<div><p>Computational design has been used with mixed success for the design of protein surfaces, with directed evolution heretofore providing better practical solutions than explicit design. Directed evolution, however, requires a tractable high-throughput screen because the random nature of mutation does not enrich for desired traits. Here we demonstrate the successful design of the β-sheet surface of a red fluorescent protein (RFP), enabling control over its oligomerization. To isolate the problem of surface design, we created a hybrid RFP from DsRed and mCherry with a stabilized protein core that allows for monomerization without loss of fluorescence. We designed an explicit library for which 93 of 96 (97%) of the protein variants are s...
The use of unnatural fluorogenic molecules widely expands the pallet of available genetically encode...
Red fluorescent proteins (RFPs) derived from organisms in the class Anthozoa have found widespread a...
Protein engineering involves generating and screening large numbers of variants for desired properti...
Computational design has been used with mixed success for the design of protein surfaces, with direc...
Computational design has been used with mixed success for the design of protein surfaces, with direc...
Fluorescent proteins (FPs) have, over the last two decades, revolutionized the way biology and bio...
Red fluorescent proteins (RFPs) have attracted significant engineering focus because of the promise ...
Red fluorescent proteins (RFPs) are used extensively in chemical biology research as fluorophores fo...
Monomeric red fluorescent proteins (RFPs) are used extensively for applications in molecular biology...
Fluorescent proteins (FPs) are used as genetic labels to study processes in live cells by using fluo...
The research comprising this thesis is presented in three chapters divided into two parts. Part One,...
Fluorescent proteins are intrinsically fluorescent, genetically encodable tags that can be expressed...
Anthozoa-class red fluorescent proteins (RFPs) are frequently used as biological markers, with far-r...
One of the greatest tools to study the complicated cellular machinery at the micro- and nanometer sc...
We characterize computationally a red fluorescent protein (RFP) with the chromophore (Chro) sandwich...
The use of unnatural fluorogenic molecules widely expands the pallet of available genetically encode...
Red fluorescent proteins (RFPs) derived from organisms in the class Anthozoa have found widespread a...
Protein engineering involves generating and screening large numbers of variants for desired properti...
Computational design has been used with mixed success for the design of protein surfaces, with direc...
Computational design has been used with mixed success for the design of protein surfaces, with direc...
Fluorescent proteins (FPs) have, over the last two decades, revolutionized the way biology and bio...
Red fluorescent proteins (RFPs) have attracted significant engineering focus because of the promise ...
Red fluorescent proteins (RFPs) are used extensively in chemical biology research as fluorophores fo...
Monomeric red fluorescent proteins (RFPs) are used extensively for applications in molecular biology...
Fluorescent proteins (FPs) are used as genetic labels to study processes in live cells by using fluo...
The research comprising this thesis is presented in three chapters divided into two parts. Part One,...
Fluorescent proteins are intrinsically fluorescent, genetically encodable tags that can be expressed...
Anthozoa-class red fluorescent proteins (RFPs) are frequently used as biological markers, with far-r...
One of the greatest tools to study the complicated cellular machinery at the micro- and nanometer sc...
We characterize computationally a red fluorescent protein (RFP) with the chromophore (Chro) sandwich...
The use of unnatural fluorogenic molecules widely expands the pallet of available genetically encode...
Red fluorescent proteins (RFPs) derived from organisms in the class Anthozoa have found widespread a...
Protein engineering involves generating and screening large numbers of variants for desired properti...