An exact algorithm for side-chain placement in protein design

Stefan Canzar, Nora C. Toussaint, Gunnar W. Klau

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Computational protein design aims at constructing novel or improved functions on the structure of a given protein backbone and has important applications in the pharmaceutical and biotechnical industry. The underlying combinatorial side-chain placement (SCP) problem consists of choosing a SCP for each residue position such that the resulting overall energy is minimum. The choice of the side-chain then also determines the amino acid for this position. Many algorithms for this N P-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 SCP 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 SCP. Our experimental results show that our method outperforms alternative state-of-the-art exact approaches and makes it possible to optimally solve large protein design instances routinely.

Original languageEnglish (US)
Pages (from-to)393-406
Number of pages14
JournalOptimization Letters
Issue number3
StatePublished - Aug 2011

All Science Journal Classification (ASJC) codes

  • Control and Optimization


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