Retrosynthetic design of metabolic pathways to chemicals not found in nature

Lin, Grace C.; Warden-Rothman, Robert; Voigt, Christopher A.

doi:10.1016/j.coisb.2019.04.004

Cited by 104 publications

(106 citation statements)

References 325 publications

Supporting

Mentioning

101

Contrasting

Order By: Relevance

“…As reviewed in a recent publication (Lin, Warden-Rothman, & Voigt, 2019), various methods have already been published and are in development that additionally allow the identification of new reactions considering the promiscuity of many enzymes but also the chemical similarity of substrates of these enzymes.…”

Section: Resultsmentioning

confidence: 99%

In‐depth characterization of genome‐scale network reconstructions for the in vitro synthesis in cell‐free systems

Schuh

Weyler

Heinzle

2020

Biotech & Bioengineering

View full text Add to dashboard Cite

Cell‐free systems containing multiple enzymes are becoming an increasingly interesting tool for one‐pot syntheses of biochemical compounds. To extensively explore the enormous wealth of enzymes in the biological space, we present methods for assembling and curing data from databases to apply them for the prediction of pathway candidates for directed enzymatic synthesis. We use Kyoto Encyclopedia of Genes and Genomes to establish single organism models and a pan‐organism model that is combining the available data from all organisms listed there. We introduce a filtering scheme to remove data that are not suitable, for example, generic metabolites and general reactions. In addition, a valid stoichiometry of reactions is required for acceptance. The networks created are analyzed by graph theoretical methods to identify a set of metabolites that are potentially reachable from a defined set of starting metabolites. Thus, metabolites not connected to such starting metabolites cannot be produced unless new starting metabolites or reactions are introduced. The network models also comprise stoichiometric and thermodynamic data that allow the definition of constraints to identify potential pathways. The resulting data can be directly applied using existing or future pathway finding tools.

show abstract

Section: Resultsmentioning

confidence: 99%

In‐depth characterization of genome‐scale network reconstructions for the in vitro synthesis in cell‐free systems

Schuh

Weyler

Heinzle

2020

Biotech & Bioengineering

View full text Add to dashboard Cite

show abstract

“…While stereochemistry has been described as one of Nature's most interesting advantages compared to the traditional chemical industry (Lin, Warden-Rothman, and Voigt 2019), it is not used in results presented here, mainly due to current technical limitations to the way stereochemistry is handled by the cheminformatics packages we used at the moment. However, since our formalism uses rules SMARTS which are stereo-aware (Daylight Chemical Information Systems, Inc. 2008), and our standardisation schemes can leave or remove stereochemistry, users wishing to use stereochemistry in RetroPath 3.0 can do so.…”

Section: Resultsmentioning

confidence: 99%

Reinforcement Learning for Bio-Retrosynthesis

Koch

Duigou

Faulon

2019

Preprint

View full text Add to dashboard Cite

Metabolic engineering aims to produce chemicals of interest from living organisms, to advance towards greener chemistry. Despite efforts, the research and development process is still long and costly and efficient computational design tools are required to explore the chemical biosynthetic space. Here, we propose to explore the bio-retrosynthesis space using an Artificial Intelligence based approach relying on the Monte Carlo Tree Search reinforcement learning method, guided by chemical similarity. We implement this method in RetroPath RL, an open-source and modular command line tool. We validate it on a golden dataset of 20 manually curated experimental pathways as well as on a larger dataset of 152 successful metabolic engineering projects. Moreover, we provide a novel feature, that suggests potential media supplements to complement the enzymatic synthesis plan.

show abstract

“…Nonmammalian systems like plants or microbes need to be investigated to uncover these metabolite damage control systems. Although these repair systems may be of little relevance to human health, their use may improve crop production [132,133] and will be vital for metabolic engineering and synthetic biology [134‐136].…”

Section: Future Perspectivesmentioning

confidence: 99%

Enzyme promiscuity, metabolite damage, and metabolite damage control systems of the tricarboxylic acid cycle

Niehaus

Hillmann

2020

The FEBS Journal

View full text Add to dashboard Cite

Promiscuous enzymes and spontaneous chemical reactions can convert normal cellular metabolites into noncanonical or damaged metabolites. These damaged metabolites can be a useless drain on metabolism and may be inhibitory and/or reactive, sometimes leading to toxicity. Thus, mechanisms to prevent metabolite damage from occurring (metabolite damage preemption) or to convert damaged metabolites back to physiological forms (metabolite repair) are essential for sustained operation of metabolic networks. Some iconic examples of metabolite damage and its repair or preemption are associated with the tricarboxylic acid (TCA) cycle, and other metabolite damage control systems are likely to exist here due to the inherent promiscuity of TCA cycle enzymes and reactivity of TCA cycle intermediates. Here, we review known metabolite damage reactions and metabolite damage control systems associated with the TCA cycle. This includes a previously unrecognized metabolite damage control system – an oxaloacetate (OAA) enol‐keto tautomerase activity that is ‘built‐in’ to the TCA cycle. This activity is required to remove the highly inhibitory enol form of OAA and is likely to be critical for TCA cycle operation. By cataloging these instances, we show that metabolite damage and its repair or preemption is a prevalent feature of the TCA cycle and suggest many more metabolite damage control systems are likely to exist.

show abstract

Retrosynthetic design of metabolic pathways to chemicals not found in nature

Cited by 104 publications

References 325 publications

In‐depth characterization of genome‐scale network reconstructions for the in vitro synthesis in cell‐free systems

In‐depth characterization of genome‐scale network reconstructions for the in vitro synthesis in cell‐free systems

Reinforcement Learning for Bio-Retrosynthesis

Enzyme promiscuity, metabolite damage, and metabolite damage control systems of the tricarboxylic acid cycle

Contact Info

Product

Resources

About