RING 4.0: faster residue interaction networks with novel interaction types across over 35,000 different chemical structures.

Residue interaction networks (RINs) are a valuable approach for representing contacts in protein structures. RINs have been widely used in various research areas, including the analysis of mutation effects, domain-domain communication, catalytic activity, and molecular dynamics simulations. The RING server is a powerful tool to calculate non-covalent molecular interactions based on geometrical parameters, providing high-quality and reliable results. Here, we introduce RING 4.0, which includes significant enhancements for identifying both covalent and non-covalent bonds in protein structures. It now encompasses seven different interaction types, with the addition of π-hydrogen, halogen bonds and metal ion coordination sites. The definitions of all available bond types have also been refined and RING can now process the complete PDB chemical component dictionary (over 35000 different molecules) which provides atom names and covalent connectivity information for all known ligands. Optimization of the software has improved execution time by an order of magnitude. The RING web server has been redesigned to provide a more engaging and interactive user experience, incorporating new visualization tools. Users can now visualize all types of interactions simultaneously in the structure viewer and network component. The web server, including extensive help and tutorials, is available from URL: https://ring.biocomputingup.it/.

RING-PyMOL: residue interaction networks of structural ensembles and molecular dynamics.

RING-PyMOL is a plugin for PyMOL providing a set of analysis tools for structural ensembles and molecular dynamic simulations. RING-PyMOL combines residue interaction networks, as provided by the RING software, with structural clustering to enhance the analysis and visualization of the conformational complexity. It combines precise calculation of non-covalent interactions with the power of PyMOL to manipulate and visualize protein structures. The plugin identifies and highlights correlating contacts and interaction patterns that can explain structural allostery, active sites, and structural heterogeneity connected with molecular function. It is easy to use and extremely fast, processing and rendering hundreds of models and long trajectories in seconds. RING-PyMOL generates a number of interactive plots and output files for use with external tools. The underlying RING software has been improved extensively. It is 10 times faster, can process mmCIF files and it identifies typed interactions also for nucleic acids. AVAILABILITY AND IMPLEMENTATION: https://github.com/BioComputingUP/ring-pymol.

Structural Characterization of Hypoxia Inducible Factor α-Prolyl Hydroxylase Domain 2 Interaction through MD Simulations.

The Prolyl Hydroxylases (PHDs) are an enzymatic family that regulates cell oxygen-sensing. PHDs hydroxylate hypoxia-inducible transcription factors α (HIFs-α) driving their proteasomal degradation. Hypoxia inhibits PHDs activity, inducing HIFs-α stabilization and cell adaptation to hypoxia. As a hallmark of cancer, hypoxia promotes neo-angiogenesis and cell proliferation. PHD isoforms are thought to have a variable impact on tumor progression. All isoforms hydroxylate HIF-α (HIF-1,2,3α) with different affinities. However, what determines these differences and how they pair with tumor growth is poorly understood. Here, molecular dynamics simulations were used to characterize the PHD2 binding properties in complexes with HIF-1α and HIF-2α. In parallel, conservation analysis and binding free energy calculations were performed to better understand PHD2 substrate affinity. Our data suggest a direct association between the PHD2 C-terminus and HIF-2α that is not observed in the PHD2/HIF-1α complex. Furthermore, our results indicate that phosphorylation of a PHD2 residue, Thr405, causes a variation in binding energy, despite the fact that this PTM has only a limited structural impact on PHD2/HIFs-α complexes. Collectively, our findings suggest that the PHD2 C-terminus may act as a molecular regulator of PHD's activity.

RING 3.0: fast generation of probabilistic residue interaction networks from structural ensembles.

Residue interaction networks (RINs) are used to represent residue contacts in protein structures. Thanks to the advances in network theory, RINs have been proved effective as an alternative to coordinate data in the analysis of complex systems. The RING server calculates high quality and reliable non-covalent molecular interactions based on geometrical parameters. Here, we present the new RING 3.0 version extending the previous functionality in several ways. The underlying software library has been re-engineered to improve speed by an order of magnitude. RING now also supports the mmCIF format and provides typed interactions for the entire PDB chemical component dictionary, including nucleic acids. Moreover, RING now employs probabilistic graphs, where multiple conformations (e.g. NMR or molecular dynamics ensembles) are mapped as weighted edges, opening up new ways to analyze structural data. The web interface has been expanded to include a simultaneous view of the RIN alongside a structure viewer, with both synchronized and clickable. Contact evolution across models (or time) is displayed as a heatmap and can help in the discovery of correlating interaction patterns. The web server, together with an extensive help and tutorial, is available from URL: https://ring.biocomputingup.it/.