Identification and Analysis of Natural Building Blocks for Evolution-Guided 
Fragment-Based Protein Design

Ferruz, N; Lobos, F; Lemm, D; Toledo-Patino, S; Farías-Rico, JA; Schmidt, S; Höcker, B

doi:10.1016/j.jmb.2020.04.013

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Identification and Analysis of Natural Building Blocks for Evolution-Guided Fragment-Based Protein Design

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Lobos, F
Research Group Protein Design, Max Planck Institute for Developmental Biology, Max Planck Society;

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Toledo-Patino, S
Research Group Protein Design, Max Planck Institute for Developmental Biology, Max Planck Society;

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Farías-Rico, JA
Department Protein Evolution, Max Planck Institute for Developmental Biology, Max Planck Society;

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Schmidt, S
Department Biochemistry, Max Planck Institute for Developmental Biology, Max Planck Society;

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Höcker, B
Research Group Protein Design, Max Planck Institute for Developmental Biology, Max Planck Society;

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Citation

Ferruz, N., Lobos, F., Lemm, D., Toledo-Patino, S., Farías-Rico, J., Schmidt, S., et al. (2020). Identification and Analysis of Natural Building Blocks for Evolution-Guided Fragment-Based Protein Design. Journal of Molecular Biology, 432, 3898-3914. doi:10.1016/j.jmb.2020.04.013.

Cite as: https://hdl.handle.net/21.11116/0000-000A-5B3B-F

Abstract

Natural evolution has generated an impressively diverse protein universe via duplication and recombination from a set of protein fragments that served as building blocks. The application of these concepts to the design of new proteins using subdomain-sized fragments from different folds has proven to be experimentally successful. To better understand how evolution has shaped our protein universe, we performed an all-against-all comparison of protein domains representing all naturally existing folds and identified conserved homologous protein fragments. Overall, we found more than 1000 protein fragments of various lengths among different folds through similarity network analysis. These fragments are present in very different protein environments and represent versatile building blocks for protein design. These data are available in our web server called F(old P)uzzle (fuzzle.uni-bayreuth.de), which allows to individually filter the dataset and create customized networks for folds of interest. We believe that our results serve as an invaluable resource for structural and evolutionary biologists and as raw material for the design of custom-made proteins.