We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy.

Accuracy of the DLPNO-CCSD(T) method for non-covalent bond dissociation enthalpies from coinage metal cation complexes Just Accepted "Just Accepted" manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides "Just Accepted" as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. "Just Accepted" manuscripts appear in full in PDF format accompanied by an HTML abstract. "Just Accepted" manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). "Just Accepted" is an optional service offered to authors. Therefore, the "Just Accepted" Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the "Just Accepted" Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these "Just Accepted" manuscripts. and -1.7 kca/mol. Results converge already at CC-PVTZ quality basis set, making highly accurate DLPNO-CCSD(T) estimates to be affordable for routine calculations (single-point) on large transition metal complexes of > 100 atoms. KAUST Repository IntroductionComputational chemistry is routinely applied nowadays to support and integrate experimental studies in transition-metal catalysis. [1][2][3][4][5][6][7] The successful standalone experimental-free theoretical predictions in this field are far less common, however. 8 While some failures in theoretical predictions are originated from the complexity of the systems themselves and can be ameliorated by proper inclusion of the effects deriving from incomplete sampling of the conformational space and/or solvation, 1,9 the other failures are related to the accuracy of electronic structure methods. In general, scalar/vector relativistic effects, basis set completeness and multireference character of some systems should be properly addressed regardless on the electronic structure method used. [10][11] When it comes specifically to density functional theory (DFT) methods, which is the only affordable computational protocol to study systems of "realistic-size", one has to remember that the performance of the underlying exchange-correlation (XC) functionals is not uniform, and provides low to high accuracy predictions depending on the chemical system under study. 12 The careful "calibration" against highly accurate experimental measurements or wave On the other hand, so-called "ab initio" WFT methods 28 are rigorous and allow to systematic...

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.

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.

romina.oliva@uniparthenope.it.

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.

BackgroundMolecular 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.ResultsOn 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.ConclusionsMDcons 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.

Abstract: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.