Full-sequence computational design and solution structure of a thermostable protein variant.

Computational protein design procedures were applied to the redesign of the entire sequence of a 51 amino acid residue protein, Drosophila melanogaster engrailed homeodomain. Various sequence optimization algorithms were compared and two resulting designed sequences were experimentally evaluated. The two sequences differ by 11 mutations and share 22% and 24% sequence identity with the wild-type protein.

A search algorithm for fixed-composition protein design.

We present a computational protein design algorithm for finding low-energy sequences of fixed amino acid composition. The search algorithms used in protein design typically do not restrict amino acid composition. However, the random energy model of Shakhnovich suggests that the use of fixed-composition sequences may circumvent defects in the modeling of the denatured state.

Dioxane contributes to the altered conformation and oligomerization state of a designed engrailed homeodomain variant.

Our goal was to compute a stable, full-sequence design of the Drosophila melanogaster engrailed homeodomain. Thermal and chemical denaturation data indicated the design was significantly more stable than was the wild-type protein. The data were also nearly identical to those for a similar, later full-sequence design, which was shown by NMR to adopt the homeodomain fold: a three-helix, globular monomer.

Preprocessing of rotamers for protein design calculations.

We have developed a process that significantly reduces the number of rotamers in computational protein design calculations. This process, which we call Vegas, results in dramatic computational performance increases when used with algorithms based on the dead-end elimination (DEE) theorem. Vegas estimates the energy of each rotamer at each position by fixing each rotamer in turn and utilizing various search algorithms to optimize the remaining positions.

Exact rotamer optimization for protein design.

Computational methods play a central role in the rational design of novel proteins. The present work describes a new hybrid exact rotamer optimization (HERO) method that builds on previous dead-end elimination algorithms to yield dramatic performance enhancements. Measured on experimentally validated physical models, these improvements make it possible to perform previously intractable designs of entire protein core, surface, or boundary regions.