Occurrence and stability of lone pair-π stacking interactions between ribose and nucleobases in functional RNAs.

The specific folding pattern and function of RNA molecules lies in various weak interactions, in addition to the strong base-base pairing and stacking. One of these relatively weak interactions, characterized by the stacking of the O4' atom of a ribose on top of the heterocycle ring of a nucleobase, has been known to occur but has largely been ignored in the description of RNA structures. We identified 2015 ribose-base stacking interactions in a high-resolution set of non-redundant RNA crystal structures. They are widespread in structured RNA molecules and are located in structural motifs other than regular stems. Over 50% of them involve an adenine, as we found ribose-adenine contacts to be recurring elements in A-minor motifs. Fewer than 50% of the interactions involve a ribose and a base of neighboring residues, while approximately 30% of them involve a ribose and a nucleobase at least four residues apart. Some of them establish inter-domain or inter-molecular contacts and often implicate functionally relevant nucleotides. In vacuo ribose-nucleobase stacking interaction energies were calculated by quantum mechanics methods. Finally, we found that lone pair-π stacking interactions also occur between ribose and aromatic amino acids in RNA-protein complexes.

Introducing a Clustering Step in a Consensus Approach for the Scoring of Protein-Protein Docking Models.

Correctly scoring protein-protein docking models to single out native-like ones is an open challenge. It is also an object of assessment in CAPRI (Critical Assessment of PRedicted Interactions), the community-wide blind docking experiment. We introduced in the field the first pure consensus method, CONSRANK, which ranks models based on their ability to match the most conserved contacts in the ensemble they belong to. In CAPRI, scorers are asked to evaluate a set of available models and select the top ten ones, based on their own scoring approach. Scorers' performance is ranked based on the number of targets/interfaces for which they could provide at least one correct solution. In such terms, blind testing in CAPRI Round 30 (a joint prediction round with CASP11) has shown that critical cases for CONSRANK are represented by targets showing multiple interfaces or for which only a very small number of correct solutions are available. To address these challenging cases, CONSRANK has now been modified to include a contact-based clustering of the models as a preliminary step of the scoring process. We used an agglomerative hierarchical clustering based on the number of common inter-residue contacts within the models. Two criteria, with different thresholds, were explored in the cluster generation, setting either the number of common contacts or of total clusters. For each clustering approach, after selecting the top (most populated) ten clusters, CONSRANK was run on these clusters and the top-ranked model for each cluster was selected, in the limit of 10 models per target. We have applied our modified scoring approach, Clust-CONSRANK, to SCORE_SET, a set of CAPRI scoring models made recently available by CAPRI assessors, and to the subset of homodimeric targets in CAPRI Round 30 for which CONSRANK failed to include a correct solution within the ten selected models. Results show that, for the challenging cases, the clustering step typically enriches the ten top ranked models in native-like solutions. The best performing clustering approaches we tested indeed lead to more than double the number of cases for which at least one correct solution can be included within the top ten ranked models.

Troubles in the Systematic Prediction of Transition Metal Thermochemistry with Contemporary Out-of-the-Box Methods.

The recently developed DLPNO-CCSD(T) method and seven popular DFT functionals (B3LYP, M06, M06L, PBE, PBE0, TPSS, and TPSSh) with and without an empirical dispersion term have been tested to reproduce 111 gas phase reaction enthalpies involving 11 different transition metals. Our calculations, corrected for both relativistic effects and basis set incompleteness, indicate that most of the methods applied with default settings perform with acceptable accuracy on average. Nevertheless, our calculations also evidenced unexpected and nonsystematic large deviations for specific cases. For group 12 metals (Zn, Cd, Hg), most of the methods provided mean unsigned errors (MUE) less than 5.0 kcal/mol, with DLPNO-CCSD(T) and PBE methods performing excellently (MUE lower 2.0 kcal/mol). Problems started with group 4 metals (Ti and Zr). The best performer for Zr complexes with MUE of 1.8 kcal/mol, PBE0-D3, provides MUE larger than 8 kcal/mol for Ti. DLPNO-CCSD(T) provides a reasonable MUE of 3.3 kcal/mol for Ti reactions but gives MUE a larger than 14.4 kcal/mol for Zr complexes, with all the larger deviations for reactions involving ZrF4. Large and nonsystematic errors have been obtained for group 6 metals (Mo and W), for eight reactions containing Fe, Cu, Nb, and Re complexes. Finally, for the whole set of 111 reactions, the DLPNO-CCSD(T), B3LYP-D3, and PBE0-D3 methods turned out to be the best performers, all providing MUE below 5.0 kcal/mol. Since DFT results cannot be systematically improved and large nonsystematic deviations of 20-30 kcal/mol were obtained even for best performers, our results indicate that current DFT methods are still unable to provide robust predictions in transition metal thermochemistry, at least for the functionals explored in this work. The same conclusion holds for both DLPNO-CCSD(T) and canonical CCSD(T) methods when used entirely as out-of-the-box. However, if careful investigation of core correlation is performed, relativistic effects are properly included and the quality of the reference wave function is properly checked, CCSD(T) methods can still provide good quality results that might even be used to validate DFT methods due to paucity of accurate thermodynamic data for realistic-sized transition metal complexes.

