Restricted dead-end elimination: protein redesign with a bounded number of residue mutations.

Dead-end elimination (DEE) has emerged as a powerful structure-based, conformational search technique enabling computational protein redesign. Given a protein with n mutable residues, the DEE criteria guide the search toward identifying the sequence of amino acids with the global minimum energy conformation (GMEC). This approach does not restrict the number of permitted mutations and allows the identified GMEC to differ from the original sequence in up to n residues. In practice, redesigns containing a large number of mutations are often problematic when taken into the wet-lab for creation via site-directed mutagenesis. The large number of point mutations required for the redesigns makes the process difficult, and increases the risk of major unpredicted and undesirable conformational changes. Preselecting a limited subset of mutable residues is not a satisfactory solution because it is unclear how to select this set before the search has been performed. Therefore, the ideal approach is what we define as the kappa-restricted redesign problem in which any kappa of the n residues are allowed to mutate. We introduce restricted dead-end elimination (rDEE) as a solution of choice to efficiently identify the GMEC of the restricted redesign (the kappaGMEC). Whereas existing approaches require n-choose-kappa individual runs to identify the kappaGMEC, the rDEE criteria can perform the redesign in a single search. We derive a number of extensions to rDEE and present a restricted form of the A* conformation search. We also demonstrate a 10-fold speed-up of rDEE over traditional DEE approaches on three different experimental systems. 2009 Wiley Periodicals, Inc.