I'm sitting at my computer, playing a game. It's not a typical game: I'm using human spatial reasoning and puzzle-solving know-how to manipulate and shape virtual proteins.
The game—FoldIt—is an exercise in molecular origami. I use my mouse to tug and twist at a backbone of mottled greens, browns, oranges and reds on my screen, each color representing the properties of a particular region of the protein. Side chains, chemical pendants that make the protein’s building blocks unique, hang off the main backbone like charms on a bracelet.
Proteins are long chains of building blocks called amino acids, the specific number and arrangement of which makes each protein—whether it makes up your hair or carries oxygen in your blood—unique. In the cell, proteins fold as they are assembled, the chain (or backbone) of molecules twisting and kinking to make a structure that resembles a tangled Slinky. A protein's shape (or structure) determines what it does, where it goes, and the molecules with which it interacts.
At the moment I'm working on a poisonous protein produced by the funnel spider. The protein is clearly unhappy: unnaturally elongated, its color palate is more angry red than green, and four atoms have been flagged as too close to one another for comfort.
A few simple moves yield big dividends: From a starting score of 1,807, two quick keystrokes make the protein noticeably more compact. The atoms get their space, and the color palate has shifted toward green. My score now at 7,710, the current high score—8,649—seems within reach. Yet I'm at a loss of how to get there.
I have a PhD in cell and molecular biology from the University of Pennsylvania, but it's not enough. Frustrated, and with my player ranking at a dismal 430th out of 450, I give up.
Having a doctorate means I know how laborious and expensive it is to determine the correct structure for a given protein in the lab. A relatively short protein of, say 100 amino acids, could assume trillions of different shapes. Only one is correct—typically the one with the lowest energy. That's because, as University of Washington (U.W.) in Seattle biochemist David Baker explains it, a protein's structure is like a ball on a sloping floor: It will find its lowest energy state just as the ball will naturally roll to the surface's lowest point. Figuring out the "correct" shape of a given protein, then means finding the shape with the lowest energy level.
Baker came up with an automated way to do that: Rosetta@home. Like the popular SETI@home screen saver that is used to help sift out any signal from the cosmos that may be of intelligent origin, Rosetta harnesses processing power from idle computers around the world to predict protein shapes, twisting and bending chains to try to get to the minimum energy. Sometimes, the program makes rookie mistakes. Users saw them: "I'm watching what's going on on my computer, and these random moves the computer's making," Baker recalls hearing, "are often just silly."
A colleague, David Salesin, suggested converting Rosetta@home into an interactive game. He connected Baker with Zoran Popović, a computer scientist at U.W., who in turn passed the project to his graduate student, Seth Cooper, and postdoc Adrien Treuille. The first public beta was unveiled a year later.
Your challenge if you download the software: to pull, push, nudge and rotate the protein, represented as a three-dimensional, multicolored pipe, into its correct shape using tools such as pull and tweak, shake and wiggle. Each structure is assigned a score: the lower the energy level, the higher the score. Introductory exercises and in-game aides like "peekaboo," which compares top-scoring solutions with yours, help novices get up to speed.