This title appears in the Scientific Report :
2020
Please use the identifier:
http://hdl.handle.net/2128/24518 in citations.
Conformational Analysis of Dual-Scale Simulations of Ubiquitin Chains
Conformational Analysis of Dual-Scale Simulations of Ubiquitin Chains
The analysis of large-scale simulations of (bio)molecular systems generated on high performance computer (HPC) clusters poses a challenge on its own due to the sheer amount of high-dimensional data. To make sense of these data and extract relevant information, techniques such as dimensionality reduc...
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Personal Name(s): | Berg, Andrej |
---|---|
Peter, Christine (Corresponding author) | |
Contributing Institute: |
John von Neumann - Institut für Computing; NIC |
Published in: |
NIC Symposium 2020 |
Imprint: |
Jülich
Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag
2020
|
Physical Description: |
137 - 146 |
Conference: | NIC Symposium 2020, Jülich (Germany), 2020-02-27 - 2020-02-28 |
Document Type: |
Contribution to a book Contribution to a conference proceedings |
Research Program: |
ohne Topic |
Series Title: |
Publication Series of the John von Neumann Institute for Computing (NIC) NIC Series
50 |
Link: |
OpenAccess OpenAccess |
Publikationsportal JuSER |
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520 | |a The analysis of large-scale simulations of (bio)molecular systems generated on high performance computer (HPC) clusters poses a challenge on its own due to the sheer amount of high-dimensional data. To make sense of these data and extract relevant information, techniques such as dimensionality reduction and clustering are used. They can be applied to characterise the sampling of conformational phase space as well as to bridge between simulations on different levels of resolution in multiscale setups. Here, we present an approach to analyse long-timescale simulations and to characterise conformational ensembles of flexibly-linked multidomain proteins using the example of differently covalently conjugated ubiquitin chains. We have analysed exhaustive coarse grained (CG) and atomistic simulations with the help of collective variables (CVs) that are particularly suitable to describe the mutual orientation of different subunits and the protein-protein interfaces between them. These data have been further processed through different dimensionality reduction techniques (relying on multidimensional-scaling like approaches as well as neural network autoencoders). The resulting low-dimensional maps have been used for the characterisation of conformational states and the quantitative comparison of conformational free energy landscapes (from simulations at different levels of resolution as well as of different chain types). With this multiscale simulation and analysis approach it is possible to identify characteristic properties of ubiquitin chains in solution which can be subsequently correlated with experimentally observed linkage- and chain length-specific behaviour. | ||
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