In silico screening of 393 mutants facilitates enzyme engineering of amidase activity in CalB
Our previously presented method for high throughput computational screening of mutant activity (Hediger et al., 2012) is benchmarked against experimentally measured amidase activity for 22 mutants of Candida antarctica lipase B (CalB). Using an appropriate cutoff criterion for the computed barriers,...
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doaj-9f0523c139a74fd5abf9b0e3f91f71b22020-11-24T22:38:59ZengPeerJ Inc.PeerJ2167-83592013-08-011e14510.7717/peerj.145145In silico screening of 393 mutants facilitates enzyme engineering of amidase activity in CalBMartin R. Hediger0Luca De Vico1Julie B. Rannes2Christian Jäckel3Werner Besenmatter4Allan Svendsen5Jan H. Jensen6Department of Chemistry, University of Copenhagen, Copenhagen, DenmarkDepartment of Chemistry, University of Copenhagen, Copenhagen, DenmarkNovozymes A/S, Bagsværd, DenmarkNovozymes A/S, Bagsværd, DenmarkNovozymes A/S, Bagsværd, DenmarkNovozymes A/S, Bagsværd, DenmarkDepartment of Chemistry, University of Copenhagen, Copenhagen, DenmarkOur previously presented method for high throughput computational screening of mutant activity (Hediger et al., 2012) is benchmarked against experimentally measured amidase activity for 22 mutants of Candida antarctica lipase B (CalB). Using an appropriate cutoff criterion for the computed barriers, the qualitative activity of 15 out of 22 mutants is correctly predicted. The method identifies four of the six most active mutants with ≥3-fold wild type activity and seven out of the eight least active mutants with ≤0.5-fold wild type activity. The method is further used to screen all sterically possible (386) double-, triple- and quadruple-mutants constructed from the most active single mutants. Based on the benchmark test at least 20 new promising mutants are identified.https://peerj.com/articles/145.pdfEnzyme EngineeringComputational Chemistry |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Martin R. Hediger Luca De Vico Julie B. Rannes Christian Jäckel Werner Besenmatter Allan Svendsen Jan H. Jensen |
spellingShingle |
Martin R. Hediger Luca De Vico Julie B. Rannes Christian Jäckel Werner Besenmatter Allan Svendsen Jan H. Jensen In silico screening of 393 mutants facilitates enzyme engineering of amidase activity in CalB PeerJ Enzyme Engineering Computational Chemistry |
author_facet |
Martin R. Hediger Luca De Vico Julie B. Rannes Christian Jäckel Werner Besenmatter Allan Svendsen Jan H. Jensen |
author_sort |
Martin R. Hediger |
title |
In silico screening of 393 mutants facilitates enzyme engineering of amidase activity in CalB |
title_short |
In silico screening of 393 mutants facilitates enzyme engineering of amidase activity in CalB |
title_full |
In silico screening of 393 mutants facilitates enzyme engineering of amidase activity in CalB |
title_fullStr |
In silico screening of 393 mutants facilitates enzyme engineering of amidase activity in CalB |
title_full_unstemmed |
In silico screening of 393 mutants facilitates enzyme engineering of amidase activity in CalB |
title_sort |
in silico screening of 393 mutants facilitates enzyme engineering of amidase activity in calb |
publisher |
PeerJ Inc. |
series |
PeerJ |
issn |
2167-8359 |
publishDate |
2013-08-01 |
description |
Our previously presented method for high throughput computational screening of mutant activity (Hediger et al., 2012) is benchmarked against experimentally measured amidase activity for 22 mutants of Candida antarctica lipase B (CalB). Using an appropriate cutoff criterion for the computed barriers, the qualitative activity of 15 out of 22 mutants is correctly predicted. The method identifies four of the six most active mutants with ≥3-fold wild type activity and seven out of the eight least active mutants with ≤0.5-fold wild type activity. The method is further used to screen all sterically possible (386) double-, triple- and quadruple-mutants constructed from the most active single mutants. Based on the benchmark test at least 20 new promising mutants are identified. |
topic |
Enzyme Engineering Computational Chemistry |
url |
https://peerj.com/articles/145.pdf |
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