bioRxivBioinformaticsPreprint
SlytheRINs: using graph parameters and residue interaction networks to analyze protein dynamics and structural ensembles
Laura Shimohara BradaschiaiD, Matheus Caetano Epifane-de-AssunçãoiD, Marília V. A. de Almeida, Ândrea Ribeiro‐dos‐SantosiD, Umberto Laino FulcoiD, Ivanovitch Medeiros Dantas da SilvaiD, Gustavo A. de SouzaiD, Diego Marques CoelhoiD, Gilderlanio Santana de AraújoiD, Joao Paulo M S LimaiD
Abstract
Establishing the relationship between protein structure and functional behavior remains a significant challenge. The recognition that proteins are inherently dynamic, with functions often dependent on conformational changes, is increasingly accepted. Among computational approaches for elucidating protein properties, Residue Interaction Network (RIN) analysis has emerged as a powerful tool. However, conventional RIN analysis is constrained by its reliance on single, static protein structures, which fail to capture the flexibility inherent in dynamic protein folding transitions. To address these limitations, SlytheRINs is introduced as an interactive tool designed for comparative analysis of protein conformations via RINs. SlytheRINs enables dynamic ensemble analysis by decomposing interaction network data across multiple conformations of a single protein and providing detailed residue-interaction mapping across conformational changes via graph parameters in comparative plots. Applying these principles, the conformational variations of the wild-type and a pathogenic variant (G188R) of the human Glucose-6-Phosphatase (G6PC1) catalytic subunit were compared to identify fluctuations in both chemical interactions and graph features associated with conformational changes induced by the residue modification. The analyses identified key shifts in dynamic residue interactions in the protein variant that compromise substrate binding and the catalytic site, thereby elucidating the impact on G6PC1s dynamic behavior and the resulting activity loss. AvailabilityThe source code for SlytheRINs is available on GitHub (https://github.com/evomol-lab/SlytheRINs), while the web tool and documentation are available at https://slytherins.streamlit.app.
- organism: human
- assay: protein structure
- research focus: protein structure prediction
- approach: statistical model
- Citations
- 0
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