ProtoFold Neighborhood Inspector

Nicolas F. Chaves-de-Plaza, Klaus Hildebrandt, Anna Vilanova

View presentation:2022-10-16T19:45:00ZGMT-0600Change your timezone on the schedule page
2022-10-16T19:45:00Z
Exemplar figure, described by caption below
User interface of the ProtoFold Neighborhood Inspector. With the Residue Constellation, users can select, inspect and analyze neighborhoods in protein structures. The figure shows an example of the analysis workflow for the transforming growth factor beta-1 proprotein (HUMAN). The user selected all residues containing a pathogenic modification using the bulk selection widget. The neighborhood summarization glyphs in the center of the residue constellation permit comparing the neighborhoods of these residues.

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Abstract

Post-translational modifications (PTMs) affecting a protein's residues (amino acids) can disturb its function, leading to illness. Whether or not a PTM is pathogenic depends on its type and the status of neighboring residues. In this paper, we present the ProtoFold Neighborhood Inspector (PFNI), a visualization system for analyzing residues neighborhoods. The main contribution is a visualization idiom, the Residue Constellation (RC), for identifying and comparing three-dimensional neighborhoods based on per-residue features and spatial characteristics. The RC leverages two-dimensional representations of the protein's three-dimensional structure to overcome problems like occlusion, easing the analysis of neighborhoods that often have complicated spatial arrangements. Using the PFNI, we explored proteins’ structural PTM data, which allowed us to identify patterns in the distribution and quantity of per-neighborhood PTMs that might be related to their pathogenic status. In the following, we define the tasks that guided the development of the PFNI and describe the data sources we derived and used. Then, we introduce the PFNI and illustrate its usage through an example of an analysis workflow. We conclude by reflecting on preliminary findings obtained while using the tool on the provided data and future directions concerning the development of the PFNI.