Protein folding & computational biology

bjhenry1 bjhenry1 at
Wed Jan 10 20:08:23 EST 2001

Louis Hom wrote:

> By "resolution", I think they're talking about the level of structural
> detail that they're going after (i.e., "resolution" as it's used in
> microscopy and crystallography).  At low resolution, you get to see the
> general form of the protein (lobes, cavities, etc.), at higher resolution
> you see the backbone of the protein and how it's shaped into helices and
> strands, and at even higher resolution you can see the relative positions
> of the amino acid side chains.

I'm wondering about that as their definition though... After doing a bit
of hunting around, I discovered that one of the software imaging tools
that can be used to actually look at the chemical structure of the
proteins being analyzed by the Folding at home project is called POV-RAY. 
With that, you get a structural representation down to the atomic
level... Granted, the 5 proteins that they appear to be looking at right
now are the smaller ones...
> Why work on protein folding (beyond the fact that it's a fascinating
> challenge)?  The short answer is that it may allow us to engineer and
> design useful proteins and ligands (small molecules that specifically bind
> particular proteins) for medical and industrial purposes.

The nanotech area seems to be a good example!  I know there were a
series of articles on some of these tiny potential tools.
> The longer answer:  It has been shown over and over that most proteins can
> be completely unfolded (e.g., by changing pH) and can refold all by
> themselves into a single distinct structure when conditions are returned
> to normal.  This means that all of the information on how to fold that
> particular protein is contained in its amino acid sequence;  no outside
> information or assistance is required.  But our current ability to
> understand that "information" is limited by our ability to test our
> understanding.

One of the articles I read did mention that fascinating behavior, ie.,
the "memory" that it has built-in to return to its known folded shape. 
I think that would happen in all but the most drastic conditions...
(eg., I expect de-naturing would sortof destroy it).
> In a given protein structure (either folded or misfolded) there are many
> interactions between the amino acids and between the amino acids and the
> solvent.  Physics tells us which interactions are favorable and which are
> unfavorable, as well as how strong these interactions are.

Even the introduction of water causing some type of hydrolysis, I would
expect would have that effect...

>  There are also
> energetic contributions from the solvent and how it's structured around
> the protein.  These are fairly basic calculations, but there are a lot of
> them -- a lot of them for each possible structure (folded or misfolded)
> that we want to assess.  And if you are start with a random coil of your
> protein and you want to figure out its final structure, you're going to
> have to consider a lot of different structures (right and wrong) along the
> way.

That's what I was figuring... The possibilities are pretty staggering...

> Historically, people have tried to reduce the number of calculations
> involved in order to make the data more manageable, for example by
> grouping atoms together to behave as a single body. 

Are you then referring in terms of say the phosphates or nitrates,
hydroxyl groups, etc.?  Those are the molecules that I would think would
be more "exposed" to reaction...

> There are lots of
> researchers, using different strategies and operating under slightly
> different assumptions.  And so far, nobody has figured out which data are
> critical, and which ones are less important, to the point of being able to
> take an amino acid sequence and precisely predict the three dimensional
> structure of the protein.

Okay... that's probably where the differences would come into play...
ie., an assumption would be made and some algorithm used to determine or
predict or assume certain things...
> By increasing the computing/calculating power, it's possible to more
> precisely assess a greater number of potential structures, hopefully
> increasing the likelihood that you'll correctly predict the final
> structure.  And then you can work on streamlining your folding algorithm
> -- seeing what's most important to consider, what's less important --
> which in itself will likely be a very informative process.

That's what I was figuring... Seems almost like a luck of the draw,
although I would think that you could eliminate certain branched
possibilities based on something like the natural pH of the molecule
> It's not that we can't currently determine the structures of proteins --
> crystallography and NMR and sometimes mass spec allow us to do that pretty
> well already.  But we can't _predict_ structures from amino acid
> sequences,

Perhaps we could if the conditions were kept constant, although
"constant" at the molecular level would probably be very very difficult
to achieve!

> and with all of the genomic data surfacing, it will become an
> increasingly important capability.  The current methods of structure
> determination take a lot of time.  Structure prediction can help us
> understand how the proteins interact with each other, how they act on
> small molecules, how they might be modified to serve some other function
> or in some other environment, and how their function might be blocked.

Very true - and possibly what may cause them to go wrong...All you need
is just one little misfold to do that...

Thanks for the response!  This is kindof an interesting discussion. 
I've been out of the macro molecule world for awhile and some of the
recent news items on the possible causes of Mad Cow's disease and
projects seeking to determine the folding mechanisms, seemed to bring
the whole topic back up out of oblivion for me!


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