Analyzing the cation-aromatic interactions in proteins: Cation-aromatic database V2.0.

The cation-aromatic database (CAD) is a comprehensive repository of cation-aromatic motifs found in experimentally determined protein structures, first reported in 2007 [Proteins, 2007, 67, 1179]. The present article is an update of CAD that contains information of approximately 27.26 million cation-aromatic motifs. CAD uses three distance parameters (r, d1, and d2) to determine the position of the cation relative to the centroid of the aromatic residue and classifies the motifs as cation-π or cation-σ interactions. As of June 2023, about 193 936 protein structures were retrieved from Protein Data Bank, and this resulted in the identification of an impressive number of 27 255 817 cation-aromatic motifs. Among these motifs, spherical motifs constituted 94.09%, while cylindrical motifs made up the remaining 5.91%. When considering the interaction of metal ions with aromatic residues, 965 564 motifs are identified. Remarkably, 82.08% of these motifs involved the binding of metal ions to the amino acid HIS. Moreover, the analysis of binding preferences between cations and aromatic residues revealed that the HIS-HIS, PHE-ARG, and TRP-ARG pairs exhibited a preferential geometry. The motif pair HIS-HIS was the most prevalent, accounting for 19.87% of the total, closely followed by TYR-LYS at 10.17%. Conversely, the motif pair TRP-HIS had the lowest occurrence, representing only 4.20% of the total. The data generated help in revealing the characteristics and biological functions of cation-aromatic interactions in biological molecules. The updated version of CAD (Cation-Aromatic Database V2.0) can be accessed at https://acds.neist.res.in/cadv2.

Analyzing the aromatic-aromatic interactions in proteins: A2ID 2.0.

The Aromatic-Aromatic Interactions Database (A2ID) is a comprehensive repository dedicated to documenting aromatic-aromatic (π-π) networks observed in experimentally determined protein structures. The first version of A2ID was reported in 2011 [Int J Biol Macromol, 2011, 48, 540]. It has undergone a series of significant updates, leading to its current version, which focuses on the identification and analysis of 3,444,619 π-π networks from proteins. The geometrical parameters such as centroid-centroid distances (r) and interplanar angles (ϕ) were used to identify and characterize π-π networks. It was observed that among the 84,500 proteins with at least one aromatic π-π network, about 92.50 % of the instances are found to be either 2π (77.34 %) or 3π (15.23 %) networks. The analysis of interacting amino acid pairs in 2π networks indicated a dominance of PHE residues followed by TYR. The updated version of A2ID incorporates analysis of π-π networks based on SCOP2 and ECOD classifiers, in addition to the existing SCOP, CATH, and EC classifications. This expanded scope allows researchers to explore the characteristics and functional implications of π-π networks in protein structures from multiple perspectives. The current version of A2ID along with its extensive dataset and detailed geometric information is publicly accessible using https://acds.neist.res.in/a2idv2.

Fate of Sc-Ion Interaction With Water: A Computational Study to Address Splitting Water Versus Solvating Sc Ion.

An exhaustive study of Sc-ion interaction with water molecules in all its possible oxidation and spin states has been carried out to delineate the relative propensity of Sc ions toward solvation and water splitting. Potential energy surface analysis of the Sc-ion reaction with water molecules, topological analysis of bonds, and the effect of sequential solvation up to 6 water molecules have been examined. Calculated values showed good agreement with the available experimental results. Close-shell systems such as singlet mono- and tricationic Sc ions prefer to split the water molecules. In contrast, the open-shell systems such as triplet mono- and doublet dicationic Sc ions prefer to get solvated than split the water molecule. Topological analysis of electron density predicted the Sc+/2+-water bond as a noncovalent bond while Sc3+-OH2, Sc2+-OH, and Sc+-H bonds as partially covalent in nature. Energy decomposition analysis revealed that Sc ion-water interactions are driven by electrostatic energy followed by polarization energy. The current study reveals that transition metal catalysis can be one of the most effective tools to employ in water splitting, by properly tuning the electrons, spin, and ligands around the catalytic center.