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PInteract: Detecting Aromatic-Involving Motifs in Proteins and Protein-Nucleic Acid Complexes
Dong Li1,2, Fabrizio Pucci1,2, Marianne Rooman1,2
1Computational Biology and Bioinformatics, Université Libre de Bruxelles, 1050 Brussels, Belgium.
Abstract:
With the recent development of accurate protein structure prediction tools, virtually all protein sequences now have an experimental or a modeled structure. It has therefore become essential to develop fast algorithms capable of detecting non-covalent interactions not only within proteins but also in protein-protein, protein-DNA, protein-RNA, and protein-ligand complexes. Interactions involving aromatic compounds, particularly their π molecular orbitals, hold unique significance among molecular interactions due to the electron delocalization, which is known to play a key role in processes such as protein aggregation. In this paper, we present PInteract, an algorithm that detects π-involving interactions in input structures based on geometric criteria, including π-π, cation-π, amino-π, His-π, and sulfur-π interactions. In addition, it is capable of detecting chains and clusters of π interactions as well as particular recurrent motifs at protein-DNA and protein-RNA interfaces, called stair motifs, consisting of a particular combination of π-π stacking, cation/amino/His-π and H-bond interactions.
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