Increasing protein stability by inferring substitution effects from high-throughput experiments

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Increasing protein stability by inferring substitution effects from high-throughput experiments. / Norrild, Rasmus Krogh; Johansson, Kristoffer Enøe; O'Shea, Charlotte; Morth, Jens Preben; Lindorff-Larsen, Kresten; Winther, Jakob Rahr.

In: Cell Reports Methods, Vol. 2, No. 11, 100333, 2022.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Norrild, RK, Johansson, KE, O'Shea, C, Morth, JP, Lindorff-Larsen, K & Winther, JR 2022, 'Increasing protein stability by inferring substitution effects from high-throughput experiments', Cell Reports Methods, vol. 2, no. 11, 100333. https://doi.org/10.1016/j.crmeth.2022.100333

APA

Norrild, R. K., Johansson, K. E., O'Shea, C., Morth, J. P., Lindorff-Larsen, K., & Winther, J. R. (2022). Increasing protein stability by inferring substitution effects from high-throughput experiments. Cell Reports Methods, 2(11), [100333]. https://doi.org/10.1016/j.crmeth.2022.100333

Vancouver

Norrild RK, Johansson KE, O'Shea C, Morth JP, Lindorff-Larsen K, Winther JR. Increasing protein stability by inferring substitution effects from high-throughput experiments. Cell Reports Methods. 2022;2(11). 100333. https://doi.org/10.1016/j.crmeth.2022.100333

Author

Norrild, Rasmus Krogh ; Johansson, Kristoffer Enøe ; O'Shea, Charlotte ; Morth, Jens Preben ; Lindorff-Larsen, Kresten ; Winther, Jakob Rahr. / Increasing protein stability by inferring substitution effects from high-throughput experiments. In: Cell Reports Methods. 2022 ; Vol. 2, No. 11.

Bibtex

@article{d2179ea7e9894c259c4068d4de3b1ca7,
title = "Increasing protein stability by inferring substitution effects from high-throughput experiments",
abstract = "We apply a computational model, global multi-mutant analysis (GMMA), to inform on effects of most amino acid substitutions from a randomly mutated gene library. Using a high mutation frequency, the method can determine mutations that increase the stability of even very stable proteins for which conventional selection systems have reached their limit. As a demonstration of this, we screened a mutant library of a highly stable and computationally redesigned model protein using an in vivo genetic sensor for folding and assigned a stability effect to 374 of 912 possible single amino acid substitutions. Combining the top 9 substitutions increased the unfolding energy 47 to 69 kJ/mol in a single engineering step. Crystal structures of stabilized variants showed small perturbations in helices 1 and 2, which rendered them closer in structure to the redesign template. This case study illustrates the capability of the method, which is applicable to any screen for protein function. ",
author = "Norrild, {Rasmus Krogh} and Johansson, {Kristoffer En{\o}e} and Charlotte O'Shea and Morth, {Jens Preben} and Kresten Lindorff-Larsen and Winther, {Jakob Rahr}",
note = "{\textcopyright} 2022 The Authors.",
year = "2022",
doi = "10.1016/j.crmeth.2022.100333",
language = "English",
volume = "2",
journal = "Cell Reports Methods",
issn = "2667-2375",
publisher = "Cell Press",
number = "11",

}

RIS

TY - JOUR

T1 - Increasing protein stability by inferring substitution effects from high-throughput experiments

AU - Norrild, Rasmus Krogh

AU - Johansson, Kristoffer Enøe

AU - O'Shea, Charlotte

AU - Morth, Jens Preben

AU - Lindorff-Larsen, Kresten

AU - Winther, Jakob Rahr

N1 - © 2022 The Authors.

PY - 2022

Y1 - 2022

N2 - We apply a computational model, global multi-mutant analysis (GMMA), to inform on effects of most amino acid substitutions from a randomly mutated gene library. Using a high mutation frequency, the method can determine mutations that increase the stability of even very stable proteins for which conventional selection systems have reached their limit. As a demonstration of this, we screened a mutant library of a highly stable and computationally redesigned model protein using an in vivo genetic sensor for folding and assigned a stability effect to 374 of 912 possible single amino acid substitutions. Combining the top 9 substitutions increased the unfolding energy 47 to 69 kJ/mol in a single engineering step. Crystal structures of stabilized variants showed small perturbations in helices 1 and 2, which rendered them closer in structure to the redesign template. This case study illustrates the capability of the method, which is applicable to any screen for protein function.

AB - We apply a computational model, global multi-mutant analysis (GMMA), to inform on effects of most amino acid substitutions from a randomly mutated gene library. Using a high mutation frequency, the method can determine mutations that increase the stability of even very stable proteins for which conventional selection systems have reached their limit. As a demonstration of this, we screened a mutant library of a highly stable and computationally redesigned model protein using an in vivo genetic sensor for folding and assigned a stability effect to 374 of 912 possible single amino acid substitutions. Combining the top 9 substitutions increased the unfolding energy 47 to 69 kJ/mol in a single engineering step. Crystal structures of stabilized variants showed small perturbations in helices 1 and 2, which rendered them closer in structure to the redesign template. This case study illustrates the capability of the method, which is applicable to any screen for protein function.

U2 - 10.1016/j.crmeth.2022.100333

DO - 10.1016/j.crmeth.2022.100333

M3 - Journal article

C2 - 36452862

VL - 2

JO - Cell Reports Methods

JF - Cell Reports Methods

SN - 2667-2375

IS - 11

M1 - 100333

ER -

ID: 327778325