AbstractCurrent pathway synthesis tools identify possible pathways that can be added to a host to produce a desired target molecule through the exploration of abstract metabolic and reaction network space. However, not many of these tools do explore gene-level information required to physically realize the identified synthesis pathways, and none explore enzyme-host compatibility. Developing tools that address this disconnect between abstract reactions/metabolic design space and physical genetic sequence design space will enable expedited experimental efforts that avoid exploring unprofitable synthesis pathways. This work describes a workflow, termed Probabilistic Pathway Assembly with Solubility Scores (ProPASS), which links synthesis pathway construction with the exploration of the physical design space as imposed by the availability of enzymes with characterized activities within the host. Predicted protein solubility propensity scores are used as a confidence level to quantify the compatibility of each pathway enzyme with the host (E. coli). This work also presents a database, termed Protein Solubility Database (ProSol DB), which provides solubility confidence scores inE. colifor 240,016 characterized enzymes obtained fromUniProtKB/Swiss-Prot. The utility ofProPASSis demonstrated by generating genetic implementations of heterologous synthesis pathways inE. colithat target several commercially useful biomolecules.AvailabilityProSol DBdata and code forProPASSare available for download fromhttps://github.com/HassounLab/
Caloric restriction creates a metabolic pattern of chronological aging delay that in budding yeast differs from the metabolic design established by two other geroprotectors
