Highly Dynamic Anion-Quadrupole Networks in Proteins

Anion-π Catalysis Enabled by the Mechanical Bond

We report a series of rotaxane‐based anion–π catalysts in which the mechanical bond between a bipyridine macrocycle and an axle containing an NDI unit is intrinsic to the activity observed, including a [3]rotaxane that catalyses an otherwise disfavoured Michael addition in >60 fold selectivity over a competing decarboxylation pathway that dominates under Brønsted base conditions. The results are rationalized by detailed experimental investigations, electrochemical and computational analysis.

Mining anion-aromatic interactions in the Protein Data Bank

Mutual positioning and non-covalent interactions in anion–aromatic motifs are crucial for functional performance of biological systems. In this context, regular, comprehensive Protein Data Bank (PDB) screening that involves various scientific points of view and individual critical analysis is of utmost importance. Analysis of anions in spheres with radii of 5 Å around all 5- and 6-membered aromatic rings allowed us to distinguish 555 259 unique anion–aromatic motifs, including 92 660 structures out of the 171 588 structural files in the PDB. The use of a scarcely exploited (x, h) coordinate system led to (i) identification of three separate areas of motif accumulation: A – over the ring, B – over the ring-substituent bonds, and C – roughly in the plane of the aromatic ring, and (ii) unprecedented simultaneous comparative description of various anion–aromatic motifs located in these areas. Of the various residues considered, i.e. aminoacids, nucleotides, and ligands, the latter two exhibited a considerable tendency to locate in region Avia archetypal anion–π contacts. The applied model not only enabled statistical quantitative analysis of space around the ring, but also enabled discussion of local intermolecular arrangements, as well as detailed sequence and secondary structure analysis, e.g. anion–π interactions in the GNRA tetraloop in RNA and protein helical structures. As a purely practical issue of this work, the new code source for the PDB research was produced, tested and made freely available at https://github.com/chemiczny/PDB_supramolecular_search.

The comprehensive analysis of non-redundant PDB macromolecular structures investigating anion distributions around all aromatic molecules in available biosystems is presented.

Benchmarking London dispersion corrected density functional theory for noncovalent ion-π interactions

The strongly attractive noncovalent interactions of charged atoms or molecules with π-systems are important binding motifs in many chemical and biological systems. These so-called ion-π interactions play a major role in enzymes, molecular recognition, and for the structure of proteins. In this work, a molecular test set termed IONPI19 is compiled for inter- and intramolecular ion-π interactions, which is well balanced between anionic and cationic systems. The IONPI19 set includes interaction energies of significantly larger molecules (up to 133 atoms) than in other ion-π test sets and covers a broad range of binding motifs. Accurate (local) coupled cluster values are provided as reference. Overall, 19 density functional approximations, including seven (meta-)GGAs, eight hybrid functionals, and four double-hybrid functionals combined with three different London dispersion corrections, are benchmarked for interaction energies. DFT results are further compared to wave function based methods such as MP2 and dispersion corrected Hartree-Fock. Also, the performance of semiempirical QM methods such as the GFNn-xTB and PMx family of methods is tested. It is shown that dispersion-uncorrected DFT underestimates ion-π interactions significantly, even though electrostatic interactions dominate the overall binding. Accordingly, the new charge dependent D4 dispersion model is found to be consistently better than the standard D3 correction. Furthermore, the functional performance trend along Jacob's ladder is generally obeyed and the reduction of the self-interaction error leads to an improvement of (double) hybrid functionals over (meta-)GGAs, even though the effect of the SIE is smaller than expected. Overall, the double-hybrids PWPB95-D4/QZ and revDSD-PBEP86-D4/QZ turned out to be the most reliable among all assessed methods for the description of ion-π interactions, which opens up new perspectives for systems where coupled cluster calculations are no longer computationally feasible.

Crowders Steal Dihydrofolate Reductase Ligands through Quinary Interactions

Dihydrofolate reductase (DHFR) reduces dihydrofolate (DHF) to tetrahydrofolate using NADPH as a cofactor. Due to its role in one carbon metabolism, chromosomal DHFR is the target of the antibacterial drug, trimethoprim. Resistance to trimethoprim has resulted in a type II DHFR that is not structurally related to the chromosomal enzyme target. Because of its metabolic significance, understanding DHFR kinetics and ligand binding behavior in more cell-like conditions, where the total macromolecule concentration can be as great as 300 mg/mL, is important. The progress-curve kinetics and ligand binding properties of the drug target (chromosomal E. coli DHFR) and the drug resistant (R67 DHFR) enzymes were studied in the presence of macromolecular cosolutes. There were varied effects on NADPH oxidation and binding to the two DHFRs, with some cosolutes increasing affinity and others weakening binding. However, DHF binding and reduction in both DHFRs decreased in the presence of all cosolutes. The decreased binding of ligands is mostly attributed to weak associations with the macromolecules, as opposed to crowder effects on the DHFRs. Computer simulations found weak, transient interactions for both ligands with several proteins. The net charge of protein cosolutes correlated with effects on NADP⁺ binding, with near neutral and positively charged proteins having more detrimental effects on binding. For DHF binding, effects correlated more with the size of binding pockets on the protein crowders. These nonspecific interactions between DHFR ligands and proteins predict that the in vivo efficiency of DHFRs may be much lower than expected from their in vitro rates.

Molecular mechanism of substrate selectivity of the arginine-agmatine Antiporter AdiC

The arginine-agmatine antiporter (AdiC) is a component of an acid resistance system developed by enteric bacteria to resist gastric acidity. In order to avoid neutral proton antiport, the monovalent form of arginine, about as abundant as its divalent form under acidic conditions, should be selectively bound by AdiC for transport into the cytosol. In this study, we shed light on the mechanism through which AdiC distinguishes Arg⁺ from Arg²⁺ of arginine by investigating the binding of both forms in addition to that of divalent agmatine, using a combination of molecular dynamics simulations with molecular and quantum mechanics calculations. We show that AdiC indeed preferentially binds Arg⁺. The weaker binding of divalent compounds results mostly from their greater tendency to remain hydrated than Arg⁺. Our data suggests that the binding of Arg⁺ promotes the deprotonation of Glu208, a gating residue, which in turn reinforces its interactions with AdiC, leading to longer residence times of Arg⁺ in the binding site. Although the total electric charge of the ligand appears to be the determinant factor in the discrimination process, two local interactions formed with Trp293, another gating residue of the binding site, also contribute to the selection mechanism: a cation-π interaction with the guanidinium group of Arg⁺ and an anion-π interaction involving Glu208.

The structures and properties of anionic tryptophan complexes

IRMPD spectroscopy and electronic structure calculations are employed to identify π–π interactions in ionic tryptophan clusters.