Increasing Protein Stability by Inferring Substitution Effects from High-throughput Experiments

Overview

Journal Cell Rep Methods

Specialty Cell Biology

Date 2022 Dec 1

PMID 36452862

Authors

Rasmus Krogh Norrild

Kristoffer Enoe Johansson

Charlotte OShea

Jens Preben Morth

Kresten Lindorff-Larsen

Jakob Rahr Winther

Affiliations

Soon will be listed here.

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.

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