alpha-helix signals -> protein folding

Paul Baulch shnub at zikzak.apana.org.au
Mon Jul 18 08:42:31 EST 1994


jones at bsm.biochemistry.ucl.ac.uk (David Jones) writes:

>Rob Miller (rmiller at bsm.bioc.ucl.ac.uk) wrote:

>stuff deleted...
Lots of stuff deleted...

>computationally expensive - they need to consider side chain positions,
>they need at least the positions of the polar hydrogen atoms and they
>really need a good model of the entropic effects of solvent. Even when
>
Presumably the major effect of solvent, in terms of energy, would be to 
encourage the tendency toward the global minimum, by providing sufficient
"brownian" impetus to surmount local (and global!) maxima. Can/has this
impetus be/been quantified with regards to protein conformational energy?


>
>or kinetically stable. What we know by looking at the native folds of
>proteins is that tertiary, super-secondary and secondary structure is
>highly recurrent as a result of evolution, stereochemistry or most likely
>both. No matter whether the proteins we observe are sitting happily in
>their global energy minimum or rolling about in a higher energy local
>minimum
>
Ah, a moment there. If they are not in the global minimum, then presumably
there exist energy maxima on either side of the global minimum which are too
high for any solvent contribution. After all, the chain's own interactions
cannot let the conformational energy potential rise, yes? Only fall.


> we know that the very next protein structure to be determined
>will consist of some mixture of alpha helices, beta sheets, beta-alpha-beta
>units, alpha or beta hairpins, alpha corners, beta barrels etc. We also
>expect that there will be a well defined hydrophobic core, no steric
>clashes and a fairly high proportion of potential hydrogen bonds will be
>made. In addition protein topologies are generally right-handed with some
>exceptions. The knowledge-based methods are based on the hope that these
>empirical constraints are sufficient to arrive at a good approximation
>of the native fold.
>
But does their source (X-ray, small-protein NMR) perhaps display a bias 
towards only a cross-section of what could perhaps be a much larger 
spectrum of conformational possibilities? Do you know what proportion of 
proteins studied have defined clear structure elucidation by the 
aforementioned methods? And, is much evidence that any particular 
residues behave differently in such proteins? That would be interesting to 
know.


> They are also based on the hope that by applying these
>constraints it is possible to get away with a far cruder model of the
>protein's energy function. Whilst we really have very little idea of what
>form the hydrophobic effect really takes, the fact that at the end of
>the real folding process hydrophobic residues tend to lie close together
>results in a very simple constraint i.e. pull hydrophobic residues close
>together or in the case of threading for example, penalize any hydrophobics
>that are not close together (or some variant thereof). Of course these
>methods don't really shed much light on how proteins compute their
>own conformation - they are (or at least will be) very useful tools for
>helping humans work out the function of newly sequenced proteins, but
>they will not necessarily help us fathom out how protein sequences
>apparently code for a unique 3-D structure.
>


>So what are the future prospects? Well I would expect that within about
>10-15 years or so, somebody, somewhere will have a program that will
>be able to predict the tertiary structure of a given protein sequence
>with at least reasonable accuracy (say to 3-4 A RMSD). I expect this program
>will be based on some kind of pattern recognition method - either
>recognizing whole folds or recurrent sub-structures. I am very doubtful,
>however, that the algorithm in use in this futuristic program will have
>anything in common with the "algorithm" proteins actually use.
>
I would hope that it would be as simple as taking as many Ramachandran-type
plots as there are residues, overlaying them on each other combinatorially
with some sort of AA-dependent matrix, then choosing the lowest potential
in each plot as the postulated conformation for the corresponding alpha
carbon conformation. That would be fairly nice and simple. One would have 
an overlay matrix for alanine, tyrosine, etc. and so each residue would 
affect the other to some (possibly often negligible) extent.
Mind you, doing "Combinatorial 1000" matrix operations may take awhile.
One could always use a coarser (smaller, less angular resolution) overlay
matrix, unfortunately the algorithmic complexity is unchanged.
The only problem with this idea is that it may be quite impossible to 
determine even empirically the value of these "overlay matrices". For a start
we only know the location of one or two minima per plot, per protein, and
although our simulations can synthesise much of the surrounding "terrain",
we cannot trust it completely. There seems to be grossly insufficient data
i.e. we would have to elucidate most conformations of a protein at most
levels of conformational energy before we have enough constants to solve
for the variables.

>One question that I often toy with when the subject of the protein folding
>problem and its possible solution arises is just how are we going to
>recognize the solution when it (eventually/if ever) arrives? If someone
>creates a black box which guesses the native conformation of a protein
>chain right every time, is this a solution? If someone works out that
>proteins fold by doing X, Y and then Z but that we cannot hope to
>simulate X or Y let alone Z, is this a solution?
>
It's an approximation, like any and EVERY simulation. The fact that its
internal structure would be unknown would mean that it's not really what 
we want, yes. It would, after all, mean that protein design would stay
very much a trial-and-error practice. Or could the same black box actually
be capable of reverse guessing? Surely not.

I think simulation is our only hope, for I believe that empirical techniques
would require the assimilation of FAR too much conformational data (remember,
most techniques get the very bottoms of a few minima). I think it would 
be much, much faster to develop (even by trial and error!) equations that
give the correct results (i.e. minimum positions) with increasing consistency.
Presumably neural networks and such are being developed which do just this.

>Anyone any comments on this? I'm sure we'd all like to know when it's
>time to give up on protein folding and find another interesting problem
>to work on!
>
I think that this is quite interesting enough. Please don't give up now!


-- 
-shnub at zikzak.apana.org.au--------------rec.toys.lego forever!!!-------------
-----Paul Evan Baulch------Reality is by far the most impressive simulation.- 



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