Probing phenylalanine/adenine pi-stacking interactions in protein complexes with explicitly correlated and CCSD(T) computations

An Atlas of the base inter-RNA stacks involved in bacterial translation

Nucleobase-specific noncovalent interactions play a crucial role in translation. Herein, we provide a comprehensive analysis of the stacks between different RNA components in the crystal structures of the bacterial ribosome caught at different translation stages. Analysis of tRNA||rRNA stacks reveals distinct behaviour; both the A-and E-site tRNAs exhibit unique stacking patterns with 23S rRNA bases, while P-site tRNAs stack with 16S rRNA bases. Furthermore, E-site stacks exhibit diverse face orientations and ring topologies-rare for inter-chain RNA interactions-with higher average interaction energies than A or P-site stacks. This suggests that stacking may be essential for stabilizing tRNA progression through the E-site. Additionally, mRNA||rRNA stacks reveal other geometries, which depend on the tRNA binding site, whereas 16S rRNA||23S rRNA stacks highlight the importance of specific bases in maintaining the integrity of the translational complex by linking the two rRNAs. Furthermore, tRNA||mRNA stacks exhibit distinct geometries and energetics at the E-site, indicating their significance during tRNA translocation and elimination. Overall, both A and E-sites display a more diverse distribution of inter-RNA stacks compared to the P-site. Stacking interactions in the active ribosome are not simply accidental byproducts of biochemistry but are likely invoked to compensate and support the integrity and dynamics of translation.

Structural Mapping of the Base Stacks Containing Post-transcriptionally Modified Bases in RNA

Post-transcriptionally modified bases play vital roles in many biochemical processes involving RNA. Analysis of the non-covalent interactions associated with these bases in RNA is crucial for providing a more complete understanding of the RNA structure and function; however, the characterization of these interactions remains understudied. To address this limitation, we present a comprehensive analysis of base stacks involving all crystallographic occurrences of the most biologically relevant modified bases in a large dataset of high-resolution RNA crystal structures. This is accompanied by a geometrical classification of the stacking contacts using our established tools. Coupled with quantum chemical calculations and an analysis of the specific structural context of these stacks, this provides a map of the stacking conformations available to modified bases in RNA. Overall, our analysis is expected to facilitate structural research on altered RNA bases.

Structural and Energetic Features of Base-Base Stacking Contacts in RNA

Nucleobase π-π stacking is one of the crucial organizing interactions within three-dimensional (3D) RNA architectures. Characterizing the structural variability of these contacts in RNA crystal structures will help delineate their subtleties and their role in determining function. This analysis of different stacking geometries found in RNA X-ray crystal structures is the largest such survey to date; coupled with quantum-mechanical calculations on typical representatives of each possible stacking arrangement, we determined the distribution of stacking interaction energies. A total of 1,735,481 stacking contacts, spanning 359 of the 384 theoretically possible distinct stacking geometries, were identified. Our analysis reveals preferential occurrences of specific consecutive stacking arrangements in certain regions of RNA architectures. Quantum chemical calculations suggest that 88 of the 359 contacts possess intrinsically stable stacking geometries, whereas the remaining stacks require the RNA backbone or surrounding macromolecular environment to force their formation and maintain their stability. Our systematic analysis of π-π stacks in RNA highlights trends in the occurrence and localization of these noncovalent interactions and may help better understand the structural intricacies of functional RNA-based molecular architectures.

Investigation of cobalt(III)-phenylalanine complexes for hypoxia-activated drug delivery

