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BioinformaticsBiomolecules
Peer-reviewed journal article

PInteract: Detecting Aromatic-Involving Motifs in Proteins and Protein-Nucleic Acid Complexes

Dong LiiD, Fabrizio PucciiD, Marianne J. RoomaniD

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{pi} molecular orbitals, hold unique significance among molecular interactions due to the electron density 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{pi} -involving interactions in input structures based on geometric criteria, including{pi} -{pi}, cation-{pi}, amino-{pi}, His-{pi}, and sulfur-{pi} interactions. In addition, it is capable of detecting chains and clusters of{pi} interactions as well as particular recurrent motifs at protein-DNA and protein-RNA interfaces, called stair motifs, consisting of a particular combination of{pi} -{pi} stacking, cation/amino/His-{pi} and H-bond interactions. PInteract is freely available for download at https://github.com/3BioCompBio/PInteract.

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02 /Specification & Classification

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