Form Follows Sequence

Form Follows Sequence

Ever since James Watson and Francis Crick solved the double helix structure of dna in 1953, biology's most formidable structural challenge has been the "protein folding problem" - learning how nature gets from a gene, a length of dna that encodes the order of amino-acid residues in a string, to a working protein, that same string intricately folded into all the pockets and creases and knobs essential to the physics and chemistry of life.

While protein structures are being collected at a steadily increasing pace, knowledge of gene sequences is exploding. The Human Genome Project, begun by the Department of Energy and the National Institutes of Health less than ten years ago, have finished a draft of all 50,000 to 100,000 human genes - all three billion base-pairs. The majority of the proteins these myriad genes code for do not resemble any already known.

"The more information you have, the more kinds of information you need to make sense of it," says Daniel Rokhsar, head of the Computational and Theoretical Biology Department in the Lab's Physical Biosciences Division and a professor of physics at the University of California at Berkeley. "Without a simultaneous explosion in computation-powerful computers and flexible programs-we'll be overwhelmed."

The Garden of Converging Paths

One way to test ideas about how proteins fold is to start with a shape smaller and less intricate than most proteins, made from units less complicated than amino acids. Supercomputers simulate the behavior of model polymers, which in their native structure-analogous to the thermodynamically stable conformation of a fully folded protein-resemble jungle gyms made from Tinker-Toy-like sticks and balls.

Instead of the varying angles between amino-acid residues in a real protein, the stick-and-ball units, or mers, in a lattice model bond to their neighborsonly at right angles or straight ahead; instead of a real amino acid's complex of properties, a mer can be assigned just a few.

"Lattice models aren't meant to model specific proteins," says Rokhsar, "but they give a good representation of certain aspects of real processes in manageable time." Using the Cray T3E at the National Energy Research Scientific Computing Center (nersc), Rokhsar and Vijay Pande, an assistant professor of chemistry at Stanford University, discovered unsuspected regularities in the folding pathways of model polymers.