Remainder of semester schedule

Hi all,

I was supposed to post this schedule for us all to see. As Kristen has already posted a reminder that this week was chapter 11, i will continue from week 10 after the hols:

week10: Chapter 12 / presentations (?)

week11: Neural Networks / 2 x presentations

week12: Photophysics / 2 x presentations

week13: Structure, property, function relationships / presentations (?)

...something like that. We have a bit of probably necessary flexibility in presentation times at the moment.

I have been a bit crook this last week, think i pushed the molecular motors too hard? haha

Also, my Biochem prac during "teaching free week" and I think I get my break at 1pm, so I might miss you all unfortunately tomorrow.

Cheers, Alex.

Michael Mulls over Machines in Membranes Meticulously

I’m not sure if any of you are the same but I have found it difficult to know what to say when blogging. If it is before I have done the reading I obviously don’t know the topic yet and if it is after the reading my head usually hurts =P. I find it difficult to just post questions on the blog as I think better when bouncing ideas off people and often better understand the answers I get if I can hear them in person and clarify what people are saying. It is also easier to realize you don’t quite understand something when talking a topic through with someone.

This said in an attempt to make blogging something I can do more successfully I am going to do a running blog as I go thought this week’s reading writing my thoughts as I go. This means either this post could get very long or the more likely option this post will be heavy with content from the beginning of the chapter and slowly decrease as my stamina dwindles.

Machines in Membranes

Initial thoughts from intro: Oh good I have done quite a bit on this subject before but I wonder what slant this chapter will take on the topic.

The brief historical recap is quite interesting and left me wondering if I would have going into science if I have been born back in those days.

11.1.2 is good to know but at the same time I have done a lot of it before and no offence to the authors but how can they manage to make something which is interesting and rather simple in principal soooo boring. – on an side note I was most disappointed when I eventually realized many of my subjects were talking about the “squid giant axon” and not the GIANT SQUID AXON which my mind had hoped for.

11.1.3 Surprisingly the term Donnan equilibrium doesn’t pop to mind when I think about this topic and I don’t really remember it being mentioned in other subjects. From what I understand it is due to charged macromolecules trapped within cells and is a description of an equilibrium state which could be representative of non neuronal cells…? We can talk about this in the tute.

N.B. Considering the number of times chapter 11 references chapter 7 maybe it was a bad choice to skip it hehehe =P.

11.2.1 Wow just found the section talking about osmotic pressure providing plants with their rigidity really cool! I would also not have remembered to say this if I had written this blog later on. I really haven’t done much plant biology mostly animal maybe I should. Then I can create some SUPERHUMAN PLANT HYBRID harnessing the POWER of OSMOSIS . . . oops side track.

I like the phrases “equilibrium is not life; its death”, and the one I want to see in a movie “Entropic forces can kill.”

Like I predicted, despite this method creating a better blog entry it has taken me a couple hours to get only half way through the chapter. Realizing this I just read ahead without blogging every thought. The rest of the chapter is also quite cool, the way in which the body really does function as a factory on so many different levels. This is a concept I am quite familiar with from my biochemistry courses so not many things caught my attention.

With that I think I might end this post as it is taking up an A4 page in word and I imagine it will be significantly larger than that on the actually blog.

See you all on Tue. Michael.

Reading this week

Hi all,

Just a reminder - at the tutorial on Tuesday, we decided that we'd all read Chapter 11 in Nelson for next week.

next assignment

Due tuesday 23 september

chapter 9 people

Problem 9.1 and 9.2 in Nelson
and any two of 9.5, 9.6, 9.7, 9.8, 9.9, C9.12, C9.13 9 (see pages 594 ff.)

chapter 10 people

10.1, 10.4
and any two of 10.5, 10.6, 10.7, 10.8, C10.10 to C10.14

Modelling complex systems

I'm yet to finish my Chapter 9 reading, but I thought I would post an idea from Chapter 9 which is probably more widely applicable.

At the beginning of Chapter 9 of Nelson, it is argued that when studying a system which has a large number of constituents which are allowed to interact - such as a biological system - the analysis of the system can be greatly simplified, using just a few degrees of freedom to effectively describe a system's behaviour.

