Fig 1.
Overview of the ARNy Plotter webserver interface.
The input and processing panels handle data upload, analysis selection, and job execution, while the results panel showcases examples of plots generated from structural ensemble analyses.
Fig 2.
Schematic overview of the software’s backend architecture, illustrating the main functional components along with the external libraries and packages supporting each module.
Fig 3.
Visualization of two representative structures from the NMR ensemble of 2AP0.
The left panels show the 3D conformations displayed in the interactive viewer, while the right panels present the corresponding base-pairing contact maps. Different symbols denote distinct interaction types according to the Leontis–Westhof classification. In the lower panels, red arrows have been added to highlight structural differences between the two ensemble members.
Fig 4.
Analysis of the structural ensemble of ORF50 obtained from a discrete path sampling exploration of the molecule’s energy landscape.
PCA reveals the partitioning of the ensemble in three main basins. Clicking on a point in the PCA plot allows to visualize the corresponding 3D structure and all its features (indicated here via the red arrow), including the 2D representation shown here.
Fig 5.
Conformational landscape analysis of the upper stem of 7SK highlighting 3 main structural basins.
A representative of each basin can be selected by clicking on a point in the landscape (top, middle, bottom), allowing to show its 3D structure and detailed features, such as the contact map.
Fig 6.
Results of the analysis of FSE rMD trajectory.
A and B show the initial unfolded structure and the final target (native) structure respectively; C: conformational landscape of the folding process projected onto RMSD and Q-values with respect to target; D: time series of the formation of canonical base-pairs; E: arc-diagam the frequency of base pairs from which we can clearly observe the presence of the pseudoknot.
Table 1.
Performance benchmarks for ARNy Plotter ensemble analysis on representative RNA systems.