SnO2 hollow nanotubes: A novel and efficient support matrix for enzyme immobilization

Muhammad Zahid Anwar, Dong Jun Kim, Ashok Kumar, Sanjay K.S. Patel, Sachin Otari, Primata Mardina, Jae Hoon Jeong, Jung Hoon Sohn, Jong Hak Kim, Jung Tae Park, Jung Kul Lee

Research output: Contribution to journalArticlepeer-review

31 Citations (Scopus)

Abstract

A major challenge in the industrial use of enzymes is maintaining their stability at elevated temperatures and in harsh organic solvents. In order to address this issue, we investigated the use of nanotubes as a support material for the immobilization and stabilization of enzymes in this work. SnO2 hollow nanotubes with a high surface area were synthesized by electrospinning the SnCl2 precursor and polyvinylpyrrolidone (dissolved in dimethyl formamide and ethanol). The electrospun product was used for the covalent immobilization of enzymes such as lipase, horseradish peroxidase, and glucose oxidase. The use of SnO2 hollow nanotubes as a support was promising for all immobilized enzymes, with lipase having the highest protein loading value of 217 mg/g, immobilization yield of 93%, and immobilization efficiency of 89%. The immobilized enzymes were fully characterized by various analytical methods. The covalently bonded lipase showed a half-life value of 4.5 h at 70 °C and retained ~91% of its original activity even after 10 repetitive cycles of use. Thus, the SnO2 hollow nanotubes with their high surface area are promising as a support material for the immobilization of enzymes, leading to improved thermal stability and a higher residual activity of the immobilized enzyme under harsh solvent conditions, as compared to the free enzyme.

Original languageEnglish
Article number15333
JournalScientific reports
Volume7
Issue number1
DOIs
Publication statusPublished - 2017 Dec 1

Bibliographical note

Funding Information:
This research was supported by the Ministry of Science, ICT and Future Planning, Republic of Korea (2013M3A6A8073184, NRF-2017R1A2B3011676, NRF-2017R1A4A1014806, NRF-2015R1C1A1A01053807). This work also was supported by the Energy Efficiency & Resources Core Technology Program of the KETEP, granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea (20153010092130). This work was also supported by the 2015 KU Brain Pool Fellowship of Konkuk University. This research was supported by the KU Research Professor program of Konkuk University.

All Science Journal Classification (ASJC) codes

  • General

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