So when you have a large interacting system - our analysis can be made more simple if we first stop to think about what are the parameters that we can use that will more widely describe the bulk behaviour of the system. I think that at times this might seem like an oversimplification, but I think when analysing a large complicated system, we need to think about what questions we're really trying to answer, and what parameters are the most important that will allow us to answer that question. If you tried to take everything into account, then at times it's going to take far too long and will be far too complex to model, when some of the minor details may not matter when trying to answer a particular question about your system.

This week's Reading

Just a reminder about the reading for this week:

We decided at the Tuesday tutorial that we wanted to be able to have time to cover topics outside of Nelson, and we knew that Alex wanted to cover some of the Enzyme material on a week when he'd definitely be able to make it. To that end, this week we're reading Chapters 9 and 10 of Nelson. Since two chapters is a lot of reading, Ack and myself will be reading Chapter 9 and Tomas, Michael and Alex will read Chapter 10, and we'll get together and teach each other any material we've missed out on at the Tuesday session.

Ross and Seth - I'm guessing you guys could just pick whichever one you found more interesting.

Kristen

Physics Colloqium this week

Just in case anyone here was interested, the Physics Colloqium for this week is titled "Nonlinear dynamic phase contrast microscopy for microfluidic and molecular biology applications". The abstract for the talk can be found here. It will be held Friday (11th September), 4pm in 7-222.

Biofilms and quorum sensing disruption

Further to Tuesday's brief discussion of biofilms and their effect on urban water supply networks, I came across the publication Biophysical controls on community succession in stream biofilms (citation). For those wanting more info on biofilms, this article (citation) is dated but a good read. (L. Sly is still at UQ, and I'm sure would answer any questions on biofilms, water quality and the SEQ supply network.)

New biophysics research prize

The McAuly-Hope prize is a new award for original biophysics research. So if you come up with something novel and fantastic during the course of PHYS3170 - and happen to have been an ABS member for two years - this could be for you...

(If you aren't interested in the prize itself, the autobiography quote on the web page is worth a few seconds.)

Supplementary Reading for Stat. Mech. in Biochem.

Hi All,

If anyone decides that they just can't go on living without more Statistical Mechanics reading, another good place to look with a Biochemistry/Mol. Bio. focus is the book by K. Dill and S. Bromberg "Statistical Thermodynamics in Chemistry and Biology".

-Seth

Thoughts on Chapter 6

I have to sympathise with Kristen as I too found the initial portion of this chapter rather dry. At the time I found it frustrating as I felt I understood most of the concepts yet continually had to think my way through equation after equation. That said it was actually the equations which helped me to better understand many of the concepts by the time I finished the chapter.

Despite my initial disapproval I did find the chapter useful although perhaps not the most interesting thing I have ever read. That said I hope someone can pull out some interesting application for this weeks discussion as I'm currently a bit light on for ideas.

Comments on Chapter 6 so far...

I have found the beginning of Chapter 6 to be very dry. To me it seems like it presents a lot of formulae all at once, and had I not seen some of that material before, I don't think I'd be able to take it in all at once. To that end, to anyone who is more interested in learning more about statistical thermodynamics I would recommend having a flick through the relevant chapters from Physical Chemistry by Atkins (any edition) or An Introduction to Thermal Physics by Schroeder. Having said that, we've probably already got a lot to digest!

It strikes me as odd in that in the entire Chapter 6 of Nelson, there is no mention of the equipartition theorem (where you have 1/2 kT of internal energy per degree of freedom in your system), but it is implied when Nelson presents a lot of results about ideal gases. I would have thought that it would be important to explain how you get, for example, the internal energy of an ideal gas, rather than just presenting the results and using them to derive other results. Perhaps it's more of a physicist thing to be concerned about the equipartition theorem - do 'biophysicists' not care about it as much?

Posts on chapter 6 to read

I just put a couple of posts on condensed concepts.
sorry, I wont be at the tuesday meeting.
Hopefully, I will see lots of other posts before then.

Recap Discussion Sept 2

To recap my impressions - one day later - from this week's discussion, we established some important points.

1. The Reynolds number gives the relative importance of inertial vs. viscous forces for an object moving through a fluid.
2. The small Reynolds numbers experienced by bacteria (and even more so, biomolecules) means that their mechanics are very different from objects on our scale (a car, for example).

