2020
DOI: 10.1093/nar/gkaa291
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The geometric influence on the Cys2His2 zinc finger domain and functional plasticity

Abstract: The Cys2His2 zinc finger is the most common DNA-binding domain expanding in metazoans since the fungi human split. A proposed catalyst for this expansion is an arms race to silence transposable elements yet it remains poorly understood how this domain is able to evolve the required specificities. Likewise, models of its DNA binding specificity remain error prone due to a lack of understanding of how adjacent fingers influence each other's binding specificity. Here, we use a synthetic approach to exhaustively i… Show more

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Cited by 5 publications
(10 citation statements)
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“…2b ). Previous work has shown that recovery of helical strategies in one library versus another is indicative of activity only in the recovered contexts, rather than sampling influences 35 . In addition, because different library contexts present different structural influences at the overlap, we investigated the physical influences that might lead to the selection of a particular type of ZF in a specific library context.…”
Section: Resultsmentioning
confidence: 99%
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“…2b ). Previous work has shown that recovery of helical strategies in one library versus another is indicative of activity only in the recovered contexts, rather than sampling influences 35 . In addition, because different library contexts present different structural influences at the overlap, we investigated the physical influences that might lead to the selection of a particular type of ZF in a specific library context.…”
Section: Resultsmentioning
confidence: 99%
“…We sought to compare ZFDesign with a baseline, but no previous model has explicitly attempted to perform full ZF-array design for a given target and with only a few collections of ZFs available. However, previous models designed to capture ZF binding specificity exist and can be adapted to design ZFs for given targets; we used ZFpred, a recently developed method that outperformed previous models 35 . We then used both ZFDesign and ZFpred to generate ZF sequences to target 6-mers from our test dataset.…”
Section: Resultsmentioning
confidence: 99%
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“…In recent years, research on the formation mechanism of metal–amino acid–nucleoside ternary compounds facilitate the in-depth understanding of aptamer–protein chelation mediated by metal ions. Metal ions can be contained in proteins or aptamers, driving the metal chelation between aptamers and proteins to promote their binding. , Thus, a series of analytical strategies based on metal chelation have been established for biomolecular detection. The zinc finger structure is a Zn 2+ -dependent folded finger-like domain. , Proteins with zinc finger structures (zinc-finger proteins) are usually functional proteins involved in the regulation of gene expression. , For instance, as a key biomarker of human immunodeficiency virus type 1 (HIV-1), nucleocapsid protein 7 (NCp7) contains two zinc-finger structures and plays a critical role in viral reverse transcription. , To achieve high-sensitivity detection of NCp7, an aptamer tightly bound to NCp7 was developed, and their interaction was found to be strongly dependent on Zn 2+ . , Based on the specific interactions between NCp7 and its aptamer, Niedzwiecki et al combined the nanopore technique with the resistive-pulse technique for NCp7 quantification . With increasing concentrations of NCp7, the amplitude of current blockades enhanced proportionally, thus achieving highly sensitive detection of NCp7.…”
Section: Analytical Assays Based On the Regulation Of Aptamer–protein...mentioning
confidence: 99%
“…The zinc finger structure is a Zn 2+ -dependent folded finger-like domain. 417,418 Proteins with zinc finger structures (zinc-finger proteins) are usually functional proteins involved in the regulation of gene expression. 419,420 For instance, as a key biomarker of human immunodeficiency virus type 1 (HIV-1), nucleocapsid protein 7 (NCp7) contains two zinc-finger structures and plays a critical role in viral reverse transcription.…”
Section: Detection Based On Other Interactionsmentioning
confidence: 99%