Four cobalt(iii)-phenylalanine complexes, [Co(Phe)(py2en)](ClO4)2·H2O (1), [Co(Phe)(TPA)](ClO4)2·H2O (2), [Co(Phe)(py2enMe2)](ClO4)2·H2O (3) and [Co(bipy)2(Phe)](ClO4)2·H2O (4), were investigated as prototype models for hypoxia-activated delivery of melphalan - a phenylalanine derivative anticancer drug of the class of nitrogen mustards. Single crystal X-ray diffraction analysis provided the molecular structures of 1-4, as a single isomer/conformer. According with NMR and theoretical calculations, the solid-state structures of 2 and 4 are maintained in solutions. For complexes 1 and 3, though, a mixture of isomers was found in DMSO solutions: Λ-cisα(exo,exo) and Δ-cisβ1(exo,exo) for 1 (3 : 2 ratio), and Λ-cisα(exo,exo) and Δ-cisα(exo,exo) for 3 (5 : 1 ratio). Theoretical calculations point to a re-equilibration reaction of the solid-state Λ-cisβ1 isomer of 1 in solution. Electrochemical analysis revealed a correlation between the electron-donor capacity of the ancillary ligands and the redox potentials of the complexes. The potentials varied from +0.01 for 1 to +0.31 V vs. SHE for 4 in aqueous media and indicate that reduction should be achieved in biological media. The integrity of the complexes in pH 5.5 and 7.4 buffered solutions was confirmed by UV-Vis monitoring up to 24 h at 25 °C. Reduction by ascorbic acid (AA) shows an O2-dependent dissociation of the l-Phe for complexes 1-3, with higher conversion rates at pH 7.4. For complex 4, a fast dissociation of l-Phe was observed, with conversion rates unaffected by the pH and presence of O2.

Anatomy of noncovalent interactions between the nucleobases or ribose and π-containing amino acids in RNA-protein complexes

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.

Cytidine Diphosphoramidate Kinase: An Enzyme Required for the Biosynthesis of the O-Methyl Phosphoramidate Modification in the Capsular Polysaccharides of Campylobacter jejuni

Campylobacter jejuni, a leading cause of gastroenteritis, produces a capsular polysaccharide that is derivatized with a unique O-methyl phosphoramidate (MeOPN) modification. This modification contributes to serum resistance and invasion of epithelial cells. Previously, the first three biosynthetic steps for the formation of MeOPN were elucidated. The first step is catalyzed by a novel glutamine kinase (Cj1418), which catalyzes the adenosine triphosphate (ATP)-dependent phosphorylation of the amide nitrogen of l-glutamine. l-Glutamine phosphate is used by cytidine triphosphate (CTP):phosphoglutamine cytidylyltransferase (Cj1416) to displace pyrophosphate from CTP to generate cytidine diphosphate (CDP)-l-glutamine, which is then hydrolyzed by γ-glutamyl-CDP-amidate hydrolase (Cj1417) to form cytidine diphosphoramidate (CDP-NH₂). Here, we show that Cj1415 catalyzes the ATP-dependent phosphorylation of CDP-NH₂ to form 3'-phospho-cytidine-5'-diphosphoramidate. Cj1415 will also catalyze the phosphorylation of adenosine diphosphoramidate (ADP-NH₂) and uridine diphosphoramidate (UDP-NH₂) but at significantly reduced rates. It is proposed that Cj1415 be named cytidine diphosphoramidate kinase.

Topology of RNA-protein nucleobase-amino acid π-π interactions and comparison to analogous DNA-protein π-π contacts

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.

Surface shapes and surrounding environment analysis of single- and double-stranded DNA-binding proteins in protein-DNA interface

Protein-DNA bindings are critical to many biological processes. However, the structural mechanisms underlying these interactions are not fully understood. Here, we analyzed the residues shape (peak, flat, or valley) and the surrounding environment of double-stranded DNA-binding proteins (DSBs) and single-stranded DNA-binding proteins (SSBs) in protein-DNA interfaces. In the results, we found that the interface shapes, hydrogen bonds, and the surrounding environment present significant differences between the two kinds of proteins. Built on the investigation results, we constructed a random forest (RF) classifier to distinguish DSBs and SSBs with satisfying performance. In conclusion, we present a novel methodology to characterize protein interfaces, which will deepen our understanding of the specificity of proteins binding to ssDNA (single-stranded DNA) or dsDNA (double-stranded DNA). Proteins 2016; 84:979-989. © 2016 Wiley Periodicals, Inc.

The effect of POPC acyl chains packing by aromatic amino acid methyl esters investigated by ATR-FTIR combined with QM calculations

​The packing of POPC acyl chains can be influenced by aromatic amino acid methyl esters significantly, thus the HCCH motif is packed closed to the other one of an adjacent acyl chain with enhancement by dispersion interactions.