One of the consequences of observation 2 is that is is incorrect to think of the energy from a chemical event (ATP bond breaking, for example) at a given site in a protein is the "same" energy that is used to accomplish something at a distant part of the protein. This would be an inertial transfer, which cannot happen in water on the scale of molecules. Rather, molecular motors work through a "Brownian Ratchet" action, where the energy is used LOCALLY to make a change that alters the energy surface on which the system is diffusing. The energy that is harvested at a distant location is not the "same" energy as was originally liberated, it is harvested instead from the thermal motions, which now occur on a BIASED surface.

En route to explaining this, we reviewed Feynman's "thought-ratchet" and his result that you cannot harvest fluctuations with a ratchet if the entire ratchet - both the handle and the ratchet itself - are in the same bath. You can harvest energy, however, if the handle and the ratchet are in different baths. This helps explain why membranes are so important to biology - they separate baths with different states, and allow energy harvest.

-Seth

Key concepts in thermodynamics

As much as I love Nelson's book I prefer to approach teaching thermodynamics and particularly entropy without introducing microscopic notions such as ensembles, probability etc.
The first ten of these slides I use in PHYS2020 to give a succinct view of the key concepts in thermodynamics. Here entropy is a macroscopic concept associated with irreversibility.

Drag profiles of mammals

For some interesting information on the drag profiles of several mammals in the laminar and turbulent regimes, skim through pages 82-88 of Fish, FE (1994). Influence of Hydrodynamic-Design and Propulsive Mode on Mammalian Swimming Energetics.Australian Journal of Zoology42, 79–101..

Turning back the clock in these turbulent times

I am enjoying reading Nelson at 2am saturday morning in Toronto. (I am still jet-lagged). I found several nice videos about turbulent and laminar flow.

This video shows how as the velocity of flow increases above a critical value (determined by the magnitude of the Reynolds number) that there is a transition to turbulent flow.

This video shows dramatically what the static photos in Figure 5.1 show. That at low Reynolds number (i.e., for laminar flow) it looks like mixing does not happen.

Enjoy!

"Real" Biophysics, Levinthal's Paradox and Dawkin's Weasel

In the last session, we made some hash about the "what is biophysics?" question, and at some points the idea of "real" biophysics came up. I have thought some more about this, and have something to write on the issue.

I am always nervous about putting a pin on a "real" anything, because "real" is often defined as the complement of "not real", and I usually am loathe to throw anything out.

Instead, let's use "ideal"...

Seth's definition of Ideal Biophysics: Ideal Biophysics is what occurs when you can't understand the biology without physics, and you can't understand the physics without biology.

OK. It is apparent (to my biased view) that there are more examples of where physics makes sense out of biology than the other way around. But, I can think of an example. The example is Levinthal's "paradox". Like most paradoxes in physics, it isn't. It is a "straw man". It does make a point though. Here goes...

Consider an idealized protein. It is a polymer of N amino acids (AAs). Now, assume the bond between each AA can only take a few orientations M. Now the total number of protein conformations is N^M (^ is "to the power"). To put a more concrete face on it, let's say N=101 and M=3. Then there are 3^101 conformations of the protein. Now, let's assume that the protein can switch conformations at the rate of 10^13 per second (this is actually ~100-1000 times too fast to be realistic). Then we conclude the following: if the protein finds it's native state by a random, serial, sampling of the available states, then it should take ~10^27 years to fold, approximately. This is longer than the age of the universe.

However, protein's fold in, at most, minutes and usually in milliseconds or seconds (101 residues is not large, so the latter is more reasonable for our ideal case). How does this happen?

We'll answer it by posing another example, put forward by Dawkins (of "Selfish Gene" fame). Dawkins asked how long it would take a monkey to write Hamlet's quote "Methinks it is like a weasel." There are 28 characters, including 5 spaces. The alphabet has 27 characters for each location (26+space). If the monkey only had these letters on a keyboard, it would take ~10^40 keystrokes. However...

If the monkey cannot change those letters that are already correctly in place, then the monkey takes only a few thousand keystrokes!

OK. So what's the point? Is it time to put me in a straight jacket? I hope not. The point is that getting around the "paradox" requires the presupposition that certain arrangements are "correct". This is not spooky, really. What it means is that understanding the physics of protein folding requires understanding that evolution has taken place and is ongoing - a biological fact. Put another way, what it means is that when we start by saying "consider a protein" we are automatically excluding those sequences which can only fold by executing a serial search of the available conformational space.

