aRMSD is an open toolbox for the structural comparison of two
constitutionally identical molecules. The data are read from common
file formats (e.g., *.xyz, *.pdb, etc.) by default, or by
assistance of openbabel.1 The results may be accessed
interactively as 3D rendering with vtk2 and exported. The
development started with Arne Wagner during his PhD
thesis in the Himmel group (University of Heidelberg) and
made available on https://github.com/armsd/aRMSD.
Contrasting to said original branch, this fork develops aRMSD
under Linux (Debian 10 / Buster, currently testing / Sid), since it
was used side-by-side with other programs already deployed
successfully in Linux. Specific to Linux: I liked to have a Python
script resolving the dependencies of aRMSD instead of a somewhat
manual download, and installation anticipated for Windows. Other
than this, changes made within this fork, however, should work
equally in other operating systems.
As shown in the figure below, aRMSD may be used to align the
models (a) and reorder the atom order by the Hungarian
algorithm (b). Subsequently, the superposition is optimized by
minimization of the RMSD according to the Kabsch algorithm.
In a newly designed representation (c), the differences between the two models may be accessed visually: atoms drawn with larger diameter indicate a larger relative contribution to the final RMSD determined for the complete model. The color scaling, corresponding to the scale at the side, corresponds to the absolute difference – in Angstroms – of said atom for both models in the optimized superposition.
In addition, the program compares the corresponding bond lengths of
model and reference indicates either by green or red color encoding
if the one by the model is shorter, or lengthier than the
corresponding bond in the reference. Not shown here, but aRMSD
allows the interactive readout of the differences found for selected
bond lengths, angles, and dihedral angles, too.
Equally, the program offers you an interactive 3D rendering of model
and reference with the optimized superposition (d). This "best fit"
determined may be saved in *.xyz files.
On an operational system including matplotlib, aRMSD may
complement the scrutiny by computing and plotting selected
statistics. The scaling may be altered by the user, equally in
charge to select the file format of export (*.png; *.ps, *.eps
*.pdf, *.svg; *.tkiz).
Besides the results of the Kabsch test, supplementary similarity
figures of merit like the cosine similarity or the GARD values may
be stored permanently in plain ASCII (aRMSD_logfile.out).
Altogether with a few test data (sub-directory examples), an
illustrated primer in sub-directory docs will guide you through
setting-up the program and detail out how to perform a basic analysis.
aRMSD emerges from the pair-wise comparison of (crystallographic,
but not limited to this) models with significant user-interaction.
This offers you multiple levels to check and adjust the progress of
the analysis. As such, a batch-wise comparison of models is not
foreseen.
Note, however, that an automate, batch-wise scrutiny of two model
data may yield wrong results. One potential pitfall is how the
model information is handled prior to the refinement of the
structure alignment, where aRMSD uses the Hungarian algorithm. To
quote Kildgaard:3
"The RMSD can be minimized by translating and rotating one set of coordinates (the other is held fixed) because the molecules are invariant under these operations. This will lead to the two molecules being superimposed but can also lead to a false RMSD value if the atoms are not ordered identically."
Independent from this problem, the conventional RMSD optimization accounts only for atom connectivity, neglecting bond order. As demonstrated (and illustrated) by Temeslo4, this may yield to results questionable from a chemists point of view.
aRMSD was developed in Windows by Arne Wagner during his PhD
thesis in the Himmel group (University of Heidelberg, Germany). It
is described briefly in his PhD thesis submitted in
2015.5 The program was presented in further detail in
Wagner, A.; Himmel, H.-J. aRMSD: A Comprehensive Tool for Structural Analysis. J. Chem. Inf. Model., 2017, 57, 428–438 (doi: 10.1021/acs.jcim.6b00516)
and originally deposit as open source code with the permissible MIT license to the public under
https://github.com/armsd/aRMSD
As by November 2018, his last public github-commit regarding aRMSD
was on April 5, 2017. My subsequent work on aRMSD is based on this release.
1 Open Babel, http://openbabel.org/wiki/Main_Page. For further details, see by O'Boyle, N. M.; Banck, M.; James, C. A.; Morley, C.; Vandermeersch, T.; Hutchison, G. R. Open Babel: An open chemical toolbox. J. Cheminf. 2011, 3:33 (doi: 10.1186/1758-2946-3-33).
3 Kildgaard, J. V.; Mikkelsen, K. V.; Bilde, M.; Elm, J. Hydration of Atmospheric Molecular Clusters: A New Method for Systematic Configurational Sampling. J. Phys. Chem. A 2018, 122, 5026–5036 (doi: 10.1021/acs.jpca.8b02758).
4 Temeslo, B.; Mabey, J. M.; Kubota, T.; Appiah-Padi, N.; Shields, G. C. ArbAlign: A Tool for Optimal Alignment of Arbitrarily Ordered Isomers Using the Kuhn-Munkres Algorithm. J. Chem. Inf. Model. 2017, 57, 1045–1054 (doi: 10.1021/acs.jcim.6b00546).
5 Wagner, A. Synthese und Koordinationschemie guanidinatstabilisierter Diboranverbindungen. (Synthesis and Coordination Chemistry of Guanidinate-Stabilised Diboranes) PhD thesis (2015), University of Heidelberg (Germany). Written in German including an English summary. The pdf of this document may be found at the doi 10.11588/heidok.00019018.