%0 Journal Article %1 Saa2019Expanding %A Saa, Pedro A. %A Cortés, María P. %A López, Javiera %A Bustos, Diego %A Maass, Alejandro %A Agosin, Eduardo %D 2019 %J Biotechnology Journal %K in-silico metabolic-engineering review %N ja %P 1800734 %R 10.1002/biot.201800734 %T Expanding metabolic capabilities using novel pathway designs: computational tools and case studies %U https://onlinelibrary.wiley.com/doi/abs/10.1002/biot.201800734 %V 0 %X Abstract Design and selection of efficient metabolic pathways is critical for the success of metabolic engineering endeavors. Convenient pathways should not only produce the target metabolite in high yields, they also require to be thermodynamically feasible under production conditions, and prefer efficient enzymes. To support the design and selection of such pathways, different computational approaches have been proposed for exploring the feasible pathway space under many of the above constraints. In this review, we present an overview of recent constraint-based optimization frameworks for metabolic pathway prediction, as well as relevant pathway engineering case studies that highlight the importance of rational metabolic designs. Despite the availability and suitability of in silico design tools for metabolic pathway engineering, we found scarce - although increasing - application of computational outcomes. Finally, we discuss challenges and limitations hindering the broad adoption and successful application of these tools in metabolic engineering projects. This article is protected by copyright. All rights reserved.

@article{Saa2019Expanding, abstract = {Abstract Design and selection of efficient metabolic pathways is critical for the success of metabolic engineering endeavors. Convenient pathways should not only produce the target metabolite in high yields, they also require to be thermodynamically feasible under production conditions, and prefer efficient enzymes. To support the design and selection of such pathways, different computational approaches have been proposed for exploring the feasible pathway space under many of the above constraints. In this review, we present an overview of recent constraint-based optimization frameworks for metabolic pathway prediction, as well as relevant pathway engineering case studies that highlight the importance of rational metabolic designs. Despite the availability and suitability of in silico design tools for metabolic pathway engineering, we found scarce - although increasing - application of computational outcomes. Finally, we discuss challenges and limitations hindering the broad adoption and successful application of these tools in metabolic engineering projects. This article is protected by copyright. All rights reserved.}, added-at = {2019-05-31T08:52:16.000+0200}, author = {Saa, Pedro A. and Cortés, María P. and López, Javiera and Bustos, Diego and Maass, Alejandro and Agosin, Eduardo}, biburl = {https://www.bibsonomy.org/bibtex/2ab45638f616036924c6efa13c2a3123c/karthikraman}, doi = {10.1002/biot.201800734}, eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/biot.201800734}, interhash = {03f36e673bb98b04c4a3af5bb9f03b20}, intrahash = {ab45638f616036924c6efa13c2a3123c}, journal = {Biotechnology Journal}, keywords = {in-silico metabolic-engineering review}, number = {ja}, pages = 1800734, timestamp = {2019-05-31T08:52:16.000+0200}, title = {Expanding metabolic capabilities using novel pathway designs: computational tools and case studies}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/biot.201800734}, volume = 0, year = 2019 }