Rshiny 2022-10-13


RamplotR is a R-Shiny app that visualizes the Ramachandran plot of a given PDB code or file. It also has additioanal features like full customization of the colors of the plot and which residues to show.

Besides just the colorschemes, it also has a customizable background density plot. The default plot is based on the 500 structures that were described in the paper of Lovell et al.. The densities have been calculated for all residues as well as for the individual amino acids. Additionally, a density matrix has also been calculated for all pre-proline amino acids as this was also mentioned in the article. Besides these densities, some other reference datasets where also used. At the moment of writing, these are the Alphafold MANE select set version 3 (consisting out of 17334 structures) and a subset of this dataset containing only residues with a pLDDT > 90 as this is described by alphafold as Regions with pLDDT > 90 are expected to be modelled to high accuracy. These should be suitable for any application that benefits from high accuracy (e.g. characterising binding sites).

The background density matrix has been split up into four regions. These regions are the favoured, allowed, generously allowed and not allowed regions. The region where 85% of the residues fall into is the favoured region. Between 85 and 98 is the allowed region, between 98 an 99.95 is the generously allowed region and whenever a residue falls into the region where less than 0.05% of all residues of all the structures in the reference dataset falls, this will be considered as not allowed. There is always a list created of the residues per region that is also shown in the web application. This list is dynamically updated based on the selected background and/or residues.
At this moment, the Ramachandran plots have only been calculated for the phi and psi angles, and not yet for the chi angles. To calculate the angles, the R package "bio3d" is used.

As a nice addition, an interactive 3D plot of the currently inspected structure is also shown. This plot is made by the NGLVieweR package and can also show non-protein structures such as the ligands and/or DNA/RNA.

The RamplotR app is available at https://bioit.shinyapps.io/RamplotR/.


About AuthorSenior Author

Hi, my name is Cedric Hermans. I'm a lecturer at the bioinformatics department of Howest. I am also a researcher at the BiKC knowledge centre. I am mainly involved in databases and data management, AI/Machine learning, Rshiny applications and python scripts.