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Enhancing the reverse transcriptase function in Taq polymerase via AI-driven multiparametric rational design.

Yulia E Tomilova¹, Nikolay E Russkikh², Igor M Yi²

¹AO Vector-Best, Novosibirsk, Russia.

Frontiers in Bioengineering and Biotechnology

|December 25, 2024

Summary

This summary is machine-generated.

This study developed Taq polymerase mutants with enhanced reverse transcriptase (RTase) activity using AI-driven design. The new mutants maintain key properties and show promise for advanced molecular diagnostics.

Keywords:

Taq polymerase bioengineering function enhancement machine learning protein language model rational design reverse transcription

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Area of Science:

Biotechnology and Bioengineering
Molecular Biology
Enzyme Engineering

Background:

Enzyme modification is crucial for bioengineering novel functionalities.
Taq polymerase is a key enzyme with potential for enhanced reverse transcriptase (RTase) activity.
Balancing RTase activity with fidelity and substrate tolerance is a significant challenge.

Purpose of the Study:

To develop Taq polymerase mutants with improved RTase activity.
To retain essential properties like fidelity and exonuclease activity.
To integrate AI-driven rational design with experimental validation.

Main Methods:

Selected candidate mutations based on literature and initial wet-lab assessment.
Employed protein language models and regression (Ridge, Gaussian process) for predictive modeling.
Performed in silico screening of millions of mutations followed by wet-lab validation.

Main Results:

Identified 18 enzyme variants with significantly enhanced RTase activity.
Observed a balance between improved RTase activity, lower K^d, and moderate fidelity changes.
Validated enzyme utility in real-time reverse-transcription PCR applications.

Conclusions:

AI-driven design effectively enhances enzyme functionality.
Developed a robust framework for designing tailored enzyme mutants.
The identified Taq polymerase mutants are suitable for advanced molecular diagnostic tools.