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Stefan Canzar, Nora C Toussaint, and Gunnar W Klau (2011)

An exact algorithm for side-chain placement in protein design

Optimization Letters:1-14.

Computational protein design aims at constructing novel or im- proved functions on the structure of a given protein backbone and has im- portant applications in the pharmaceutical and biotechnical industry. The underlying combinatorial side-chain placement problem consists of choosing a side-chain placement for each residue position such that the resulting over- all energy is minimum. The choice of the side-chain then also determines the amino acid for this position. Many algorithms for this NP-hard problem have been proposed in the context of homology modeling, which, however, reach their limits when faced with large protein design instances. In this paper, we propose a new exact method for the side-chain placement problem that works well even for large instance sizes as they appear in protein design. Our main contribution is a dedicated branch-and-bound algorithm that combines tight upper and lower bounds resulting from a novel Lagrangian relaxation approach for side-chain placement. Our experimental results show that our method outperforms alternative state-of-the-art exact approaches and makes it possible to solve large protein design instances.
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