Landscape of π-π and sugar-π contacts in DNA-protein interactions

There were 1765 contacts identified between DNA nucleobases or deoxyribose and cyclic (W, H, F, Y) or acyclic (R, E, D) amino acids in 672 X-ray structures of DNA-protein complexes. In this first study to compare π-interactions between the cyclic and acyclic amino acids, visual inspection was used to categorize amino acid interactions as nucleobase π-π (according to biological edge) or deoxyribose sugar-π (according to sugar edge). Overall, 54% of contacts are nucleobase π-π interactions, which involve all amino acids, but are more common for Y, F, and R, and involve all DNA nucleobases with similar frequencies. Among binding arrangements, cyclic amino acids prefer more planar (stacked) π-systems than the acyclic counterparts. Although sugar-π interactions were only previously identified with the cyclic amino acids and were found to be less common (38%) than nucleobase-cyclic amino acid contacts, sugar-π interactions are more common than nucleobase π-π contacts for the acyclic series (61% of contacts). Similar to DNA-protein π-π interactions, sugar-π contacts most frequently involve Y and R, although all amino acids adopt many binding orientations relative to deoxyribose. These DNA-protein π-interactions stabilize biological systems, by up to approximately -40 kJ mol(-1) for neutral nucleobase or sugar-amino acid interactions, but up to approximately -95 kJ mol(-1) for positively or negatively charged contacts. The high frequency and strength, despite variation in structure and composition, of these π-interactions point to an important function in biological systems.

Serine and Cysteine π-Interactions in Nature: A Comparison of the Frequency, Structure, and Stability of Contacts Involving Oxygen and Sulfur

Despite many DNA–protein π-interactions in high-resolution crystal structures, only four X–H···π or X···π interactions were found between serine (Ser) or cysteine (Cys) and DNA nucleobase π-systems in over 100 DNA–protein complexes (where X = O for Ser and X = S for Cys). Nevertheless, 126 non-covalent contacts occur between Ser or Cys and the aromatic amino acids in many binding arrangements within proteins. Furthermore, Ser and Cys protein–protein π-interactions occur with similar frequencies and strengths. Most importantly, due to the great stability that can be provided to biological macromolecules (up to –20 kJ mol–1 for neutral π-systems or –40 kJ mol–1 for cationic π-systems), Ser and Cys π-interactions should be considered when analyzing protein stability and function.

DNA-protein π-interactions in nature: abundance, structure, composition and strength of contacts between aromatic amino acids and DNA nucleobases or deoxyribose sugar

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.

Hydrophobic noncovalent interactions of inosine-phenylalanine: a theoretical model for investigating the molecular recognition of nucleobases

Understanding the molecular recognition process of nucleobases is one of the greatest challenges for both computational chemistry and biophysics fields. In fact, our results point out that it is a hard task to take into account the hydrophobic interactions, such as π-π and T-stacking interactions, by theoretical calculations using conventional force fields due to quantum effects of hyperconjugation and electronic correlation. In this line, our findings put in evidence that simple modifications in the Lennard-Jones potential can improve theoretical predictions in scenarios where hydrophobic interactions can drive the molecular recognition.

Aromatic interactions modulate the 5'-base selectivity of the DNA-binding autoantibody ED-10

We present detailed computational analyses of the binding of four dinucleotides to a highly sequence-selective single-stranded DNA (ssDNA) binding antibody (ED-10) and selected point mutants. Anti-DNA antibodies are central to the pathogenesis of systemic lupus erythematosus (SLE), and a more complete understanding of the mode of binding of DNA and other ligands will be necessary to elucidate the role of anti-DNA antibodies in the kidney inflammation associated with SLE. Classical molecular mechanics based molecular dynamics simulations and density functional theory (DFT) computations were applied to pinpoint the origin of selectivity for the 5'-nucleotide. In particular, the strength of interactions between each nucleotide and the surrounding residues were computed using MMGBSA as well as DFT applied to a cluster model of the binding site. The results agree qualitatively with experimental binding free energies, and indicate that π-stacking, CH/π, NH/π, and hydrogen-bonding interactions all contribute to 5'-base selectivity in ED-10. Most importantly, the selectivity for dTdC over dAdC arises primarily from differences in the strength of π-stacking and XH/π interactions with the surrounding aromatic residues; hydrogen bonds play little role. These data suggest that a key Tyr residue, which is not present in other anti-DNA antibodies, plays a key role in the 5'-base selectivity, while we predict that the mutation of a single Trp residue can tune the selectivity for dTdC over dAdC.