More precisely, and to bring in more ideas from the last session, the statement should read more like "consider a functional, single-domain protein". What Levinthal was getting at (he wasn't confused - he set up the paradox to shoot it down) was that the ensemble of possibilities given "functional single-domain protein" automatically must exclude a very large number of possible amino acid sequences. The ability to fold in biologically relevant time is a constraint on the ensemble.

And, as I mentioned, when you see a "funnel" representing a protein landscape, the usual X-axis is literally "the number of native contacts" in the same way that you could consider the "number of correct letters" as a suitable reaction coordinate for the Hamlet-writing monkey.

-Seth

Just so we have it in writing: everyone seemed happy with the suggestion that the final due time for the assignments would be our old meeting time of 12:00 (midday) Thursday at the room we currently meet in. Tomas if you want to hand yours in at 11 because of you lab meeting at 12 I will be at the room from 10:50 to 11.05 for you but have a class I need to be at so cant be there any longer than that. Hope this works for everyone just comment here if there are any problems.

Michael.

Recap & Chapter 4 Problem Set

The minutes of this weeks meeting (as I remember them):

1.We will read and discuss Chap 5 of Nelson.
2. Chap 3 problem sets are to go to Michael. I will furnish Michael with the answers as soon as I receive them. Michael will decide how to deal with late submissions (the only contraint being that the policy is dealt consistently in all cases, even his own).
3.The course syllabus is up to the students. Paper discussion is on the agenda. We (Ross and myself) will suggest papers, but so can all of you.
4. The steady state is important for model problems in Biophysics, even if it is not the same as equilibrium. In many cases, it sets boundary conditions on the diffusion equation which lead to interesting and relevant solutions.
4. We all want to understand Maxwell's Demon.
5. Biophysics is difficult to define, but nonetheless interesting.

If I missed anything, please chime in.

The problem set for Chap. 4 is: 4.2 (a-c only), 4.3, 4.7. Enjoy!

Tutorial Questions

Hey if anyone wants to discuss the tutorial questions for this week I will be in the physics tea room the same as last time from 9 to 10 just before our session.

Myoglobin structure

The protein that I've chosen to look at is myoglobin, which incidentally was the first protein structure to be found. Here is a picture of the structure:


Myoglobin binds carries oxygen in muscles, and binds oxygen at the heme group. The heme group is a porphyrin, which contains an iron atom at the centre. Porphyrins are aromatic molecules which are highly conjugated, usually deeply coloured and like to form complexes with other atoms. In this case, it is iron. The heme group is the red group of atoms at around the middle of the structure. Oxygen molecules bind directly to the iron atom.

The heme group is stabilised by hydrophobic interaction between the pyrrole rings in the porphyrin and hydrophobic amino acids in the interior of the protein. Additionally, a nitrogen atom from a histidine residue above the plane of the heme ring is coordinated with the iron atom, which also stabilises the interaction. I was able to find this particular histidine atom, and while it is still hard to see, it is one of the light green residues with the pentagon-like shape at the end of it in this picture, situated above the plane of the heme ring:

In order to better see the heme group and the binding site, I also made a ribbon structure. The iron atom in the centre of the heme group can easily be seen.

Hey Sorry this is a bit late. I managed to get myself nice and sick and had close to 12 hours sleep the last few days.

This is what I ended up with for question 2.4 - I choose ATP as the small molecule to investigate and interestingly GrowEL came up as one of the molecules which binds to it. I covered this protein in one lecture and found it quite cool which is why it caught my attention. It is a chaperone protein so it helps other proteins fold by encasing them in the central pore shown in the picture included.


Both ends of the protein are capped by growes in this process and ATP is used when the growes is removed. Sadly I could not find the ATP binding sites as the protein is rather large but u can see in the central pore several little legs which stick out and interact with the protein being folded either hydrophobicly or electrostaticly if the protein has charged residues within it. These residues vary depending on the protein to be folded and help overcome energy barriers ect to prevent incorrect conformations being attained (which I think is really clever design to help the protein reach the desired conformation).

Upcoming Reading

So for next week, we're doing the reading for Chapter 4 of Nelson, but the week after (if we follow the book), we'd be set to read Chapter 5, entitled "Life in the Slow Lane: The Low Reynolds-Number World". While the contents of the chapter are definitely important to some aspects of biophysics, the year I did PHYS2170, the second year biophysics course, we covered a lot of that material in quite a bit of depth. To that end, I'd like to propose that we skip Chapter 5 in our reading.

