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Natural-like function in artificial WW domains

Nature volume 437, pages 579–583 (2005)Cite this article

Abstract

Protein sequences evolve through random mutagenesis with selection for optimal fitness1. Cooperative folding into a stable tertiary structure is one aspect of fitness, but evolutionary selection ultimately operates on function, not on structure. In the accompanying paper2, we proposed a model for the evolutionary constraint on a small protein interaction module (the WW domain) through application of the SCA, a statistical analysis of multiple sequence alignments3,4. Construction of artificial protein sequences directed only by the SCA showed that the information extracted by this analysis is sufficient to engineer the WW fold at atomic resolution. Here, we demonstrate that these artificial WW sequences function like their natural counterparts, showing class-specific recognition of proline-containing target peptides5,6,7,8. Consistent with SCA predictions, a distributed network of residues mediates functional specificity in WW domains. The ability to recapitulate natural-like function in designed sequences shows that a relatively small quantity of sequence information is sufficient to specify the global energetics of amino acid interactions.

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Figure 1: Statistical coupling analysis for the WW domain, a proline-binding protein interaction module.
Figure 2: Assays for binding affinity and specificity in WW domains.
Figure 3: A summary of functional measurements for all tested natural and artificial WW domains.
Figure 4: A spatially distributed network underlying WW function.

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Acknowledgements

We thank members of the Ranganathan laboratory for advice and critical review of the manuscript, J. P. Noel for providing the pHIS8 expression vector, and K. Voegler for contributing to this project. This study was supported by the Robert A. Welch foundation (R.R.), the Mallinckrodt Foundation Scholar Award (R.R.), NIH grants (M.B.Y.), and a Burroughs-Wellcome Career Development Award (M.B.Y.). D.M.L. was supported by a Howard Hughes Medical Institute pre-doctoral award. W.P.R. is an associate and R.R. is an investigator of the Howard Hughes Medical Institute.

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Authors and Affiliations

  1. Howard Hughes Medical Institute and Department of Pharmacology, University of Texas Southwestern Medical Center, Texas, 75390-9050, Dallas, USA

    William P. Russ, Prashant Mishra & Rama Ranganathan

  2. Center for Cancer Research, Department of Biology and Division of Biological Engineering, Massachusetts Institute of Technology, Massachusetts, 02139, Cambridge, USA

    Drew M. Lowery & Michael B. Yaffe

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Correspondence to Rama Ranganathan.

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Supplementary information

Supplementary Figure Legends

Text to accompany the below Supplementary Figures. (DOC 35 kb)

Supplementary Figure S1

Binding specificity assays determined by the oriented peptide library assay for (a) 28 natural WW domains and (b) 10 artificial WW domains designed using the SCA matrix. (PDF 1571 kb)

Supplementary Figure S2

Saturation mutagenesis of the peptide ligands for the two major functional classes of WW domains identified. (PDF 6239 kb)

Supplementary Figure S3

Thermodynamic double mutant cycles in the WW domain Nedd4.3 (N39), measuring the energetic coupling between the T28A mutant and mutants at three other sites within the network of co-evolving residues (L3A, E8A, and H23A). (PDF 272 kb)

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Russ, W., Lowery, D., Mishra, P. et al. Natural-like function in artificial WW domains. Nature 437, 579–583 (2005). https://doi.org/10.1038/nature03990

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