Experimental protocols for generating focused mutant libraries and screening for thermostable proteins


Many proteins are rapidly deactivated when exposed to high or even ambient temperatures. This cannot only impede the study of a particular protein, but also is one of the major reasons why enzyme catalysis is still widely unable to compete with established chemical processes. Furthermore, differences in protein stability are a challenge in synthetic biology, when individual modules prove to be incompatible. The targeted stabilization of proteins can overcome these hurdles, and protein engineering techniques are more and more reliably supported by computational chemistry tools. Accordingly, algorithms to predict the differences in folding energy of a mutant compared to the wild-type, ΔΔGfold, are used in the highly successful FRESCO workflow. The resulting single mutant prediction library consists typically of a few hundred amino acid exchanges, and after combining the most successful hits we so far obtained stabilized mutants which exhibited increases in apparent melting temperature of 20–35°C and showed vastly increased half-lives, as well as resistance to cosolvents. Here, we report a detailed protocol to generate these mutant libraries experimentally, covering the entire workflow from primer design, through mutagenesis, protein production and screening, to mutation combination strategies. The individual parts of the method are furthermore applicable to many other scenarios besides protein stabilization, and these protocols are valuable for any project requiring individual or semi high-throughput site-directed mutagenesis, protein expression and purification, or generation of mutant combination libraries.

ACS Catalysis
Maximilian JLJ Fürst
Maximilian JLJ Fürst
Assistant Professor of Computational Protein Design

I research computational protein design and high-throughput protein engineering.