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Protein design automation

Dahiyat, Bassil I. and Mayo, Stephen L. (1996) Protein design automation. Protein Science, 5 (5). pp. 895-903. ISSN 0961-8368. PMCID PMC2143401. doi:10.1002/pro.5560050511.

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We have conceived and implemented a cyclical protein design strategy that couples theory, computation, and experimental testing. The combinatorially large number of possible sequences and the incomplete understanding of the factors that control protein structure are the primary obstacles in protein design. Our protein design automation algorithm objectively predicts protein sequences likely to achieve a desired fold. Using a rotamer description of the side chains, we implemented a fast discrete search algorithm based on the Dead-End Elimination Theorem to rapidly find the globally optimal sequence in its optimal geometry from the vast number of possible solutions. Rotamer sequences were scored for steric complementarity using a van der Waals potential. A Monte Carlo search was then executed, starting at the optimal sequence, in order to find other high-scoring sequences. As a test of the design methodology, high-scoring sequences were found for the buried hydrophobic residues of a homodimeric coiled coil based on GCN4-p1. The corresponding peptides were synthesized and characterized by CD spectroscopy and size-exclusion chromatography. All peptides were dimeric and nearly 100% helical at 1 °C, with melting temperatures ranging from 24 °C to 57 °C. A quantitative structure activity relation analysis was performed on the designed peptides, and a significant correlation was found with surface area burial. Incorporation of a buried surface area potential in the scoring of sequences greatly improved the correlation between predicted and measured stabilities and demonstrated experimental feedback in a complete design cycle.

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URLURL TypeDescription CentralArticle
Mayo, Stephen L.0000-0002-9785-5018
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Additional Information:© 1996 The Protein Society. Received December 5, 1995; Accepted February 7, 1996. Article first published online: 31 Dec. 2008. We thank J. Desmet and M. De Maeyer for providing us with their rotamer library and a manuscript before publication; P.J. Bjorkman, J. Holton, E.M. Marzluff, D.B. Gordon, and D.C. Rees for critical comments on the manuscript; and B.D. Olafson for help with partial atomic charges and critical comments on the manuscript. This work was supported by the Rita Allen Foundation, the Chandler Family Trust, the Booth Ferris Foundation, the David and Lucile Packard Foundation, and the Searle Scholars Program/The Chicago Community Trust. B.I.D. is partially supported by NIH training grant GM 08346.
Funding AgencyGrant Number
Rita Allen FoundationUNSPECIFIED
Chandler Family TrustUNSPECIFIED
Booth Ferris FoundationUNSPECIFIED
David and Lucile Packard FoundationUNSPECIFIED
Searle Scholars ProgramUNSPECIFIED
Chicago Community TrustUNSPECIFIED
NIH Predoctoral FellowshipGM 08346
Subject Keywords:Circular Dichroism; Viral Proteins; Structure-Activity Relationship; Amino Acid Sequence; Proteins; DNA-Binding Proteins; Computer-Aided Design; Feedback; Protein Conformation; Monte Carlo Method; Repressor Proteins; Computer Simulation; Viral Regulatory and Accessory Proteins; Algorithms; Molecular Sequence Data; computational; dead-end elimination; packing; proteindesign; sidechain
Issue or Number:5
PubMed Central ID:PMC2143401
Record Number:CaltechAUTHORS:20110620-160429268
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Official Citation:Dahiyat, B. I. and Mayo, S. L. (1996), Protein design automation. Protein Science, 5: 895–903. doi: 10.1002/pro.5560050511
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:24099
Deposited By: Marie Ary
Deposited On:28 Sep 2011 20:51
Last Modified:09 Nov 2021 16:20

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