A simple physical model for the prediction and design of protein-DNA interactions

TitleA simple physical model for the prediction and design of protein-DNA interactions
Publication TypeJournal Article
Year of Publication2004
AuthorsHavranek, J. J., Duarte C. M., & Baker D.
JournalJournal of molecular biology
Volume344
Issue1
Pagination59-70
Date Published2004 Nov 12
ISSN0022-2836
KeywordsAmino Acid Sequence, Amino Acids, Base Sequence, Binding Sites, Databases, Nucleic Acid, Databases, Protein, DNA, Endonucleases, Models, Molecular, Nucleic Acid Conformation, Primary Publication, Protein Conformation, Proteins, Thermodynamics, Zinc Fingers
Abstract

Protein-DNA interactions are crucial for many biological processes. Attempts to model these interactions have generally taken the form of amino acid-base recognition codes or purely sequence-based profile methods, which depend on the availability of extensive sequence and structural information for specific structural families, neglect side-chain conformational variability, and lack generality beyond the structural family used to train the model. Here, we take advantage of recent advances in rotamer-based protein design and the large number of structurally characterized protein-DNA complexes to develop and parameterize a simple physical model for protein-DNA interactions. The model shows considerable promise for redesigning amino acids at protein-DNA interfaces, as design calculations recover the amino acid residue identities and conformations at these interfaces with accuracies comparable to sequence recovery in globular proteins. The model shows promise also for predicting DNA-binding specificity for fixed protein sequences: native DNA sequences are selected correctly from pools of competing DNA substrates; however, incorporation of backbone movement will likely be required to improve performance in homology modeling applications. Interestingly, optimization of zinc finger protein amino acid sequences for high-affinity binding to specific DNA sequences results in proteins with little or no predicted specificity, suggesting that naturally occurring DNA-binding proteins are optimized for specificity rather than affinity. When combined with algorithms that optimize specificity directly, the simple computational model developed here should be useful for the engineering of proteins with novel DNA-binding specificities.

Alternate JournalJ. Mol. Biol.
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