(605b) novoStoic2.0: An Integrated Framework for Pathway Synthesis, Thermodynamic Evaluation, and Enzyme Selection

(Retro)-biosynthetic approaches in synthetic biology have made significant advances in designing (i) production routes for new biochemicals, (ii) novel biodegradation strategies of toxic compounds, and (ii) funneling of heterogeneous aromatics towards biorenewable chemicals with industrial interest. Pathway design is an integrated task that requires knowledge and encoding of relevant biochemistries, biophysical understanding of enzymatic activity and specificity, understanding thermodynamic feasibility of individual steps, and subsequent host selection and metabolic engineering. However, using only cataloged enzymatic activities can limit discovery of novel production routes. Through the use of retro-biosynthesis algorithms, novel conversions can be assembled that leverage alteration of enzymatic substrate or cofactor specificity. These novel pathways may shorten existing routes, avoid toxic intermediates or low capacity conversions. The need to modify existing enzymes gives rise to enzyme engineering challenges in implementing these designs. Herein, we introduce novoStoic2.0, an integrated workflow for pathway synthesis that combines different tools for de novo pathway design within a single framework. dGPredictor estimates Gibbs energy change for (novel) reactions involving possibly novel structures to assess thermodynamic feasibility of various steps. The integration of dGPredictor within novoStoic2.0 safeguards against using reactions (or novel conversion steps) in thermodynamically unfavorable direction. EnzRank is a convolutional neural network (CNN) based approach to select enzyme candidates for novel conversions in pathway design. EnzRank rank-order existing enzymes for their suitability to undergo successful protein engineering through directed evolution or de novo design towards desired specific substrate activity. EnzRank supplements pathway designs provided by novoStoic to find enzyme candidates for any novel reaction step. novoStoic2.0 aims to usher a unified web-based interface for biosynthesis of thermodynamically feasible, carbon and energy balanced pathways with a way of selecting enzymes to undergo re-engineering for novel reaction steps.