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Cell-free systems are useful tools for prototyping metabolic pathways and optimizing the production of various bioproducts. Mechanistically-based kinetic models are uniquely suited to analyze dynamic experimental data collected from cell-free systems and provide vital qualitative insight. However, to date, dynamic kinetic models have not been applied with rigorous biological constraints or trained on adequate experimental data to the degree that they would give high confidence in predictions and broadly demonstrate the potential for widespread use of such kinetic models. In this work, we construct a large-scale dynamic model of cell-free metabolism with the goal of understanding and optimizing butanol production in a cell-free system. Using a combination of parameterization methods, the resultant model captures experimental metabolite measurements across two experimental conditions for nine metabolites at timepoints between 0 and 24 h. We present analysis of the model predictions, provide recommendations for butanol optimization, and identify the aldehyde/alcohol dehydrogenase as the primary bottleneck in butanol production. Sensitivity analysis further reveals the extent to which various parameters are constrained, and our approach for probing valid parameter ranges can be applied to other modeling efforts., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.)

Enzyme substrate promiscuity has significant implications for metabolic engineering. The ability to predict the space of possible enzymatic side reactions is crucial for elucidating underground metabolic networks in microorganisms, as well as harnessing novel biosynthetic capabilities of enzymes to produce desired chemicals. Reaction rule-based cheminformatics platforms have been implemented to computationally enumerate possible promiscuous reactions, relying on existing knowledge of enzymatic transformations to inform novel reactions. However, past versions of curated reaction rules have been limited by a lack of comprehensiveness in representing all possible transformations, as well as the need to prune rules to enhance computational efficiency in pathway expansion. To this end, we curated a set of 1224 most generalized reaction rules, automatically abstracted from atom-mapped MetaCyc reactions and verified to uniquely cover all common enzymatic transformations. We developed a framework to systematically identify and correct redundancies and errors in the curation process, resulting in a minimal, yet comprehensive, rule set. These reaction rules were capable of reproducing more than 85% of all reactions in the KEGG and BRENDA databases, for which a large fraction of reactions is not present in MetaCyc. Our rules exceed all previously published rule sets for which reproduction was possible in this coverage analysis, which allows for the exploration of a larger space of known enzymatic transformations. By leveraging the entire knowledge of possible metabolic reactions through generalized enzymatic reaction rules, we are able to better utilize underground metabolic pathways and accelerate novel biosynthetic pathway design to enable bioproduction towards a wider range of new molecules., (Copyright © 2021 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.)

There have been many achievements in applying biochemical synthetic routes to the synthesis of commodity chemicals. However, most of these endeavors have focused on optimizing and increasing the yields of naturally existing pathways. We sought to evaluate the potential for biosynthesis beyond the limits of known biochemistry towards the production of small molecule drugs that do not exist in nature. Because of the potential for improved yields compared to total synthesis, and therefore lower manufacturing costs, we focused on drugs for diseases endemic to many resource poor regions, like tuberculosis and HIV. Using generalized biochemical reaction rules, we were able to design biochemical pathways for the production of eight small molecule drugs or drug precursors and identify potential enzyme-substrate pairs for nearly every predicted reaction. All pathways begin from native metabolites, abrogating the need for specialized precursors. The simulated pathways showed several trends with the sequential ordering of reactions as well as the types of chemistries used. For some compounds, the main obstacles to finding feasible biochemical pathways were the lack of appropriate, natural starting compounds and a low diversity of biochemical coupling reactions necessary to synthesize molecules with larger molecular size., (Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.)