This notebook contains material from PyRosetta; content is available on Github.

Packing & Design

Rosetta uses a Monte Carlo optimization routine to pack side chains using a library of conformations, or rotamers. This operation can be used for side-chain packing for operations like refinement or for designing optimal sequences. This workshop will examine both capabilities.

We will also cover many more ways to do protein design within Rosetta including parametric, denovo, and hydrogen-bond based design. All of these can be useful tools for protein engineering.

Suggested readings

  1. J. Desmet et al., “The dead-end elimination theorem and its use in protein side-chain positioning,” Nature 356, 539-543 (1992).
  2. B. Kuhlman & D. Baker, “Native protein structures are close to optimal for their structures,” PNAS 97, 10383, 2000.
  3. Denovo paper
  4. HbNet
  5. Andrew's packing paper
  6. Denovo design
  7. Parametric design paper
In [ ]:

Chapter contributors:

  • Jared Adolf-Bryfogle (Scripps; Institute for Protein Innovation)
  • Jason C. Klima (University of Washington; Lyell Immunopharma)
  • Jack Maguire (University of North Carolina)
  • Kathy Le (Johns Hopkins University); parts of this chapter were adapted from the PyRosetta book (J. J. Gray, S. Chaudhury, S. Lyskov, J. Labonte).