Examination of tyrosine/adenine stacking interactions in protein complexes

The π-stacking interactions between tyrosine amino acid side chains and adenine-bearing ligands are examined. Crystalline protein structures from the protein data bank (PDB) exhibiting face-to-face tyrosine/adenine arrangements were used to construct 20 unique 4-methylphenol/N9-methyladenine (p-cresol/9MeA) model systems. Full geometry optimization of the 20 crystal structures with the M06-2X density functional theory method identified 11 unique low-energy conformations. CCSD(T) complete basis set (CBS) limit interaction energies were estimated for all of the structures to determine the magnitude of the interaction between the two ring systems. CCSD(T) computations with double-ζ basis sets (e.g., 6-31G*(0.25) and aug-cc-pVDZ) indicate that the MP2 method overbinds by as much as 3.07 kcal mol(-1) for the crystal structures and 3.90 kcal mol(-1) for the optimized structures. In the 20 crystal structures, the estimated CCSD(T) CBS limit interaction energy ranges from -4.00 to -6.83 kcal mol(-1), with an average interaction energy of -5.47 kcal mol(-1), values remarkably similar to the corresponding data for phenylalanine/adenine stacking interactions. Geometry optimization significantly increases the interaction energies of the p-cresol/9MeA model systems. The average estimated CCSD(T) CBS limit interaction energy of the 11 optimized structures is 3.23 kcal mol(-1) larger than that for the 20 crystal structures.

Significant strength of charged DNA-protein π-π interactions: a preliminary study of cytosine

The present work characterized the preferred gas-phase structure and optimum interaction energy of both parallel stacked and perpendicular T-shaped dimers between cytosine (C), as a representative nucleobase, and aspartic/glutamic acid (DE), aspartate/glutamate (DE(-)) or arginine (R(+)), using detailed M06-2X/6-31+G(d,p) potential energy surface scans as a function of the relative monomer orientation. Through comparison to previous literature on the π-π interactions between the DNA nucleobases and the aromatic amino acid residues, this work will allow for comparisons between DNA-protein interactions involving aromatic and acyclic R-side chains, as well as comparisons of the relative geometric dependence and magnitude of π-π (C:DE), πcation-π (C:R(+)), and πanion-π (C:DE(-)) interactions. Our results show that the preferred relative monomer orientation is highly dependent on the monomer composition and charge, and is dictated by electrostatic-driven interactions. More importantly, for the first time, we report that the π-π interactions between cytosine and (neutral) aspartic/glutamic acid are up to approximately -40 kJ mol(-1), while the πcation-π or πanion-π interactions between cytosine and arginine or aspartate/glutamate are up to approximately -90 and -99 kJ mol(-1), respectively. An extensive investigation of the effects of the computational methodology implemented, including comparisons to detailed CCSD(T)/CBS potential energy surfaces and interaction energies, supports the use of M06-2X, as well as ωB97X-D, to study DNA-protein π-π interactions of varying composition and charge. Most importantly, the CCSD(T)/CBS results verify the strong nature of these DNA-protein π-π interactions, as well as the unique nature of the πcation-π and πanion-π counterparts. Therefore, our results emphasize that a wide variety of different types of noncovalent interactions between both cyclic and acyclic π-containing components can significantly contribute to the stability of DNA-protein complexes and likely play a larger role in biology than currently accepted.

On the molecular basis of D-bifunctional protein deficiency type III

Molecular basis of D-bifunctional protein (D-BP) deficiency was studied with wild type and five disease-causing variants of 3R-hydroxyacyl-CoA dehydrogenase fragment of the human MFE-2 (multifunctional enzyme type 2) protein. Complementation analysis in vivo in yeast and in vitro enzyme kinetic and stability determinants as well as in silico stability and structural fluctuation calculations were correlated with clinical data of known patients. Despite variations not affecting the catalytic residues, enzyme kinetic performance (K(m), V(max) and k(cat)) of the recombinant protein variants were compromised to a varying extent and this can be judged as the direct molecular cause for D-BP deficiency. Protein stability plays an additional role in producing non-functionality of MFE-2 in case structural variations affect cofactor or substrate binding sites. Structure-function considerations of the variant proteins matched well with the available data of the patients.

