Toward a 3D Search Engine
Plasma Droid writes "NewScientistTech has a story about a 3D molecular search engine that is over 1,500 times faster than anything previously developed. The researchers, from Oxford University, developed a lightning-fast way to quickly match 3D shapes mathematically. This could not only speed up searches for new drugs, but lead to 3D search engines, for finding objects uploaded to platforms such as Google Earth, they say." The problem will be in jump-starting the supply of 3D data about molecules and everything else.
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No, that will be a problem. Once you have the database, what exactly am I supposed to input for searching? Will I need to learn how to create a 3D model in order to search for similar objects?
The rest of your comments are pretty valid, however in this case that would seem to be aside the point. Searching objects in this fashion would be as simple as metadata that is appropriate for 3d model searches. Rather than provide a base model, you could search the metadata supplied with/for/generated for shapes, and once you have a few from the library, use THOSE as searches for -similar- or combined models. It's actually quite possible, if of questionable use - not to mention your criticism could be thrown back at you by simply saying "What!??! A search engine for sound? That will never work, I'd have to learn how to whistle".
The implication both from the summary and from the article itself is that this new search is just as thorough as other search methods but much faster. To prove thoroughness they would have had to show that anything found by other search methods will also be found by their new, much faster, search method. I doubt very much that they were able to do prove this rigorously.
That's not to say that the problem of matching 3D molecular shapes is not important or that their research is not valuable. I would say, though, that it is misleading to claim that they have solved the 3D search problem with a much faster algorithm. There are many different measure of 3D similarity and, for many measures of similarity, the only way to guarantee an optimum match is by exhaustive search.
Note that, in general, every search will be exhaustive in the sense that the query must be compared to every entry in the database. The problem is that many measures of similarity have additional parameters that must be optimized by exhaustive enumeration for each comparison. The classic example is a measure of 3D similarity that pairs each atom in the query with an atom from the structure in the database. In the general case, all possible pairings must be tried through an exhaustive enumeration.
I tend to think the authors of the article are refering to the problems of a "useable form" for the structures and easy access of many of these databases. The first problem is mearly a problem of converting between the various structural file formats out there, something a good programmer (or grad student) can solve is a few weeks or less. The second is a bureaucrat issue and not a scientific one.
The problem isn't that it takes a while to find new stuff. The problem is the barriers to entry are so high that sufficient competition can't take place, hence there is no pressure to work quickly. Basically the medical industry is *not* a free market.
Now, I don't think the barriers need to be removed, because most of the high barrier is to ensure that treatments are effective without nasty side effects. About the only part of the barrier I can see being removed is somehow changing the liability laws, but I don't know what would be acceptable.
"There are a dozen opinions on a matter until you know the truth. Then there is only one." - CS Lewis (paraprhase)
Except the barriers to entry are mostly not regulatory in nature. As with most advanced R&D-based industries, the barriers are brainpower and equipment. There's plenty of capital out there to handle the hit-and-miss nature of drug design, and the regulatory restrictions on drug production and marketing are not barriers to entry for research.
IMO, what is truly limiting the pharma industry is profit incentive. Big pharma researches the things that will make them the most money -- which, BTW, are not cures for diseases, but rather treatments for conditions.
The 'competition' you speak of has nothing to do with R&D of new drugs. Barriers to entry prevent new entrants from producing and selling a commodity good, and new drugs are by no means commodities (patents have a lot to do with that). If you're talking about R&D as a commodity, that's a whole different discussion -- but again, it's brainpower and equipment that are the limiting factors causing the barriers to entry.
As for incentive to work quickly, that is not the case. There is definitely an incentive to work quickly as there is competition from all the big companies -- look at the COX2 inhibitors that were all the rage as low-side effect NSAIDS a couple years ago until certain really bad interactions manifested. Merck, Schering-Plough, everybody was in the game when the new sub-class was discovered. It was literally a rush to market, which is why the adverse effects weren't recognized until post-phase 4 trials.
"Trolls they were, but filled with the evil will of their master: a fell race..." -- J.R.R. Tolkien on Olog-hai
Although the crystal structure is not the same as the structure in solution, it can't be that far off.
:) Only joking, you may be right. I don't work on drug design, only backbone structure.
Crystals are pretty watery, much like the cell. Unless packing contacts are altering the active site, they are unlikely to be much different.
Also, the bulk of the structure is there to keep the active site residues in a particular orientation.
Perhaps management vitriol was partially justified?
Great for robot AI technology. With a couple cameras and some laser equipment, get a good 3D representation of what it's looking at, then run it through the list and find a match.