Solid-State NMR and DFT Studies on the Formation of Well-Defined Silica-Supported Tantallaaziridines: From Synthesis to Catalytic Application.

Single-site, well-defined, silica-supported tantallaaziridine intermediates [≡Si-O-Ta(η(2) -NRCH2 )(NMe2 )2 ] [R=Me (2), Ph (3)] were prepared from silica-supported tetrakis(dimethylamido)tantalum [≡Si-O-Ta(NMe2 )4 ] (1) and fully characterized by FTIR spectroscopy, elemental analysis, and (1) H,(13) C HETCOR and DQ TQ solid-state (SS) NMR spectroscopy. The formation mechanism, by ß-H abstraction, was investigated by SS NMR spectroscopy and supported by DFT calculations. The C-H activation of the dimethylamide ligand is favored for R=Ph. The results from catalytic testing in the hydroaminoalkylation of alkenes were consistent with the N-alkyl aryl amine substrates being more efficient than N-dialkyl amines.

Theoretical Characterization of the H-Bonding and Stacking Potential of Two Nonstandard Nucleobases Expanding the Genetic Alphabet.

We report a quantum chemical characterization of the non-natural (synthetic) H-bonded base pair formed by 6-amino-5-nitro-2(1H)-pyridone (Z) and 2-aminoimidazo[1,2-a]-1,3,5-triazin-4(8H)-one (P). The Z:P base pair, orthogonal to the classical G:C base pair, has been introduced into DNA molecules to expand the genetic code. Our results indicate that the Z:P base pair closely mimics the G:C base pair in terms of both structure and stability. To clarify the role of the NO2 group on the C5 position of the Z base, we compared the stability of the Z:P base pair with that of base pairs having different functional groups at the C5 position of Z. Our results indicate that the electron-donating/-withdrawing properties of the group on C5 have a clear impact on the stability of the Z:P base pair, with the strong electron-withdrawing nitro group achieving the largest stabilizing effect on the H-bonding interaction and the strong electron-donating NH2 group destabilizing the Z:P pair by almost 4 kcal/mol. Finally, our gas-phase and in-water calculations confirm that the Z-nitro group reinforces the stacking interaction with its adjacent purine or pyrimidine ring.

The D173G mutation in ADAMTS-13 causes a severe form of congenital thrombotic thrombocytopenic purpura. A clinical, biochemical and in silico study.

Congenital thrombotic thrombocytopenic purpura (TTP) is a rare form of thrombotic microangiopathy, inherited with autosomal recessive mode as a dysfunction or severe deficiency of ADAMTS-13 (A Disintegrin And Metalloprotease with ThromboSpondin 1 repeats Nr. 13), caused by mutations in the ADAMTS-13 gene. About 100 mutations of the ADAMTS-13 gene were identified so far, although only a few characterised by in vitro expression studies. A new Asp to Gly homozygous mutation at position 173 of ADAMTS-13 sequence was identified in a family of Romanian origin, with some members affected by clinical signs of TTP. In two male sons, this mutation caused a severe (< 3%) deficiency of ADAMTS-13 activity and antigen level, associated with periodic thrombocytopenia, haemolytic anaemia and mild mental confusion. Both parents, who are cousins, showed the same mutation in heterozygous form. Expression studies of the mutant ADAMTS-13, performed in HEK293 cells, showed a severe decrease of the enzyme's activity and secretion, although the protease was detected inside the cells. Molecular dynamics found that in the D173G mutant the interface area between the metalloprotease domain and the disintegrin-like domain significantly decreases during the simulations, while the proline-rich 20 residues linker region (LR, 285-304) between them undergoes extensive conformational changes. Inter-domain contacts are also significantly less conserved in the mutant compared to the wild-type. Both a decrease of the inter-domain contacts along with a substantial conformational rearrangement of LR interfere with the proper maturation and folding of the mutant ADAMTS-13, thus impairing its secretion.

Accuracy of DLPNO-CCSD(T) method for noncovalent bond dissociation enthalpies from coinage metal cation complexes.

