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

This iterative, data-driven strategy ultimately led to the identification of 18 enzyme variants that exhibited markedly improved RTase activity while maintaining a favorable balance of other key properties. These enhancements were generally accompanied by lower K^d, moderately reduced fidelity, and greater tolerance to noncanonical substrates, thereby illustrating a strong interdependence among these traits. Several enzymes validated via this procedure were effective in single-enzyme real-time reverse-transcription PCR setups, implying their utility for the development of new tools for real-time reverse-transcription PCR technologies, such as pathogen RNA detection and gene expression analysis. This study illustrates how AI can be effectively integrated with experimental bioengineering to enhance enzyme functionality systematically. Our approach offers a robust framework for designing enzyme mutants tailored to specific biotechnological applications. The results of our biological activity predictions for mutated Taq polymerases can be accessed at https://huggingface.co/datasets/nerusskikh/taqpol_insilico_dms.