Journal Article

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

Li, Dong, Rooman, Marianne, Pucci, Fabrizio

2025

Overview

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.

• Publisher: MDPI AG,MDPI
• Subject: aggregation / Algorithms / Amino Acid Motifs / Amino acids / Analysis / Aromatic compounds / DNA - chemistry / DNA - metabolism / Energy / Geometry / Models, Molecular / Mutation / Phase transitions / protein affinity / Protein Binding / Protein interaction / protein stability / Protein structure / Protein structure prediction / Proteins / Proteins - chemistry / Proteins - metabolism / RNA / RNA - chemistry / RNA - metabolism / solubility / stacking geometry / Sulfur / Sulfur compounds / T-shaped geometry