An affinity-based scoring scheme for predicting DNA-binding activities of modularly assembled zinc-finger proteins

Jeffry D. Sander, Peter Zaback, J. Keith Joung, Daniel F. Voytas, Drena Dobbs

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

Zinc-finger proteins (ZFPs) have long been recognized for their potential to manipulate genetic information because they can be engineered to bind novel DNA targets. Individual zinc-finger domains (ZFDs) bind specific DNA triplet sequences; their apparent modularity has led some groups to propose methods that allow virtually any desired DNA motif to be targeted in vitro. In practice, however, ZFPs engineered using this 'modular assembly' approach do not always function well in vivo. Here we report a modular assembly scoring strategy that both identifies combinations of modules least likely to function efficiently in vivo and provides accurate estimates of their relative binding affinities in vitro. Predicted binding affinities for 53 'three-finger' ZFPs, computed based on energy contributions of the constituent modules, were highly correlated (r = 0.80) with activity levels measured in bacterial two-hybrid assays. Moreover, Kd values for seven modularly assembled ZFPs and their intended targets, measured using fluorescence anisotropy, were also highly correlated with predictions (r = 0.91). We propose that success rates for ZFP modular assembly can be significantly improved by exploiting the score-based strategy described here.

Original languageEnglish (US)
Pages (from-to)506-515
Number of pages10
JournalNucleic acids research
Volume37
Issue number2
DOIs
StatePublished - 2009

Bibliographical note

Funding Information:
National Institutes of Health (GM066387 to D.D.); National Science Foundation (DBI0501678 to D.F.V.); National Institutes of Health (GM069906 and GM078369 to J.K.J.); and graduate research assistantships provided by United States Department of Agriculture (MGET 2001-52100-11506, NSF IGERT0504304 and ISU’s Center for Integrated Animal Genomics (CIAG). Funding for open access charge: National Science Foundation (DBI0501678).

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