JACOB: a dynamic database for computational chemistry benchmarking

JACOB (just a collection of benchmarks) is a database that contains four diverse benchmark studies, which in-turn included 72 data sets, with a total of 122,356 individual results. The database is constructed upon a dynamic web framework that allows users to retrieve data from the database via predefined categories. Additional flexibility is made available via user-defined text-based queries. Requested sets of results are then automatically presented as bar graphs, with parameters of the graphs being controllable via the URL. JACOB is currently available at www.wallerlab.org/jacob.

Basis set dependence of higher-order correlation effects in π-type interactions

The basis set dependence of higher-order correlation effects on π-type interaction energies was examined by scanning the potential energy surfaces of five dimer systems. The dimers of acetylene (H-C≡C-H), diacetylene (H-C≡C-C≡C-H), cyanogen (N≡C-C≡N), diphosphorous (P≡P), and 1,4-diphosphabutadiyne (P≡C-C≡P) were studied in three different configurations: cross, parallel-displaced, and t-shaped. More than 800 potential energy curves (PECs) were generated by computing the interaction energies for all 15 dimer configurations over a range of intermolecular distances with the MP2, coupled-cluster single double (CCSD), and coupled-cluster single double triple (CCSD(T)) methods in conjunction with 21 basis sets ranging from a small 6-31G*(0.25) split-valence basis set to a large aug-cc-pVQZ correlation consistent basis set. Standard extrapolation techniques were also used to construct MP2, CCSD, and CCSD(T) complete basis set (CBS) limit PECs as well as CBS limit higher-order correlation corrections based on the differences between CCSD(T) and MP2 interaction energies, denoted δ(MP2)(CCSD(T)), and the corresponding differences between CCSD(T) and CCSD interactions energies, denoted δ(CCSD)(CCSD(T)). Double-ζ basis sets struggled to reproduce the former but provided quite reasonable descriptions of the latter as long as diffuse functions were included. The aug-cc-pVDZ basis deviated from the δ(CCSD)(CCSD(T)) CBS limit by only 0.06 kcal mol(-1) on average and never by more than 0.24 kcal mol(-1), whereas the corresponding deviations were approximately twice that for the δ(MP2)(CCSD(T)) term. While triple-ζ basis sets typically improved results, only aug-cc-pVTZ provided appreciable improvement over utilizing the aug-cc-pVDZ basis set to compute δ(CCSD)(CCSD(T)). Counterpoise (CP) corrections were also applied to all double- and triple-ζ basis sets, but they rarely yielded a better description of these higher-order correlation effects. CP corrections only consistently improved results when the aug-cc-pVDZ basis set was used to compute δ(MP2)(CCSD(T)), yielding mean and maximum absolute deviations from the CBS values of 0.10 and 0.39 kcal mol(-1), respectively, for all five dimer systems.

Evaluating how discrete water molecules affect protein-DNA π-π and π(+)-π stacking and T-shaped interactions: the case of histidine-adenine dimers

Changes in the magnitude of (M06-2X/6-31+G(d,p)) π-π stacking and T-shaped (nucleobase-edge and amino acid-edge) interactions between (neutral or protonated) histidine (His) and adenine (A) dimers upon microsolvation with up to four discrete water molecules were determined. A variety of histidine-water interactions were considered including conventional (N-H···O, N···H-O, C-H···O) hydrogen bonding and nonconventional (X-H···π (neutral His) or lone-pair···π (protonated His)) contacts. Overall, the effects of discrete His-H(2)O interactions on the neutral histidine-adenine π-π contacts are negligible (<3 kJ mol(-1) or 15%) regardless of the type of water binding, the number of water molecules bound, or the His-A dimer (stacked or (amino acid- or nucleobase-edge) T-shaped) configuration. This suggests that previously reported gas-phase binding strengths for a variety of neutral amino acid-nucleobase dimers are likely relevant for a wide variety of (microsolvated) environments. In contrast, the presence of water decreases the histidine-adenine π(+)-π interaction by up to 15 kJ mol(-1) (or 30%) for all water binding modes and orientations, as well as different stacked and T-shaped His(+)-A dimers. Regardless of the larger effect of discrete histidine-water interactions on the magnitude of the π(+)-π compared with π-π interactions, the π(+)-π binding strengths remain substantially larger than the corresponding π-π contacts. These findings emphasize the distinct nature of π(+)-π and π-π interactions and suggest that π(+)-π contacts can provide significant stabilization in biological systems relative to π-π contacts under many different environmental conditions.

