Abstract
Computational grafting of target residues onto existing protein scaffolds is a powerful method for the design of proteins with novel function. In the grafting method side chain mutations are introduced into a preexisting protein scaffold to recreate a target functional motif. The success of this approach relies on two primary criteria: (1) the availability of compatible structural scaffolds, and (2) the introduction of mutations that do not affect the protein structure or stability. To identify compatible structural motifs we use the Erebus webserver, to search the protein data bank (PDB) for user-defined structural scaffolds. To identify potential design mutations we use the Eris webserver, which accurately predicts changes in protein stability resulting from mutations. Mutations that increase the protein stability are more likely to maintain the protein structure and therefore produce the desired function. Together these tools provide effective methods for identifying existing templates and guiding further design experiments. The software tools for scaffold searching and design are available at http://dokhlab.org.
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Acknowledgment
This work was supported by National Institutes of Health Awards R01GM080742 and R01AI102732.
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Zhu, C., Mowrey, D.D., Dokholyan, N.V. (2017). Computational Protein Design Through Grafting and Stabilization. In: Samish, I. (eds) Computational Protein Design. Methods in Molecular Biology, vol 1529. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6637-0_11
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DOI: https://doi.org/10.1007/978-1-4939-6637-0_11
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