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. Computational demonstrations include a full core design of the variable domains of the light and heavy chains of catalytic antibody 48G7 FAB with 74 residues and 10^(128) conformations, a full core/boundary design of the β1 domain of protein G with 25 residues and 10^(53) conformations, and a full surface design of the β1 domain of protein G with 27 residues and 10^(60) conformations. In addition, a full sequence design of the β1 domain of protein G is used to demonstrate the strong dependence of algorithm performance on the exact form of the potential function and the fidelity of the rotamer library. These results emphasize that search algorithm performance for protein design can only be meaningfully evaluated on physical models that have been subjected to experimental scrutiny. The new algorithm greatly facilitates ongoing efforts to engineer increasingly complex protein features.
['D. Benjamin Gordon', 'Geoffrey K. Hom', 'Stephen L. Mayo', 'Niles A. Pierce']
Exact rotamer optimization for protein design.