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Experimental library screening demonstrates the successful application of computational protein design to large structural ensembles

Allen, Benjamin D. and Nisthal, Alex and Mayo, Stephen L. (2010) Experimental library screening demonstrates the successful application of computational protein design to large structural ensembles. Proceedings of the National Academy of Sciences of the United States of America, 107 (46). pp. 19838-19843. ISSN 0027-8424. http://resolver.caltech.edu/CaltechAUTHORS:20101213-150517069

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Abstract

The stability, activity, and solubility of a protein sequence are determined by a delicate balance of molecular interactions in a variety of conformational states. Even so, most computational protein design methods model sequences in the context of a single native conformation. Simulations that model the native state as an ensemble have been mostly neglected due to the lack of sufficiently powerful optimization algorithms for multistate design. Here, we have applied our multistate design algorithm to study the potential utility of various forms of input structural data for design. To facilitate a more thorough analysis, we developed new methods for the design and high-throughput stability determination of combinatorial mutation libraries based on protein design calculations. The application of these methods to the core design of a small model system produced many variants with improved thermodynamic stability and showed that multistate design methods can be readily applied to large structural ensembles. We found that exhaustive screening of our designed libraries helped to clarify several sources of simulation error that would have otherwise been difficult to ascertain. Interestingly, the lack of correlation between our simulated and experimentally measured stability values shows clearly that a design procedure need not reproduce experimental data exactly to achieve success. This surprising result suggests potentially fruitful directions for the improvement of computational protein design technology.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1073/pnas.1012985107 DOIUNSPECIFIED
http://www.pnas.org/content/107/46/19838.abstractPublisherUNSPECIFIED
Additional Information:© 2010 by the National Academy of Sciences. Contributed by Stephen L. Mayo, September 7, 2010 (sent for review April 20, 2010). Published online before print November 2, 2010. We thank Barry Olafson for preparation of the MD structural ensembles, Christina Vizcarra for the pInSALect plasmid, and Jost Vielmetter for useful discussions. This work was supported by the Howard Hughes Medical Institute, the Defense Advanced Research Projects Agency, and the National Security Science and Engineering Faculty Fellowship. Author contributions: B.D.A. and A.N. designed research; B.D.A. and A.N. performed research; B.D.A., A.N., and S.L.M. analyzed data; and B.D.A., A.N., and S.L.M. wrote the paper.
Funders:
Funding AgencyGrant Number
Howard Hughes Medical Institute UNSPECIFIED
Defense Advanced Research Projects Agency (DARPA)UNSPECIFIED
National Security Science and Engineering Faculty Fellowship UNSPECIFIED
Subject Keywords:protein engineering; high-throughput stability determination; library design; molecular dynamics; NMR ensemble
Record Number:CaltechAUTHORS:20101213-150517069
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20101213-150517069
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:21335
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:14 Dec 2010 20:18
Last Modified:26 Dec 2012 12:45

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