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- W4308981514 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." @default.
- W4308981514 created "2022-11-20" @default.
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- W4308981514 date "2022-11-01" @default.
- W4308981514 modified "2023-10-13" @default.
- W4308981514 title "Increasing protein stability by inferring substitution effects from high-throughput experiments" @default.
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- W4308981514 doi "https://doi.org/10.1016/j.crmeth.2022.100333" @default.
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