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Most likely, there will be a scientific paper containing the results, and as far as I know, scientific research papers are public (or maybe require a fee to read).

Yes, they require a fee to read - in this case, $32 - and yes, scientists are just as unhappy about this as everyone else, but we have no other way to prove our worth to prospective employers, funding agencies, and tenure committees other than prominent publications. However, the actual structure (including experimental data) is deposited in a public database, as required by every major journal in the field, and should be available shortly. (There is usually a little bit of lag time before these depositions are released to the public, but rarely more than a couple of weeks.)

PyMOL http://www.pymol.org/ is a great open source crystal structure viewer and there's all sorts of available enzymes with small molecule inhibitors in them at the protein data bank. http://www.pdb.org/pdb/home/home.do Let the students find an enzyme online, make a picture of the enzyme active site with or without an inhibitor. Set them to the task of finding a small molecule inhibitor via the internet or based on what's in the crystal structure. As them to tell you what functional groups are involved in the molecule, etc. There aren't any easy to use, free docking programs to screen student-designed potential inhibitors... sadly.

PNA (peptide nucleic acids) are most certainly NOT nucleic acids chains with some protein bound to it.

A PNA is nucleic acid bases (the purines/pyrimidines in the first image) linked together by an amidate backbone, similar (nut not identical) to the one that links amino acids in a protein.

If you want to see the structure of a DNA/PNA duplex, look here. Pay close attention to the structure of the backbones in the two strands. There is no protein in a PNA.

hn

It will cost the space program a lot of support.
There goes the 'we can make much better crystals of proteins in zero-G' sales pitch (Anyone dare to guess how many http://www.pdb.org/PDB entries are space-crystals and how much better they are than the flatland versions?)

There are some models for this, including the National Nuclear Data Center (http://www.nndc.bnl.gov/) and the Protein Data Bank (http://www.pdb.org/). I'm sure there are other examples out there.
(Disclosure - I currently work at BNL, where the NNDC is located and the PDB originated).

if you are interested to see the surface of such a storage media before even somebody have build it, have a look here: http://www.pdb.org/pdb/explore.do?structureId=1QM8 and just imagine not seeing only one protein but a whole lot in one surface :) greetings from a molecular biologist!

All available genetic data (and protein data) from every sequenced organism has always been publicly available. Whether it's due to requirements by publishers of the journals that they publish their analysis in, a requirement of their funding agencies, or for the mere goal of sharing their data with the global scientific community.

Gene sequence databases have been around since 1981:
EMBL: http://www.ebi.ac.uk/embl/
GenBank: http://www.ncbi.nlm.nih.gov/
DDBJ: http://www.ddbj.nig.ac.jp/
HUGO: http://www.gene.ucl.ac.uk/nomenclature/
JGI: http://www.jgi.doe.gov/

Protein sequence/structure data is also publicly available:
Expasy: http://ca.expasy.org/
PDB: http://www.pdb.org/

Their statement "Google is guilty of biopiracy because a searchable database could make it easier for private genetic information to be abused" is flawed on many levels.. and is merely an attempt at media hype.

A - If the genetic data is private (ie. industry funded and not shared with the global scientific community), how will Google get access to it?
B - Searchable databases that contain private/public genetic information have existed since before most other types of searchable databases.
C - Sharing data from biological analyses (whether genetic sequence data, protein sequence data, gene expression data, protein structure data, etc.) is an important aspect of understanding the underlying mechanisms of biological systems.

Many of the medical advances that we've seen these past couple decades have resulted directly from the fact that biological data has been publicly available... facilitating collaborations beyond borders and beyond disciplines.

I look forward to Google's role in facilitating access to this information, and look forward to applying it in future research projects.

Ryan

NMR has an inherit weight limit. Relatively few protein structures are found using it, most are done by XRAY-C. Currently, of all proteins structured, 5000 are by NMR 28,000 by XRAY. See http://www.pdb.org/pdb/static.do?p=general_informa tion/pdb_statistics/index.html&tb=false

There are ways to obtain structure of proteins from DNA, just that they're not so good if a similar structure doesn't exist in the Protein Data Bank (http://pdb.org/ already, its called homology modelling. You have the protein sequence of an unknown structure then look for similiar sequences in the 20,000 known protein structures. That's why the more structures we add to the PDB makes it easier to find structures of unknown proteins.

When they can predict the structure of the F1F0 ATPase, then we can throw out crystallography- but it's not going to happen.
(Ignoring for the moment that crystallography has it's own issues. . . at least it can show active sites and quaternary structure)

Well, for the first, we can't throw out crystallography even then. When you're doing a computer calculation, you are in the realm of theory. (even if you have arbitrary accuracy).

You will still need to do experimental verifications now and then.

At the moment, about 2/3 of known protein structures have been mapped through X-ray crystallography. At best the resolutions are about 1.8 Å, which is pretty good. So you can see quite a bit more than quaternary structure!

The other third is done with NMR spectroscopy,
usually with some powerful computing help to figure it out.

And then there are a pitiful few,
done with computers and experimental data.
These structures also have the poorest accuracy.

Note that computers will never, ever be able to figure out a protein structre ab initio. (i.e. without any info except the sequence)
Do the math, say you have 100 amino acids, and you
test say, 4 conformations for each, that's 4^100
combinations to test.. and you test 10 million a second, it'll take you 5E45 years.
Much older than the current universe.

(Disclaimer: I do not -yet- have my PhD in computational biochemistry.. but I'm working on it..)

Now, let's move on to the "understanding" of the human body. Excuse me, but who says you HAVE to understand it???

I should hope that if your going to have a go at combating AIDs then you'ld have a damn good understanding of the haman body. After all, as a Virus it does hijack a lot of the native human machinery to do its job.

Its very simple to combat AIDs, whats trickier is combating it and keeping the patient alive.

At any given instant, you can only ever have an interaction between two molecules. (DUH!)

Hardly. Anothing thing about human machinery is it's very rarely just one molecule interacting at a time, rather a number of subunits. If A couples to B which couples to C, and you have drug D, it's interaction with subunit C may cause A to go off and begin a potentially leathal cascade somewhere else.

Now, inorder to do your minimum energy computations you'll need to know the structures of each subunit, and the solvent conditions they are in (probably water, but who knows, they could exist in the lipid bilayers). The PDB is good, but its no where near having all the structures present in the human body. You arnt just dealing with chemical bonds either, there are weaker interactions like Hydrogen bonds to consider. These are trickier to calculate.

And then, maybe your drug (assuming its any good) may never even make it to the target sites. Maybe its not lipid soluble (and so cant get inside the cell), or acid labile (cant be swallowed).

You see, you've tried to over simplify things to the point that your pissing in the wind. In many cases, you really are looking at the ant seriously affecting the elephant, maybe indirectly by affecting the mouse (say bacteria).

That said, rational drug design has worked (IIRC even in designing a few nucliotide analogues used to combat the HIV virus). But the people in sat infront of the computers understand that it's more than a question of crunching numbers. As my Bioinformatics lecturer once said "Biology is a knowledge based disciplin, you work from what youve seen before. Physics/computing is ultimately easier, because you can work from first principles". We just dont know anywhere near enough of Biologies first principles to even think of moving completely to rational drug design.