2002
DOI: 10.1073/pnas.212627499
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Combining computational and experimental screening for rapid optimization of protein properties

Abstract: We present a combined computational and experimental method for the rapid optimization of proteins. Using ␤-lactamase as a test case, we redesigned the active site region using our Protein Design Automation technology as a computational screen to search the entire sequence space. By eliminating sequences incompatible with the protein fold, Protein Design Automation rapidly reduced the number of sequences to a size amenable to experimental screening, resulting in a library of Ϸ200,000 mutants. These were then c… Show more

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Cited by 105 publications
(92 citation statements)
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“…The application of random mutagenesis did not yield either one of the rational design variants rTK2 or rTK3. The result can be explained by the fact that an Arg104Gln change is possible by a single nucleotide substitution (CGA to CAA) while Arg104Met (CGA to ATG) requires simultaneous nucleotide changes in all three codon positions (29). Confronted with the possibility that alternative amino acid substitutions in these two residues could produce enzymes with tk activity, we applied site-saturation mutagenesis to completely randomize both positions.…”
Section: In Vitro Characterization Of Selected Dck Mutants From Randomentioning
confidence: 99%
“…The application of random mutagenesis did not yield either one of the rational design variants rTK2 or rTK3. The result can be explained by the fact that an Arg104Gln change is possible by a single nucleotide substitution (CGA to CAA) while Arg104Met (CGA to ATG) requires simultaneous nucleotide changes in all three codon positions (29). Confronted with the possibility that alternative amino acid substitutions in these two residues could produce enzymes with tk activity, we applied site-saturation mutagenesis to completely randomize both positions.…”
Section: In Vitro Characterization Of Selected Dck Mutants From Randomentioning
confidence: 99%
“…Although many algorithms have now been proposed to design such combinatorial libraries (7-9, 11, 12), few computationally designed libraries have been characterized experimentally (9,18,19), and, to our knowledge, there have been no controlled experiments comparing these methods with each other or with libraries of randomly generated sequence diversity. The results of such a comparison would be hard to predict, especially because none of these methods models protein function explicitly.…”
mentioning
confidence: 99%
“…The success of the semidirected library, which was based only on considerations of E6AP stability, suggests that enriching with well-folded sequences was the critical step for identifying binders. Computationally enriching for folded protein has similarly been shown to aid the selection of proteins with previously undescribed fluorescent properties and improved enzymatic activity (23,30,31).…”
Section: Discussionmentioning
confidence: 99%