- Title
- MODE-TASK: Large-scale protein motion tools
- Creator
- Ross, Caroline J, Nizami, B, Glenister, Michael, Amamuddy, Olivier S, Atilgan, Ali R, Atilgan, Canan, Tastan Bishop, Özlem
- Date
- 2018
- Type
- text
- Type
- article
- Identifier
- http://hdl.handle.net/10962/125206
- Identifier
- vital:35746
- Identifier
- http://dx.doi.org/10.1101/217505
- Description
- Conventional analysis of molecular dynamics (MD) trajectories may not identify global motions of macromolecules. Normal Mode Analysis (NMA) and Principle Component Analysis (PCA) are two popular methods to quantify large-scale motions, and find the “essential motions”; and have been applied to problems such as drug resistant mutations (Nizami et al., 2016) and viral capsid expansion (Hsieh et al., 2016). MODE-TASK is an array of tools to analyse and compare protein dynamics obtained from MD simulations and/or coarse grained elastic network models. Users may perform standard PCA, kernel and incremental PCA (IPCA). Data reduction techniques (Multidimensional Scaling (MDS) and t-Distributed Stochastics Neighbor Embedding (t-SNE)) are implemented. Users may analyse normal modes by constructing elastic network models (ENMs) of a protein complex. A novel coarse graining approach extends its application to large biological assemblies.
- Format
- 2 pages, pdf
- Language
- English
- Relation
- Bioinformatics, Ross, C., Nizami, B., Glenister, M., Sheik Amamuddy, O., Atilgan, A.R., Atilgan, C. and Tastan Bishop, Ö., 2018. MODE-TASK: large-scale protein motion tools. Bioinformatics, 34(21), pp.3759-3763, Bioinformatics volume 34 number 21 3759 3763 2018 1367-4803
- Rights
- Bioinformatics
- Rights
- Use of this resource is governed by the terms and conditions of the bioRxiv Open Access Statement (https://www.biorxiv.org/about-biorxiv)
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