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A Protocol for Functional Assessment of Whole-Protein Saturation Mutagenesis Libraries Utilizing High-Throughput Sequencing
Published on: July 3, 2016
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Protein stability: computation, sequence statistics, and new experimental methods.
1Department of Chemistry & Biochemistry, The Ohio State University, 100 W. 18(th) Ave., Columbus, OH 43210, USA.
Current Opinion in Structural Biology
|October 27, 2015
Summary
Predicting protein stability and designing stabilizing mutations are challenging. Computational and statistical methods, combined with new technologies, show promise for advancing protein stability engineering.
Area of Science:
- Biochemistry
- Computational Biology
- Protein Engineering
Background:
- Calculating protein stability and predicting stabilizing mutations are complex challenges.
- Inadequacy of potential functions, entropy modeling, and sampling difficulties hinder accurate predictions.
- Recent computational designs have yielded highly stable proteins due to optimal structural and sequence features.
Purpose of the Study:
- To review the challenges and advancements in predicting protein stability and guiding mutations.
- To highlight the potential of computational and statistical approaches in protein engineering.
- To discuss the integration of new technologies for enhanced stability engineering.
Main Methods:
- Review of computational design strategies for protein stability.
- Analysis of consensus sequence analysis and co-variation filters for mutation prediction.
- Integration of library approaches, deep sequencing, and high-throughput stability measurements.
Main Results:
- Computational prediction of stability can guide mutation strategies with caveats.
- Mutations from consensus sequence analysis, especially with co-variation filters, are likely to stabilize proteins without functional loss.
- Combining computational, statistical, and library approaches shows significant potential.
Conclusions:
- Despite computational challenges, protein stability engineering is advancing rapidly.
- The synergy of computational and experimental methods is key to future progress.
- New technologies are poised to revolutionize the field of protein stability engineering.