The performance of the domain based local pair-natural orbital coupled-cluster (DLPNO-CCSD(T)) method has been tested to reproduce the experimental gas phase ligand dissociation enthalpy in a series of Cu(+), Ag(+), and Au(+) complexes. For 33 Cu(+)-noncovalent ligand dissociation enthalpies, all-electron calculations with the same method result in MUE below 2.2 kcal/mol, although a MSE of 1.4 kcal/mol indicates systematic underestimation of the experimental values. Inclusion of scalar relativistic effects for Cu either via effective core potential (ECP) or Douglass-Kroll-Hess Hamiltonian, reduces the MUE below 1.7 kcal/mol and the MSE to -1.0 kcal/mol. For 24 Ag(+)-noncovalent ligand dissociation enthalpies, the DLPNO-CCSD(T) method results in a mean unsigned error (MUE) below 2.1 kcal/mol and vanishing mean signed error (MSE). For 15 Au(+)-noncovalent ligand dissociation enthalpies, the DLPNO-CCSD(T) methods provides larger MUE and MSE, equal to 3.2 and 1.7 kcal/mol, which might be related to poor precision of the experimental measurements. Overall, for the combined data set of 72 coinage metal ion complexes, DLPNO-CCSD(T) results in a MUE below 2.2 kcal/mol and an almost vanishing MSE. As for a comparison with computationally cheaper density functional theory (DFT) methods, the routinely used M06 functional results in MUE and MSE equal to 3.6 and -1.7 kcal/mol. Results converge already at CC-PVTZ quality basis set, making highly accurate DLPNO-CCSD(T) estimates affordable for routine calculations (single-point) on large transition metal complexes of >100 atoms.

Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps.

In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a consequence, the screening of many docking models is usually required in the analysis step, to possibly single out the correct ones. Here, making use of exemplary cases, we review our recently introduced methods for the analysis of protein complex structures and for the scoring of protein docking poses, based on the use of inter-residue contacts and their visualization in inter-molecular contact maps. We also show that the ensemble of tools we developed can be used in the context of rational drug design targeting protein-protein interactions.

CONSRANK: a server for the analysis, comparison and ranking of docking models based on inter-residue contacts.

SUMMARY: Herein, we present CONSRANK, a web tool for analyzing, comparing and ranking protein-protein and protein-nucleic acid docking models, based on the conservation of inter-residue contacts and its visualization in 2D and 3D interactive contact maps. AVAILABILITY AND IMPLEMENTATION: CONSRANK is accessible as a public web tool at https://www.molnac.unisa.it/BioTools/consrank/. CONTACT: romina.oliva@uniparthenope.it.

Molecular dynamics characterization of five pathogenic Factor X mutants associated with decreased catalytic activity.

Factor X (FX) is one of the major players in the blood coagulation cascade. Upon activation to FXa, it converts prothrombin to thrombin, which in turn converts fibrinogen into fibrin (blood clots). FXa deficiency causes hemostasis defects, such as intracranial bleeding, hemathrosis, and gastrointestinal blood loss. Herein, we have analyzed a pool of pathogenic mutations, located in the FXa catalytic domain and directly associated with defects in enzyme catalytic activity. Using chymotrypsinogen numbering, they correspond to D102N, T135M, V160A, G184S, and G197D. Molecular dynamics simulations were performed for 1.68 µs on the wild-type and mutated forms of FXa. Overall, our analysis shows that four of the five mutants considered, D102N, T135M, V160A, and G184S, have rigidities higher than those of the wild type, in terms of both overall protein motion and, specifically, subpocket S4 flexibility, while S1 is rather insensitive to the mutation. This acquired rigidity can clearly impact the substrate recognition of the mutants.

MDcons: Intermolecular contact maps as a tool to analyze the interface of protein complexes from molecular dynamics trajectories.

BACKGROUND: Molecular Dynamics (MD) simulations of protein complexes suffer from the lack of specific tools in the analysis step. Analyses of MD trajectories of protein complexes indeed generally rely on classical measures, such as the RMSD, RMSF and gyration radius, conceived and developed for single macromolecules. As a matter of fact, instead, researchers engaged in simulating the dynamics of a protein complex are mainly interested in characterizing the conservation/variation of its biological interface. RESULTS: On these bases, herein we propose a novel approach to the analysis of MD trajectories or other conformational ensembles of protein complexes, MDcons, which uses the conservation of inter-residue contacts at the interface as a measure of the similarity between different snapshots. A "consensus contact map" is also provided, where the conservation of the different contacts is drawn in a grey scale. Finally, the interface area of the complex is monitored during the simulations. To show its utility, we used this novel approach to study two protein-protein complexes with interfaces of comparable size and both dominated by hydrophilic interactions, but having binding affinities at the extremes of the experimental range. MDcons is demonstrated to be extremely useful to analyse the MD trajectories of the investigated complexes, adding important insight into the dynamic behavior of their biological interface. CONCLUSIONS: MDcons specifically allows the user to highlight and characterize the dynamics of the interface in protein complexes and can thus be used as a complementary tool for the analysis of MD simulations of both experimental and predicted structures of protein complexes.