Communications BiologyBioinformaticsPeer-reviewed journal article
ARCTIC-3D: Automatic Retrieval and ClusTering of Interfaces in Complexes from 3D structural information
Marco GiuliniiD, Rodrigo V. HonoratoiD, Jesús L. Rivera, Alexandre M. J. J. BonviniD
Abstract
The formation of a stable complex between proteins lies at the core of a wide variety of biological processes and has been the focus of countless experiments. The huge amount of information contained in the protein structural interactome in the Protein Data Bank can now be used to characterise and classify the existing biological interfaces. We here introduce ARCTIC-3D, a fast and user-friendly data mining and clustering software to retrieve data and rationalise the interface information associated with the protein input data. We demonstrate its use by various examples ranging from showing the increased interaction complexity of eukaryotic proteins, 20% of which on average have more than 3 different interfaces compared to only 10% for prokaryotes, to associating different functions to different interfaces. In the context of modelling biomolecular assemblies, we introduce the concept of "recognition entropy", related to the number of possible interfaces of the components of a protein-protein complex, which we demonstrate to correlate with the modelling difficulty. The identified interface clusters can also be used to generate various combinations of interface-specific restraints for integrative modelling. The ARCTIC-3D software is freely available at https://github.com/haddocking/arctic3d and can be accessed as a web-service at https://wenmr.science.uu.nl/arctic-3d
- assay: protein structure
- research focus: clustering
- research focus: benchmarking
- research focus: database / resource
- research focus: software / tool
- approach: statistical model
- approach: machine learning (classical)
- Citations
- 2
- FWCI
- 0.27
- Field percentile
- 43th percentile
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