Beyond directed evolution - semi-rational protein engineering and design

By Stefan Lutz. Current Opinion in Biotechnology, 2010

482 citations recorded by the source corpus.

Over the last two decades, directed evolution has transformed the field of protein engineering. The advances in understanding protein structure and function, in no insignificant part a result of directed evolution studies, are increasingly empowering scientists and engineers to device more effective methods for manipulating and tailoring biocatalysts. Abandoning large combinatorial libraries, the focus has shifted to small, functionally-rich libraries and rational design. A critical component to the success of these emerging engineering strategies are computational tools for the evaluation of protein sequence datasets and the analysis of conformational variations of amino acids in proteins. Highlighting the opportunities and limitations of such approaches, this review focuses on recent engineering and design examples that require screening or selection of small libraries.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/7fb70bbac4f0d0afbfb2e4d749d9003fd6f1833f

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Citations in the corpus

Enhanced Poly(ethylene terephthalate) Hydrolase Activity by Protein Engineering (2018, background): “Preliminary screening by a simple and convenient high-throughput technique has been a great challenge for researchers [23,24].”
Low-N protein engineering with data-efficient deep learning (2020, background): “Additionally, they often require expert judgment to learn from data, which may include modifying energy functions for biophysical design 61 , and iteratively designing and testing structure-guided mutation combinations 19,62–65 .”
Engineering the third wave of biocatalysis (2012, background): “(S)-2,3-dihydro-1H-indole-2carboxylic acid (39) Phenylalanine ammonia lyase; recombinant enzyme frommetagenome; industrial scale.”
Computational protein structure refinement: Almost there, yet still so far to go (2017, background): “As template-based models often come within 2 – 5 Å C α RMSD from an experimentally determined native structure, 46 the goal of structure re ﬁ nement is a seemingly moderate degree of improvement in accuracy by just a few Å. 48 – 50 Template-based models already incorporate knowledge from existing…”
Consensus protein design (2016, methodology): “…the stabilities of functional and non-functional proteins, for example increasing melting temperatures by 10–32°C (Wirtz and Steipe, 1999; Lehmann and Wyss, 2001; Lehmann et al., 2002; Dai et al., 2007; Lutz, 2010; Magliery et al., 2011; Magliery, 2015; Porebski et al., 2015; Paatero et al., 2016).”