Computational redesign of a thermostable T7 RNA polymerase

Area of Science:

• Biochemistry and Molecular Biology
• Protein Engineering
• Computational Biology

Background:

• T7 RNA polymerase (T7 RNAP) is crucial for biotechnology but limited by low thermal stability (43-44°C).
• Existing stabilized variants have limitations, including proprietary sequences for commercial versions.

Purpose of the Study:

• To develop a highly stable T7 RNA polymerase variant using structure-based computational design.
• To enhance the thermal stability of T7 RNAP while preserving its enzymatic activity.

Main Methods:

• Combined mutations from previous stabilized variants with new mutations identified by PROSS (Protein Engineering by Rational Selection).
• Filtered mutations using data-driven heuristics to maintain protein function.
• Assessed thermal stability via thermal challenge assays and circular dichroism spectroscopy.

Main Results:

• The designed variant, T7^T+, exhibits a functional stability (T₅₀) of 54.9°C, a 2.4°C increase over the previous best open-source variant.
• Circular dichroism spectroscopy indicated an apparent melting temperature of 53.8°C.
• T7^T+ retained 59% of wild-type activity at 37°C, demonstrating a balance of stability and function.

Conclusions:

• Structure-based computational design successfully created a significantly more thermally stable T7 RNAP.
• The high success rate (16/18 designs) validates computational methods for designing stable, functional proteins.
• The T7^T+ plasmid is available via AddGene for non-commercial research, facilitating its use in biotechnology.