The intermolecular interactions in the aminonitromethylbenzenes

The intermolecular non-covalent interactions in aminonitromethylbenzenes namely 2-methyl-4-nitroaniline, 4-methyl-3-nitroaniline, 2-methyl-6-nitroaniline, 4-amino-2,6-dinitrotoluene, 2-methyl-5-nitroaniline, 4-methyl-2-nitroaniline, 2,3-dimethyl-6-nitroaniline, 4,5-dimethyl-2-nitroaniline and 2-methyl-3,5-dinitroaniline were studied by quantum mechanical calculations at RHF/311++G(3df,2p) and B3LYP/311++G(3df,2p) level of theory. The calculations prove that solely geometrical study of hydrogen bonding can be very misleading because not all short distances (classified as hydrogen bonds on the basis of interaction geometry) are bonding in character. For studied compounds interaction energy ranges from 0.23 kcal mol−1 to 5.59 kcal mol−1. The creation of intermolecular hydrogen bonds leads to charge redistribution in donors and acceptors. The Natural Bonding Orbitals analysis shows that hydrogen bonds are created by transfer of electron density from the lone pair orbitals of the H-bond acceptor to the antibonding molecular orbitals of the H-bond donor and Rydberg orbitals of the hydrogen atom. The stacking interactions are the interactions of delocalized molecular π-orbitals of the one molecule with delocalized antibonding molecular π-orbitals and the antibonding molecular σ-orbital created between the carbon atoms of the second aromatic ring and vice versa.

Effects of the biological backbone on stacking interactions at DNA-protein interfaces: the interplay between the backbone···π and π···π components

The (gas-phase) MP2/6-31G*(0.25) π···π stacking interactions between the five natural bases and the aromatic amino acids calculated using (truncated) monomers composed of conjugated rings and/or (extended) monomers containing the biological backbone (either the protein backbone or deoxyribose sugar) were previously compared. Although preliminary energetic results indicated that the protein backbone strengthens, while the deoxyribose sugar either strengthens or weakens, the interaction calculated using truncated models, the reasons for these effects were unknown. The present work explains these observations by dissecting the interaction energy of the extended complexes into individual backbone···π and π···π components. Our calculations reveal that the total interaction energy of the extended complex can be predicted as a sum of the backbone···π and π···π components, which indicates that the biological backbone does not significantly affect the ring system through π-polarization. Instead, we find that the backbone can indirectly affect the magnitude of the π···π contribution by changing the relative ring orientations in extended dimers compared with truncated dimers. Furthermore, the strengths of the individual backbone···π contributions are determined to be significant (up to 18 kJ mol(-1)). Therefore, the origin of the energetic change upon model extension is found to result from a balance between an additional (attractive) backbone···π component and differences in the strength of the π···π interaction. In addition, to understand the effects of the biological backbone on the stacking interactions at DNA-protein interfaces in nature, we analyzed the stacking interactions found in select DNA-protein crystal structures, and verified that an additive approach can be used to examine the strength of these interactions in biological complexes. Interestingly, although the presence of attractive backbone···π contacts is qualitatively confirmed using the quantum theory of atoms in molecules (QTAIM), QTAIM electron density analysis is unable to quantitatively predict the additive relationship of these interactions. Most importantly, this work reveals that both the backbone···π and π···π components must be carefully considered to accurately determine the overall stability of DNA-protein assemblies.

The assessment of density functionals for DNA–protein stacked and T-shaped complexes

The present work uses 129 nucleobase – amino acid CCSD(T)/CBS stacking and T-shaped interaction energies as reference data to test the ability of various density functionals with double-zeta quality basis sets, as well as some semi-empirical and molecular mechanics methods, to accurately describe noncovalent DNA–protein π–π and π+–π interactions. The goal of this work is to identify methods that can be used in hybrid approaches (QM/MM, ONIOM) for large-scale modeling of enzymatic systems involving active-site (substrate) π–π contacts. Our results indicate that AMBER is a more appropriate choice for the lower-level method in hybrid techniques than popular semi-empirical methods (AM1, PM3), and suggest that AMBER accurately describes the π–π interactions found throughout DNA–protein complexes. The M06–2X and PBE-D density functionals were found to provide very promising descriptions of the 129 nucleobase – amino acid interaction energies, which suggests that these may be the most suitable methods for describing high-level regions. Therefore, M06–2X and PBE-D with both the 6–31G(d) and 6–31+G(d,p) basis sets were further examined through potential-energy surface scans to better understand how these techniques describe DNA–protein π–π interactions in both minimum and nonminimum regions of the potential-energy surfaces, which is critical information when modeling enzymatic reaction pathways. Our results suggest that studies of stacked nucleobase – amino acid systems should implement the PBE-D/6–31+G(d,p) method. However, if T-shaped contacts are involved and (or) smaller basis sets must be considered due to limitations in computational resources, then M06–2X/6–31G(d) provides an overall excellent description of both nucleobase – amino acid stacking and T-shaped interactions for a range of DNA–protein π–π and π+–π interactions.

