Four hundred twenty-eight high-resolution DNA–protein complexes were chosen for a bioinformatics study. Although 164 crystal structures (38% of those searched) contained no interactions, 574 discrete π–contacts between the aromatic amino acids and the DNA nucleobases or deoxyribose were identified using strict criteria, including visual inspection. The abundance and structure of the interactions were determined by unequivocally classifying the contacts as either π–π stacking, π–π T-shaped or sugar–π contacts. Three hundred forty-four nucleobase–amino acid π–π contacts (60% of all interactions identified) were identified in 175 of the crystal structures searched. Unprecedented in the literature, 230 DNA–protein sugar–π contacts (40% of all interactions identified) were identified in 137 crystal structures, which involve C–H···π and/or lone–pair···π interactions, contain any amino acid and can be classified according to sugar atoms involved. Both π–π and sugar–π interactions display a range of relative monomer orientations and therefore interaction energies (up to –50 (–70) kJ mol⁻¹ for neutral (charged) interactions as determined using quantum chemical calculations). In general, DNA–protein π-interactions are more prevalent than perhaps currently accepted and the role of such interactions in many biological processes may yet to be uncovered.

The present work analyzed 120 high-resolution X-ray crystal structures and identified 335 RNA–protein π-interactions (154 nonredundant) between a nucleobase and aromatic (W, H, F, or Y) or acyclic (R, E, or D) π-containing amino acid. Each contact was critically analyzed (including using a visual inspection protocol) to determine the most prevalent composition, structure, and strength of π-interactions at RNA–protein interfaces. These contacts most commonly involve F and U, with U:F interactions comprising one-fifth of the total number of contacts found. Furthermore, the RNA and protein π-systems adopt many different relative orientations, although there is a preference for more parallel (stacked) arrangements. Due to the variation in structure, the strength of the intermolecular forces between the RNA and protein components (as determined from accurate quantum chemical calculations) exhibits a significant range, with most of the contacts providing significant stability to the associated RNA–protein complex (up to −65 kJ mol⁻¹). Comparison to the analogous DNA–protein π-interactions emphasizes differences in RNA– and DNA–protein π-interactions at the molecular level, including the greater abundance of RNA contacts and the involvement of different nucleobase/amino acid residues. Overall, our results provide a clearer picture of the molecular basis of nucleic acid–protein binding and underscore the important role of these contacts in biology, including the significant contribution of π–π interactions to the stability of nucleic acid–protein complexes. Nevertheless, more work is still needed in this area in order to further appreciate the properties and roles of RNA nucleobase–amino acid π-interactions in nature.

Aberrant KRAS signaling is a driver of many cancers and yet remains an elusive target for drug therapy. The nuclease hypersensitive element of the KRAS promoter has been reported to form secondary DNA structures called G-quadruplexes (G4s) which may play important roles in regulating KRAS expression, and has spurred interest in structural elucidation studies of the KRAS G-quadruplexes. Here, we report the first high-resolution crystal structure (1.6 Å) of a KRAS G-quadruplex as a 5′-head-to-head dimer with extensive poly-A π-stacking interactions observed across the dimer. Molecular dynamics simulations confirmed that the poly-A π-stacking interactions are also maintained in the G4 monomers. Docking and molecular dynamics simulations with two G4 ligands that display high stabilization of the KRAS G4 indicated the poly-A loop was a binding site for these ligands in addition to the 5′-G-tetrad. Given sequence and structural variability in the loop regions provide the opportunity for small-molecule targeting of specific G4s, we envisage this high-resolution crystal structure for the KRAS G-quadruplex will aid in the rational design of ligands to selectively target KRAS.

A set of >300 nonredundant high-resolution RNA–protein complexes were rigorously searched for π-contacts between an amino acid side chain (W, H, F, Y, R, E and D) and an RNA nucleobase (denoted π–π interaction) or ribose moiety (denoted sugar–π). The resulting dataset of >1500 RNA–protein π-contacts were visually inspected and classified based on the interaction type, and amino acids and RNA components involved. More than 80% of structures searched contained at least one RNA–protein π-interaction, with π–π contacts making up 59% of the identified interactions. RNA–protein π–π and sugar–π contacts exhibit a range in the RNA and protein components involved, relative monomer orientations and quantum mechanically predicted binding energies. Interestingly, π–π and sugar–π interactions occur more frequently with RNA (4.8 contacts/structure) than DNA (2.6). Moreover, the maximum stability is greater for RNA–protein contacts than DNA–protein interactions. In addition to highlighting distinct differences between RNA and DNA–protein binding, this work has generated the largest dataset of RNA–protein π-interactions to date, thereby underscoring that RNA–protein π-contacts are ubiquitous in nature, and key to the stability and function of RNA–protein complexes.

The treatment of chronic pain is poorly managed by current analgesics, and there is a need for new classes of drugs. We recently developed a series of bioactive lipids that inhibit the human glycine transporter GlyT2 (SLC6A5) and provide analgesia in animal models of pain. Here, we have used functional analysis of mutant transporters combined with molecular dynamics simulations of lipid-transporter interactions to understand how these bioactive lipids interact with GlyT2. This study identifies a novel extracellular allosteric modulator site formed by a crevice between transmembrane domains 5, 7, and 8, and extracellular loop 4 of GlyT2. Knowledge of this site could be exploited further in the development of drugs to treat pain, and to identify other allosteric modulators of the SLC6 family of transporters.