Yu, H;
Dalby, PA;
(2020)
A beginner's guide to molecular dynamics simulations and the identification of cross-correlation networks for enzyme engineering.
In: Tawfik, DS, (ed.)
Enzyme Engineering and Evolution: General Methods.
(pp. 15-49).
Academic Press
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Text (Accepted manuscript)
Methods to assess correlation network for engineering transketolase(revised).pdf - Submitted Version Access restricted to UCL open access staff Download (546kB) |
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Text (Supporting information)
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Abstract
The functional properties of proteins are decided not only by their relatively rigid overall structures, but even more importantly, by their dynamic properties. In a protein, some regions of structure exhibit highly correlated or anti-correlated motions with others, some are highly dynamic but uncorrelated, while other regions are relatively static. The residues with correlated or anti-correlated motions can form a so-called dynamic cross-correlation network, through which information can be transmitted. Such networks have been shown to be critical to allosteric transitions, and ligand binding, and have also been shown to be able to mediate epistatic interactions between mutations. As a result, they are likely to play a significant role in the development of new enzyme engineering strategies. In this chapter, protocols are provided for the assessment of dynamic cross-correlation networks, and for their application in protein engineering. Transketolase from E. coli is used as a model and the software GROMACS is applied for carrying out MD simulations to generate trajectories containing structural ensembles. The trajectory is then used for a dynamic cross correlation analysis using the R package, Bio3D. A matrix of all atom-wise cross-correlation coefficients is finally obtained, which can be displayed in a graphical representation termed a dynamical cross-correlation matrix.
| Type: | Book chapter |
|---|---|
| Title: | A beginner's guide to molecular dynamics simulations and the identification of cross-correlation networks for enzyme engineering |
| ISBN-13: | 78-0-12-821149-6 |
| DOI: | 10.1016/bs.mie.2020.04.020 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Biochemical Engineering |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10122705 |
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