If I'm outvoted and everyone else would like to study Chapter 5, then that's fine, but I just thought I'd put the suggestion out there. Thoughts?

Tutorial Tues 18 August

For those of you that weren't at the tutorial on Tuesday, here is a summary of what we discussed.

We discussed Chapter 3 of Nelson. The first part of the chapter gave some details of statistical analysis, and went on to talk about Activation energy, and how it was related to a distribution of molecules. Not all molecules in the system will have the same energy and the high energy molecules are the ones that are able to get over the barrier first.

There also seemed to be two sections of Chapter 3, which seemed to be unrelated at first glance. We spent a little bit of time discussing the link between the two sections, and concluded that the second part of the chapter was trying to emphasis that there was a stable entity that could encode genetic information, and the stability arose from the high activation energy due to chemical bonds.

We talked about how the distribution of energy of molecules in a system had a Gaussian shape, and that this held regardless of the details of the system (the type of molecules, for example), as long as we could treat the system as an ideal gas.

We also discussed how crossing over is a process which creates diversity, and that it would probably be a rare occurance. The genetics section was trying to emphasise the point that if we take simple physical arguments, and apply statistical reasoning, we can infer things that we can't see - in this case, the encoding of information. It is also important to be able to find a good model system. For most genetics work, this model system is Drosophila Melanogaster, the fruit fly, which enabled study of genes more easily as it has large polytene chromosomes present in its saliva.

next assignment

Due tuesday August 25

Complete at least one of 2.2, 2.3, 2.4, or 2.5 and post the results on the blog.
Comment on the relationship between structure, property, and function for the molecule of choice.

Questions 3.1, 3.2, 3.3, 3.4 Nelson

Proton Pump

To add to our discussion last week's chapter (Ch 2), I thought I'd put up something on proton pumps. Below is a video with voice-over giving a simple explanation, and p56-57;59 from Ch 2 has some generic information on ion pumps.


And here is the full 3D structure of 3B8C, a P-type proton pump, determined from X-ray crystallography experiments.


Right-click on the Jmol applet above to interact with the structure (highlight domains, calculate hydrogen bonds, show surface et cetera). If you want to visualise how this might fit into the cell membrane, try colouring residues by charge (e.g Select→Protein→Basic Residues (+), Color→Surfaces→Blue||Color→Structures→Cartoon→Blue ).

(Edit: If the above widget fails, or you want to look examine this in more detail, you can view the structure here.)

Chapter 3

Where are all your posts guys?
How are you going with the problems from chapter 2?

Here is my take on chapter 3.

Tomorrow morning I will select some problems for you to do and hand in by next tuesday.

See you 10am tuesday.

Biophysics vs. Biological Physics

I’ve wondered before if there’s any substantial difference between the terms “biological physics” and “biophysics”, because it seems that they’re sometimes used interchangeably. Then reading back over Ross’s condensed concepts post on July 22, I noted he had made a distinction between the two terms so I thought a bit of clarification early on would be a good idea. The best I’ve come up with is this:
Biophysics = existing physics applied to biological problems. We know the physics and we know the biological entities involved. Eg. action potentials in neuron firing.
Biological physics = developing new physical models relevant to biology. We might use existing physics concepts / approaches, but come up with descriptions that are “new” at least insofar as they are different qualitatively from existing models. Eg. ion channels?
Does this sound reasonable to you? Is there an example of biological physics that is more clearly different from biophysics? Does it matter?

This second definition sounds a little like the description Nelson gave in 1.3 of how physicists and biologists can best work together: as well as using powerful existing experimental and theoretical tools from physics to explore biology (eg. X-ray diffraction and…the maths used to describe co-operative helix-coil transitions in DNA), physicists can apply their knack for simplifying things to deduce new nontrivial, testable and relevant (!) hypotheses from simple accurate models of biological situations.
As a physics student with little background in biology, it’s been interesting to read chapter 2 this week while keeping in mind that a number of great “solutions” to problems in biological physics have, in the end, looked a lot like straight biology. That is, solutions have ended in suggesting the existence of new biological entities (some of which were among the different supramolecular complexes considered in ch. 2!!) such as ion pumps.

