Your browser doesn't support javascript.
loading
novoPathFinder: a webserver of designing novel-pathway with integrating GEM-model.
Ding, Shaozhen; Tian, Yu; Cai, Pengli; Zhang, Dachuan; Cheng, Xingxiang; Sun, Dandan; Yuan, Le; Chen, Junni; Tu, Weizhong; Wei, Dong-Qing; Hu, Qian-Nan.
Affiliation
  • Ding S; CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Shanghai 200031, People's Republic of China.
  • Tian Y; School of Biology and Pharmaceutical Engineering, Wuhan Polytechnic University, Wuhan, Hubei 430023, China.
  • Cai P; CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Shanghai 200031, People's Republic of China.
  • Zhang D; Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, People's Republic of China.
  • Cheng X; CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Shanghai 200031, People's Republic of China.
  • Sun D; CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Shanghai 200031, People's Republic of China.
  • Yuan L; CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Shanghai 200031, People's Republic of China.
  • Chen J; Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, SE412 96 Gothenburg, Sweden.
  • Tu W; Wuhan LifeSynther Science and Technology Co. Limited, Wuhan 430070, People's Republic of China.
  • Wei DQ; Wuhan LifeSynther Science and Technology Co. Limited, Wuhan 430070, People's Republic of China.
  • Hu QN; State Key Laboratory of Microbial Metabolism (Shanghai Jiao Tong University), Shanghai 200240, China.
Nucleic Acids Res ; 48(W1): W477-W487, 2020 07 02.
Article in En | MEDLINE | ID: mdl-32313937
ABSTRACT
To increase the number of value-added chemicals that can be produced by metabolic engineering and synthetic biology, constructing metabolic space with novel reactions/pathways is crucial. However, with the large number of reactions that existed in the metabolic space and complicated metabolisms within hosts, identifying novel pathways linking two molecules or heterologous pathways when engineering a host to produce a target molecule is an arduous task. Hence, we built a user-friendly web server, novoPathFinder, which has several features (i) enumerate novel pathways between two specified molecules without considering hosts; (ii) construct heterologous pathways with known or putative reactions for producing target molecule within Escherichia coli or yeast without giving precursor; (iii) estimate novel pathways with considering several categories, including enzyme promiscuity, Synthetic Complex Score (SCScore) and LD50 of intermediates, overall stoichiometric conversions, pathway length, theoretical yields and thermodynamic feasibility. According to the results, novoPathFinder is more capable to recover experimentally validated pathways when comparing other rule-based web server tools. Besides, more efficient pathways with novel reactions could also be retrieved for further experimental exploration. novoPathFinder is available at http//design.rxnfinder.org/novopathfinder/.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Biosynthetic Pathways / Metabolic Engineering Type of study: Prognostic_studies Language: En Journal: Nucleic Acids Res Year: 2020 Type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Biosynthetic Pathways / Metabolic Engineering Type of study: Prognostic_studies Language: En Journal: Nucleic Acids Res Year: 2020 Type: Article