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Random Field Model Reveals Structure of the Protein Recombinational Landscape

Romero, Philip A. and Arnold, Frances H. (2012) Random Field Model Reveals Structure of the Protein Recombinational Landscape. PLoS Computational Biology, 8 (10). Art. No. e1002713. ISSN 1553-734X. PMCID PMC3464211. doi:10.1371/journal.pcbi.1002713.

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We are interested in how intragenic recombination contributes to the evolution of proteins and how this mechanism complements and enhances the diversity generated by random mutation. Experiments have revealed that proteins are highly tolerant to recombination with homologous sequences (mutation by recombination is conservative); more surprisingly, they have also shown that homologous sequence fragments make largely additive contributions to biophysical properties such as stability. Here, we develop a random field model to describe the statistical features of the subset of protein space accessible by recombination, which we refer to as the recombinational landscape. This model shows quantitative agreement with experimental results compiled from eight libraries of proteins that were generated by recombining gene fragments from homologous proteins. The model reveals a recombinational landscape that is highly enriched in functional sequences, with properties dominated by a large-scale additive structure. It also quantifies the relative contributions of parent sequence identity, crossover locations, and protein fold to the tolerance of proteins to recombination. Intragenic recombination explores a unique subset of sequence space that promotes rapid molecular diversification and functional adaptation.

Item Type:Article
Related URLs:
URLURL TypeDescription DOIArticle CentralArticle
Romero, Philip A.0000-0002-2586-7263
Arnold, Frances H.0000-0002-4027-364X
Additional Information:© 2012 Romero, Arnold. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Received June 5, 2012; Accepted August 3, 2012; Published October 4, 2012. Funding: The authors acknowledge support from the National Institutes of Health, ARRA (grant R01 GM068664) for funding the theoretical and P450 chimera work, and the U.S. Army Research Office, Institute for Collaborative Biotechnologies (grant W911NF-09-D-0001) for funding design and construction of the cellulase libraries. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank Zhen-Gang Wang and M. Shum for helpful discussions, and D. A. Drummond for feedback on the manuscript. Author Contributions: Analyzed the data: PAR FHA. Wrote the paper: PAR FHA.
Funding AgencyGrant Number
NIHR01 GM068664-01
Army Research Office (ARO)W911NF-09-D-0001
Issue or Number:10
PubMed Central ID:PMC3464211
Record Number:CaltechAUTHORS:20130220-094932746
Persistent URL:
Official Citation:omero PA, Arnold FH (2012) Random Field Model Reveals Structure of the Protein Recombinational Landscape. PLoS Comput Biol 8(10): e1002713. doi:10.1371/journal.pcbi.1002713
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:37014
Deposited By: Tony Diaz
Deposited On:22 Feb 2013 23:55
Last Modified:09 Nov 2021 23:26

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