Reading chapter 2

I posted a few brief comments on condensed concepts

Tutorial Question Session

Just wondering if anyone would like to got together Thursday morning to compare answers to the chapter 1 tutorial questions possible 9 or 10? I have an answer to each of them but a couple of them seem wrong so I would like to bounce ideas off someone or even work the questions through with anyone who hasn't had time to look at them yet.

Have a nice holiday tomorrow (for anyone who isn't currently bogged down in assignments amazingly early in the semester),

Michael.

Getting Blog Updates By Email

Hey all just a quick tidbit of info i found:

If your anything like me its really hard to remember to regularly check the blog in the busyness of everyday life which is why I was excited to find that the blog can be set to send you an email when a post is made. Now I don't yet know if it will let you know if a comment is left on a past post but I know it emails you when a new post is made cause I just received an email telling me Ross posted.

To set it up just go "Customize" (top right corner), "Settings", click the tab "Email & Mobile" and type in you email, then click save settings down the bottom of the page.

Hope this helps and makes sense considering how heavy my eyelids currently feel.
Michael.

How is your reading?

Post something!
Someone should post a summary of the discussion of the last tute.

If you come by my office between 9am and noon on tuesday I should be able
to give you a copy of the textbook.

Please post comments on your reading on chapter 2.
The next assignment (due 2 weeks from this thursday) will be most of the questions at the end of chapter 2. You can post most of the answers on the blog since it involves looking at cool pictures of biomolecules....

Why Entropy?

Thomas asked a question at the end of the class today. If memory serves, it was something like: if you had access to all of the information, wouldn't you just keep track of the energy itself?

I am not going to answer this question now, although maybe later the answer can be revealed. However I will pose a question in return...

What - in practical terms - would it mean to "have access to all of the information" in such a way that this could be done?

The second law of thermodynamics

For an adiabatically isolated system the entropy of the system can
never decrease.

But, a more practically useful form of the second law is:

for a system in equilibrium with an environment at a given temperature and pressure the Gibbs free energy, G = U + PV-T S, can never increase.

Consequently, in the equilibrium state of any system (whether a folded protein or a superconductor) the Gibbs free energy must be a minimum.

Never forget this! This is the most important idea in all of thermodynamics!

Thursdays tutorial

Today I have done a three more posts on chapter 1 over on condensed concepts.

Tomorrow we will meet in the interaction room at noon (physics annex 424) since I hope it will be more congenial to round table discussion.

For the first assignment (due next thursday August 13 at noon) I propose problems 1.5, 1.6, and 1.7 in Nelson. We can discuss this.

Free Energy

Chapter 1 of Nelson's book to me felt a bit like revision. It went over a few important concepts for us to know, focusing on thermodynamics, which is very important for a biological system. I think that there was a lot of focus on making sure we realise how physics, and physical methods can apply to biological systems.

I think a lot of the main concepts in the chapter have already been discussed by Ross, but an important concept for me was the concept of minimisation of free energy, which can spontaneously drive processes in a system. Whilst the book doesn't give many direct biological examples, I still think that this is important. Free energy minimisation can be an important tool in structure prediction of proteins, where it is used to try and determine how a protein will fold, based on its amino acid sequence. A likely structure is found when there is a free energy minimum, found using computational methods and taking into account forces between the atoms. Unfortunately, though, this free energy minimum may be only a local minimum, so several likely protein structures can be found. I am yet to find a good reference on the internet that explains this further - so if anyone has one, feel free to comment.

Molecular motors were described as "free energy transducers" by Nelson. This is a youtube video of the molecular motor kinesin. This molecule transports other molecules, and sometimes organelles such as mitochondria around the cell by converting ATP into energy, and using that energy to "walk" along.

For me, this chapter didn't bring much that was new to the table, but I think laid the foundation for future chapters. It will be interesting to see how Nelson further develops the main ideas in Chapter 1 as the book progresses.

- Kristen

Questions on chapter 1 of Nelson

I hope you are enjoying chapter 1 which I emailed around last week.
I have posted two items on my condensedconcepts blog about it. Now, that I can post
on this one I will start posting here.

What questions do you have?

What do you think the main points were?

Maybe someone could find a good youtube? video of
-reverse osmosis
-a molecular motor

Kicking Things Off

Hey fellow Phys3170ians, just kicking this blog off to make sure we can all access it and are able to post. Just add a quick reply to this post saying hi and we should be ready for action.

Michael.