7Q3J

Computationally designed thioredoxin subjected to stability optimizing mutations.

Summary for 7Q3J

• Entry DOI: 10.2210/pdb7q3j/pdb
• Related: 5j7d
• Descriptor: MM9, GLYCEROL (3 entities in total)
• Functional Keywords: de-novo protein design, deep mutational scanning, stability, screening, de novo protein
• Biological source: synthetic construct
• Total number of polymer chains: 2
• Total formula weight: 26939.01

Authors

Norrild, R.K.,Johansson, K.E.,O'Shea, C.,Lindorff-Larsen, K.,Winther, J.R.,Morth, J.P. (deposition date: 2021-10-27, release date: 2022-11-16, Last modification date: 2024-02-07)

Primary citation

Norrild, R.K.,Johansson, K.E.,O'Shea, C.,Morth, J.P.,Lindorff-Larsen, K.,Winther, J.R.
Increasing protein stability by inferring substitution effects from high-throughput experiments.
Cell Rep Methods, 2:100333-100333, 2022

PubMed 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 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.

PubMed: 36452862
DOI: 10.1016/j.crmeth.2022.100333

Experimental method

X-RAY DIFFRACTION (1.9 Å)