EteRNA is a project from Carnegie Melon University, and at first it might seem frivolous. The historical attempts to churn through the nearly infinitely complex problems involved in molecular folding have focused on computer power as the answer. SETI helped to pioneer this idea with a processor sharing scheme that let supporters offer up computer time for free.
The research community took the idea to another level with Folding@Home, a program now running on many PlayStation 3 consoles and passively sending results to researchers around the world. With so much computing power available, it seemed downright silly to turn to human beings as mathematical problem solvers.
And yet, this week CMU released research arguing that not only has there EteRNA produced results matching those of their specially designed folding machines, but that the humans are actually better. That’s not to say they’re faster, mind you; a problem that takes a powerful computer less than a minute to solve could vex a human for several days. The computer will take fewer false starts and produce an answer from reliable reasoning processes — and in the end produce answers that turn out to be far less accurate, when tested.
With more than 130,000 users, EteRNA seems to be able to leverage the incredible breadth of the human brain, a virtue that has never been more clearly distinct from its lackluster processing speed.
EteRNA is a simple game about designing RNA molecules: G pairs with C, A with T and U, and each of these combinations has a characteristic bonding strength. The interplay between these matches, and their relative strengths, lets players manipulate the molecular codes of example strands, seeing the effects in real-time.
For a research project, the game is very aesthetically pleasing, illustrating the changes in molecule shape with smooth animations and bright colors. Tasked with creating molecules with a very specific shape, players must adjust the A-C-U-G sequence (A-C-T-G in DNA) and let chemistry do the rest.
Refreshingly, this online exercise is verified with real lab work. Accuracy is measured by actually going out and building the molecules in question, building nucleic acids in the sequences suggested by both computers and players. Doing such testing returns some amazing results: the CMU researchers found that the human-made versions had a 99% chance to beat the algorithmically generated ones.
Amazingly, since these helpful players are so studious as to actually report their problem-solving workflows, the researchers were able to build new, human-inspired algorithms. The first of these, called EteRNAbot, can best the pre-EteRNA algorithms a cool 19 times out of 20.
Of course, the user base isn’t quite as ignorant as EteRNA might want you to believe. A good portion of the EteRNA players are grad students or professional researchers in related fields. Still, the main mechanism they found to explain the human advantage is in pattern recognition, a familiar refrain to those interested in the development of real artificial intelligence. Rather than deriving chemical principles from the many puzzles, people tended to key more on visual patterns. This is why the developers used a different primary color for each base type, and why the bases U and T are both blue (they bond to the same base, G).
The shape of RNA is important for a whole host of reasons. For one, we can directly affect the action of an RNA molecule by altering its shape; putting a troublesome gene in a locked hairpin turn should prevent it from being transcribed. Additionally, the shape of a molecule is what determines its method of action when interacting with an enzyme — or when acting as an enzyme itself. So-called “ribozymes” are becoming increasingly known, and their importance increasingly appreciated. The ability to fold and un-fold in different chemical conditions also makes nucleic acids quite useful, as it could pack down for efficient delivery through the body, uncurling into its final conformation only after entering the cell.