Issue 14, 2022

Mining anion–aromatic interactions in the Protein Data Bank

Abstract

Mutual positioning and non-covalent interactions in anion–aromatic motifs are crucial for functional performance of biological systems. In this context, regular, comprehensive Protein Data Bank (PDB) screening that involves various scientific points of view and individual critical analysis is of utmost importance. Analysis of anions in spheres with radii of 5 Å around all 5- and 6-membered aromatic rings allowed us to distinguish 555 259 unique anion–aromatic motifs, including 92 660 structures out of the 171 588 structural files in the PDB. The use of a scarcely exploited (x, h) coordinate system led to (i) identification of three separate areas of motif accumulation: A – over the ring, B – over the ring-substituent bonds, and C – roughly in the plane of the aromatic ring, and (ii) unprecedented simultaneous comparative description of various anion–aromatic motifs located in these areas. Of the various residues considered, i.e. aminoacids, nucleotides, and ligands, the latter two exhibited a considerable tendency to locate in region Avia archetypal anion–π contacts. The applied model not only enabled statistical quantitative analysis of space around the ring, but also enabled discussion of local intermolecular arrangements, as well as detailed sequence and secondary structure analysis, e.g. anion–π interactions in the GNRA tetraloop in RNA and protein helical structures. As a purely practical issue of this work, the new code source for the PDB research was produced, tested and made freely available at https://github.com/chemiczny/PDB_supramolecular_search.

Graphical abstract: Mining anion–aromatic interactions in the Protein Data Bank

Supplementary files

Article information

Article type
Edge Article
Submitted
07 Feb 2022
Accepted
28 Feb 2022
First published
01 Mar 2022
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY license

Chem. Sci., 2022,13, 3984-3998

Mining anion–aromatic interactions in the Protein Data Bank

E. Kuzniak-Glanowska, M. Glanowski, R. Kurczab, A. J. Bojarski and R. Podgajny, Chem. Sci., 2022, 13, 3984 DOI: 10.1039/D2SC00763K

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