dGPredictor: Automated fragmentation method for metabolic reaction free energy prediction and de novo pathway design

Group contribution (GC) methods are conventionally used in thermodynamics analysis of metabolic pathways to estimate the standard Gibbs free energy change (ΔrG′o) of enzymatic reactions from limited experimental measurements. However, these methods are limited by their dependence on manually curated groups and inability to capture stereochemical information, leading to low reaction coverage. Herein, we introduce an automated molecular fingerprint-based thermodynamic analysis tool called dGPredictor that enables the consideration of stereochemistry within metabolite structures and thus increases reaction coverage. dGPredictor has a higher prediction accuracy as compared to existing GC methods and can capture free energy changes for isomerase and transferase reactions, which exhibit no overall group changes. We also demonstrate dGPredictor’s ability to predict the Gibbs free energy change for novel reactions and seamless integration within de novo metabolic pathway design tools such as novoStoic. This enables performing a thermodynamic analysis for synthetic pathways, thus safeguarding against the inclusion of reaction steps with infeasible directionalities. To facilitate easy access to dGPredictor, we developed a graphical user interface to predict the standard Gibbs free energy change for reactions at various pH and ionic strengths. The tool allows customized user input of known metabolites as KEGG IDs and novel metabolites as InChI strings (https://github.com/maranasgroup/dGPredictor).Author summaryThe genome-scale metabolic networks consist of a large number of biochemical reactions interconnected in a complex system. The standard Gibbs free energy change is commonly used to check for the feasibility of enzyme-catalyzed reactions as thermodynamics plays a crucial role in pathway design for biochemical synthesis. The group contribution methods using expert-defined functional groups have been extensively used for estimating standard Gibbs free energy change with limited experimental measurements. However, current methods using functional groups have major issues that limit its ability to cover all the metabolites and reactions as well as the inability to consider stereochemistry leads to erroneous estimation of free energy that undergoes only stereochemical change such as isomerases. Here, we introduce a molecular fingerprint-based thermodynamic tool dGPredictor that enables stereochemistry in metabolites and thus improves the reaction coverage with higher prediction accuracy compared to current GC methods. It also allows the ability to predict free energy change for novel reactions which can aid the de novo metabolic pathway design tool to ensure the reaction feasibility. We apply and test our method on reactions in the KEGG database and isobutanol synthesis pathway. In addition, we provide an open-source user-friendly web interface to facilitate easy access for standard Gibbs free energy change of reactions at different physiological states.

Galaxy-SynBioCAD: Synthetic Biology Design Automation tools in Galaxy workflows

Many computer-aided design tools are available for synthetic biology and metabolic engineering. Yet, these tools can be difficult to apprehend, sometimes requiring a level of expertise that limits their use by a wider community. Furthermore, some of the tools, although complementary, rely on different input and output formats and cannot communicate with one another. Scientific workflows address these shortcomings while offering a novel design strategy. Among the workflow systems available, Galaxy is a web-based platform for performing findable and accessible data analyses for all scientists regardless of their informatics expertise, along with interoperable and reproducible computations regardless of the particular platform that is being used.Here, we introduce the Galaxy-SynBioCADa portal, the first Galaxy toolshed for synthetic biology and metabolic engineering. It allows one to easily create workflows or use those already developed by the community. The portal is a growing community effort where developers can add new tools and users can evaluate the tools performing design for their specific projects. The tools and workflows currently shared on the Galaxy-SynBioCAD portal cover an end-to-end metabolic pathway design process from the selection of strain and target to the calculation of DNA parts to be assembled to build libraries of strains to be engineered to produce the target.Standard formats are used throughout to enforce the compatibility of the tools. These include SBML for strain and pathway and SBOL for genetic layouts. The portal has been benchmarked on 81 literature pathways, overall, we find we have a 65% (and 88%) success rate in retrieving the literature pathways among the top 10 (50) pathways predicted and generated by the workflows.

Selenzyme: Enzyme selection tool for pathway design

Synthetic biology applies the principles of engineering to biology in order to create biological functionalities not seen before in nature. One of the most exciting applications of synthetic biology is the design of new organisms with the ability to produce valuable chemicals including pharmaceuticals and biomaterials in a greener; sustainable fashion. Selecting the right enzymes to catalyze each reaction step in order to produce a desired target compound is, however, not trivial. Here, we present Selenzyme, a free online enzyme selection tool for metabolic pathway design. The user is guided through several decision steps in order to shortlist the best candidates for a given pathway step. The tool graphically presents key information about enzymes based on existing databases and tools such as: similarity of sequences and of catalyzed reactions; phylogenetic distance between source organism and intended host species; multiple alignment highlighting conserved regions, predicted catalytic site, and active regions; and relevant properties such as predicted solubility and transmembrane regions. Selenzyme provides bespoke sequence selection for automated workflows in biofoundries. The tool is integrated as part of the pathway design stage into the design-build-test-learn SYNBIOCHEM pipeline. The Selenzyme web server is available at http://selenzyme.synbiochem.co.uk.