A preliminary investigation of the additivity of pi-pi or pi+-pi stacking and T-shaped interactions between natural or damaged DNA nucleobases and histidine

Previous computational studies have examined pi-pi and pi(+)-pi stacking and T-shaped interactions in nucleobase-amino acid dimers, yet it is important to investigate how additional amino acids affect these interactions since simultaneous contacts often appear in nature. Therefore, this paper investigates the geometries and binding strengths of amino acid-nucleobase-amino acid trimers, which are compared to the corresponding nucleobase-amino acid dimer interactions. We concentrate on systems containing the natural nucleobase adenine or its (cationic) damaged counterpart, 3-methyladenine, and the aromatic amino acid histidine, in both the neutral and protonated forms. This choice of molecules provides information about pi-pi and pi(+)-pi stacking and T-shaped interactions in asymmetric, biologically relevant systems. We determined that both stacked and T-shaped interactions, as well as both pi-pi and pi(+)-pi interactions, exhibit geometric additivity. To investigate the energetic additivity in our trimers, the synergy (E(syn)) and the additivity (E(add)) energy were examined. E(add) reveals that it is important to consider the interaction between the two amino acids when examining the additivity of nucleobase-amino acid interactions. Additionally, E(syn) and E(add) indicate that pi(+)-pi interactions are quite different from pi-pi interactions. The magnitude of E(add) is generally less than 2 kJ mol(-1), which suggests that these interactions are additive. However, the interaction energy analysis does not provide information about the individual interactions in the trimers. Therefore, the quantum theory of atoms in molecules (QTAIM) was implemented. We find inconsistent conclusions from our QTAIM analysis and interaction energy evaluation. However, the magnitudes of the differences between the dimer and trimer critical point properties are extremely small and therefore may not be able to yield conclusive descriptions of differences (if any) between the dimer and trimer interactions. We hypothesize that, due to the limited number of investigations of this type, it is currently unclear how QTAIM can improve our understanding of pi-pi and pi(+)-pi dimers and trimers. Therefore, future work must systematically alter the pi-pi or pi(+)-pi system to definitively determine how the geometry, symmetry, and system size alter the QTAIM analysis, which can then be used to understand biologically relevant complexes.

Effects of the biological backbone on DNA-protein stacking interactions

The pi-pi stacking (face-to-face) interactions between the five natural DNA or RNA nucleobases and the four aromatic amino acids were compared using three different types of dimers: (1) a truncated nucleoside (nucleobase) stacked with a truncated amino acid; (2) a truncated nucleoside (nucleobase) stacked with an extended amino acid; and (3) a nucleoside (extended nucleobase) stacked with a truncated amino acid. Systematic (MP2/6-31G*(0.25)) potential energy surface scans reveal important information about the effects of the deoxyribose sugar and protein backbone on the structure and binding energy between truncated nucleobase and amino acid models that are typically implemented in the literature. Most notably, electrostatic and steric interactions arising from the bulkiness of the biological backbones can change the preferred relative orientations of DNA and protein pi-systems. More importantly, the protein backbone can strengthen the stacking energy (by up to 10 kJ mol(-1)), while the deoxyribose moiety can strengthen or weaken the stacking interaction depending on the positioning of the amino acid relative to the sugar residue. These effects are likely due to additional interactions between the amino acid or nucleobase ring and the backbone in the extended monomer rather than significant changes in the properties of the biological pi-systems upon model extension. Since the present work reveals that all calculated DNA-protein stacking interactions are significant and approach the strength of other noncovalent interactions between biomolecules, both pi-pi and backbone-pi interactions must be considered when attempting to gain a complete picture of DNA-protein binding.