Computational design of artificial metallo-haloalkane dehalogenase
Haloalkane dehalogenases (HLDs) can catalyze conversion of some toxic haloalkanes to corresponding harmless alcohols. The limiting factors of native HLDs are their slow product releasing step, low activity against non-natural substrates and synthetic substrates. By creating an artificial metallo-HLD...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2015
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| Online Access: | http://psasir.upm.edu.my/id/eprint/75677/ http://psasir.upm.edu.my/id/eprint/75677/1/Computational%20design%20of%20artificial%20metallo-haloalkane%20dehalogenase.pdf |
| _version_ | 1848857755813675008 |
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| author | Ang, Thiau Fu Mohd Yahaya, Normi Salleh, Abu Bakar Leow, Adam Thean Chor |
| author_facet | Ang, Thiau Fu Mohd Yahaya, Normi Salleh, Abu Bakar Leow, Adam Thean Chor |
| author_sort | Ang, Thiau Fu |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Haloalkane dehalogenases (HLDs) can catalyze conversion of some toxic haloalkanes to corresponding harmless alcohols. The limiting factors of native HLDs are their slow product releasing step, low activity against non-natural substrates and synthetic substrates. By creating an artificial metallo-HLD might provide solutions for these problems as metalloenzymes can provide certain advantages like high turnover rate, better stabilization of substrate-enzyme docking and broader substrate specificity. Metallo-HLDs are expected to carry out hydrolysis of haloalkane in 1 step catalysis and with higher KM. Nowadays, computational studies have been improved and commonly used by researchers to validate some structural designs before engineer the proteins in the lab. Computational studies using molecular dynamic simulation software and online molecular tools had largely increase the rate of success in protein engineering. In this work, through the computational design starting from template and metal binding site selection, in silico mutation, in silico metal docking, several validation of metal binding site and in silico docking of substrates had successful created 2 model of metallo-HLDs. These computational approaches had been validated using native metalloenzyme and functional artificial metalloenzyme as positive controls. |
| first_indexed | 2025-11-15T12:02:36Z |
| format | Conference or Workshop Item |
| id | upm-75677 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T12:02:36Z |
| publishDate | 2015 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-756772019-11-12T02:49:04Z http://psasir.upm.edu.my/id/eprint/75677/ Computational design of artificial metallo-haloalkane dehalogenase Ang, Thiau Fu Mohd Yahaya, Normi Salleh, Abu Bakar Leow, Adam Thean Chor Haloalkane dehalogenases (HLDs) can catalyze conversion of some toxic haloalkanes to corresponding harmless alcohols. The limiting factors of native HLDs are their slow product releasing step, low activity against non-natural substrates and synthetic substrates. By creating an artificial metallo-HLD might provide solutions for these problems as metalloenzymes can provide certain advantages like high turnover rate, better stabilization of substrate-enzyme docking and broader substrate specificity. Metallo-HLDs are expected to carry out hydrolysis of haloalkane in 1 step catalysis and with higher KM. Nowadays, computational studies have been improved and commonly used by researchers to validate some structural designs before engineer the proteins in the lab. Computational studies using molecular dynamic simulation software and online molecular tools had largely increase the rate of success in protein engineering. In this work, through the computational design starting from template and metal binding site selection, in silico mutation, in silico metal docking, several validation of metal binding site and in silico docking of substrates had successful created 2 model of metallo-HLDs. These computational approaches had been validated using native metalloenzyme and functional artificial metalloenzyme as positive controls. 2015 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/75677/1/Computational%20design%20of%20artificial%20metallo-haloalkane%20dehalogenase.pdf Ang, Thiau Fu and Mohd Yahaya, Normi and Salleh, Abu Bakar and Leow, Adam Thean Chor (2015) Computational design of artificial metallo-haloalkane dehalogenase. In: 12th Asian Congress on Biotechnology (ACB 2015), 15-19 Nov. 2015, Istana Hotel, Kuala Lumpur, Malaysia. (p. 194). |
| spellingShingle | Ang, Thiau Fu Mohd Yahaya, Normi Salleh, Abu Bakar Leow, Adam Thean Chor Computational design of artificial metallo-haloalkane dehalogenase |
| title | Computational design of artificial metallo-haloalkane dehalogenase |
| title_full | Computational design of artificial metallo-haloalkane dehalogenase |
| title_fullStr | Computational design of artificial metallo-haloalkane dehalogenase |
| title_full_unstemmed | Computational design of artificial metallo-haloalkane dehalogenase |
| title_short | Computational design of artificial metallo-haloalkane dehalogenase |
| title_sort | computational design of artificial metallo-haloalkane dehalogenase |
| url | http://psasir.upm.edu.my/id/eprint/75677/ http://psasir.upm.edu.my/id/eprint/75677/1/Computational%20design%20of%20artificial%20metallo-haloalkane%20dehalogenase.pdf |