Computational redesign of a thermostable T7 RNA polymerase

Area of Science:

• Biotechnology
• Protein Engineering
• Enzymology

Background:

• T7 RNA polymerase (T7 RNAP) is crucial for biotechnology but limited by low thermal stability (43-44°C).
• Existing stabilized variants have limitations, and the most stable commercial version is proprietary.

Purpose of the Study:

• To develop a highly stable T7 RNAP variant using structure-based computational design.
• To improve thermal stability beyond existing open-source options.

Main Methods:

• Combined mutations from previous variants with new PROSS-identified mutations.
• Filtered mutations using data-driven heuristics to maintain enzyme function.
• Utilized circular dichroism spectroscopy and thermal challenge assays.

Main Results:

• Developed T7T+ with 30 point mutations, exhibiting a functional stability (T50) of 54.9°C.
• Achieved a 2.4°C increase in stability over the best published open-source variant.
• T7T+ retained 59% of wild-type activity at 37°C, demonstrating a high success rate for computational protein design.

Conclusions:

• The T7T+ variant represents a significant advancement in T7 RNAP thermal stability.
• Structure-based computational design is effective for creating stable, functional proteins.
• The T7T+ plasmid is available via AddGene for non-commercial research.