Global analysis of multi-mutants to improve protein function

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Global analysis of multi-mutants to improve protein function. / Johansson, Kristoffer E; Lindorff-Larsen, Kresten; Winther, Jakob R.

I: Journal of Molecular Biology, Bind 435, Nr. 8, 168034, 2023.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Johansson, KE, Lindorff-Larsen, K & Winther, JR 2023, 'Global analysis of multi-mutants to improve protein function', Journal of Molecular Biology, bind 435, nr. 8, 168034. https://doi.org/10.1016/j.jmb.2023.168034

APA

Johansson, K. E., Lindorff-Larsen, K., & Winther, J. R. (2023). Global analysis of multi-mutants to improve protein function. Journal of Molecular Biology, 435(8), [168034]. https://doi.org/10.1016/j.jmb.2023.168034

Vancouver

Johansson KE, Lindorff-Larsen K, Winther JR. Global analysis of multi-mutants to improve protein function. Journal of Molecular Biology. 2023;435(8). 168034. https://doi.org/10.1016/j.jmb.2023.168034

Author

Johansson, Kristoffer E ; Lindorff-Larsen, Kresten ; Winther, Jakob R. / Global analysis of multi-mutants to improve protein function. I: Journal of Molecular Biology. 2023 ; Bind 435, Nr. 8.

Bibtex

@article{24457712b96d4bbe8bbcf9ba38227996,

title = "Global analysis of multi-mutants to improve protein function",

abstract = "The identification of amino acid substitutions that both enhance the stability and function of a protein is a key challenge in protein engineering. Technological advances have enabled assaying thousands of protein variants in a single high-throughput experiment, and more recent studies use such data in protein engineering. We present a Global Multi-Mutant Analysis (GMMA) that exploits the presence of multiply-substituted variants to identify individual amino acid substitutions that are beneficial for the stability and function across a large library of protein variants. We have applied GMMA to a previously published experiment reporting on >54,000 variants of green fluorescent protein (GFP), each with known fluorescence output, and each carrying 1-15 amino acid substitutions (Sarkisyan et al., 2016). The GMMA method achieves a good fit to this dataset while being analytically transparent. We show experimentally that the six top-ranking substitutions progressively enhance GFP. More broadly, using only a single experiment as input our analysis recovers nearly all the substitutions previously reported to be beneficial for GFP folding and function. In conclusion, we suggest that large libraries of multiply-substituted variants may provide a unique source of information for protein engineering.",

author = "Johansson, {Kristoffer E} and Kresten Lindorff-Larsen and Winther, {Jakob R}",

year = "2023",

doi = "10.1016/j.jmb.2023.168034",

language = "English",

volume = "435",

journal = "Journal of Molecular Biology",

issn = "0022-2836",

publisher = "Academic Press",

number = "8",

}

RIS

TY - JOUR

T1 - Global analysis of multi-mutants to improve protein function

AU - Johansson, Kristoffer E

AU - Lindorff-Larsen, Kresten

AU - Winther, Jakob R

PY - 2023

Y1 - 2023

N2 - The identification of amino acid substitutions that both enhance the stability and function of a protein is a key challenge in protein engineering. Technological advances have enabled assaying thousands of protein variants in a single high-throughput experiment, and more recent studies use such data in protein engineering. We present a Global Multi-Mutant Analysis (GMMA) that exploits the presence of multiply-substituted variants to identify individual amino acid substitutions that are beneficial for the stability and function across a large library of protein variants. We have applied GMMA to a previously published experiment reporting on >54,000 variants of green fluorescent protein (GFP), each with known fluorescence output, and each carrying 1-15 amino acid substitutions (Sarkisyan et al., 2016). The GMMA method achieves a good fit to this dataset while being analytically transparent. We show experimentally that the six top-ranking substitutions progressively enhance GFP. More broadly, using only a single experiment as input our analysis recovers nearly all the substitutions previously reported to be beneficial for GFP folding and function. In conclusion, we suggest that large libraries of multiply-substituted variants may provide a unique source of information for protein engineering.

AB - The identification of amino acid substitutions that both enhance the stability and function of a protein is a key challenge in protein engineering. Technological advances have enabled assaying thousands of protein variants in a single high-throughput experiment, and more recent studies use such data in protein engineering. We present a Global Multi-Mutant Analysis (GMMA) that exploits the presence of multiply-substituted variants to identify individual amino acid substitutions that are beneficial for the stability and function across a large library of protein variants. We have applied GMMA to a previously published experiment reporting on >54,000 variants of green fluorescent protein (GFP), each with known fluorescence output, and each carrying 1-15 amino acid substitutions (Sarkisyan et al., 2016). The GMMA method achieves a good fit to this dataset while being analytically transparent. We show experimentally that the six top-ranking substitutions progressively enhance GFP. More broadly, using only a single experiment as input our analysis recovers nearly all the substitutions previously reported to be beneficial for GFP folding and function. In conclusion, we suggest that large libraries of multiply-substituted variants may provide a unique source of information for protein engineering.

U2 - 10.1016/j.jmb.2023.168034

DO - 10.1016/j.jmb.2023.168034

M3 - Journal article

C2 - 36863661

VL - 435

JO - Journal of Molecular Biology

JF - Journal of Molecular Biology

SN - 0022-2836

IS - 8

M1 - 168034

ER -

ID: 337986347

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