Another way to use computers to translate dna sequences into protein structures is to work directly from a growing library of known folds. I decided to tackle the problem differently, from a taxonometric perspective. However, because entirely different dna sequences may produce structures of similar topology, large uncertainties remain. Head-Gordon's goal is to find, within the range of possibilities, the protein structure corresponding to a specific sequence that has the lowest energy. Repeated perturbations of amino-acid positions use gospel to lower the energy further, homing in on the lowest possible total energy.
Global optimization is a voracious consumer of computer power and time.
In the case of 1pou, for example, a dna binding protein with 72 amino acids arranged as several alpha helices, the structure predicted by gospel from sequence gave a reasonable estimate of the fold but had some six percent higher binding energy than the known structure derived from nuclear magnetic resonance imaging. Proteins are like strings of beads wound into bundles. Their structure is described at increasingly intricate levels. Secondary structure results from the angles between amino acids, plus the hydrogen bonds that may form from one residue to another. Tertiary structures are made from helices, sheets, and other secondary elements.