Multi-layer 3D Chirality and Double-Helical Assembly in a Copper Nanocluster with a Triple-Helical Cu15 Core.

Conceptually mimicking biomolecules' ability to construct multiple-helical aggregates with emergent properties and functions remains a long-standing challenge. Here we report an atom-precise 18-copper nanocluster (NC), Cu18 H(PET)14 (TPP)6 (NCS)3 (Cu18 H) which contains a pseudo D3 -symmetrical triple-helical Cu15 core. Structurally, Cu18 H may be also viewed as sandwich type of sulfur-bridged chiral copper cluster units [Cu6 -Cu6 -Cu6 ], endowing three-layered 3D chirality. More importantly, the chiral NCs are aggregated into an infinite double-stranded helix supported by intra-strand homonuclear C-H⋅⋅⋅H-C dihydrogen contacts and inter-strand C-H/π and C-H/S interactions. The unique multi-layered 3D chirality and the double-helical assembly of Cu18 H are evocative of DNA. Moreover, the collective behaviours of the aggregated NCs not only exhibit crystallization-induced emission enhancement (CIEE) and aggregation-induced emission enhancement (AIEE) effects in the deep-red region, but also efficiently catalyze electron transfer (ET) reaction. This study thus presents that hierarchical assemblies of atomically defined copper NCs could be intricate as observed for important biomolecules like DNA with emergent properties arising from aggregated behaviours.

Total Structure, Electronic Structure and Catalytic Hydrogenation Activity of Metal-Deficient Chiral Polyhydride Cu57 Nanoclusters.

Accurate identifying and in-depth understanding of the defect sites in a working nanomaterial could hinge on establishing specific defect-activity relationships. Yet, atomically precise coinage-metal nanoclusters (NCs) possessing surface vacancy defects are scarce primarily owing to challenges in the synthesis and isolation of such defective NCs. Herein we report a mixed-ligand strategy to synthesizing an intrinsically chiral and metal-deficient copper hydride-rich NC [Cu57 H20 (PET)36 (TPP)4 ]+ (Cu57 H20 ). Its total structure (including hydrides) and electronic structure are well established by combined experimental and computational results. Crystal structure reveals Cu57 H20 features a cube-like Cu8 kernel embedded in a corner-missing metal-ligand shell of Cu49 (PET)36 (TPP)4 . Single Cu vacancy defect site occurs at one corner of the shell, evocative of mono-lacunary polyoxometalates. Theoretical calculations demonstrate that the above-mentioned point vacancy causes one surface hydride exposed as an interfacial capping µ3 -H- , which is accessible in chemical reaction, as proved by deuterated experiment. Moreover, Cu57 H20 shows catalytic activity in the hydrogenation of nitroarene. The success of this work opens the way for the research on well-defined chiral metal-deficient Cu and other metal NCs, including exploring their application in asymmetrical catalysis.

Unusual Intramolecular Motion of ReH92- in K2ReH9 Crystal: Circle Dance and Three-Arm Turnstile Mechanisms Revealed by Computational Studies.

The nonahydridorhenate dianion ReH92- is a unique rhenium polyhydride complex due to its remarkably high coordination number; however, its detailed polytopal rearrangement process in either solution or crystal is so far unclear. In this work, our quantum chemical calculations have identified two previously unreported fluxional mechanisms for the ReH92- dianion in the K2ReH9 crystal: three-arm turnstile rotation and circle dance mechanism. These two polytopal rearrangements in the crystal offer an alternative interpretation to the pulse and wide-line NMR spectra (Farrar et al. J. Chem. Phys. 1969, 51, 3595). The previously postulated hindered rotation of the whole ReH92- dianion in K2ReH9 (White et al. J. Chem. Soc., Faraday Trans. 2 1972, 68, 1414) turns out to be a combination of the above-mentioned two elementary fluxional processes. In addition, our calculations have confirmed the Muetterties' D3h⇌C4v rearrangement as the intramolecular motion for the ReH92- dianion in solution.

Comment on "Exploring nature and predicting strength of hydrogen bonds: A correlation analysis between atoms-in-molecules descriptors, binding energies, and energy components of symmetry-adapted perturbation theory".

We evaluate the correlation between binding energy (BE) and electron density ρ(r) at the bond critical point for 28 neutral hydrogen bonds, recently reported by Emamian and co-workers (J. Comput. Chem., 2019, 40, 2868). As an efficient tool, we use local stretching force constant k HB a derived from the local vibrational mode theory of Konkoli and Cremer. We compare the physical nature of BE versus k HB a , and provide an important explanation for cases with significant deviation in the BE- k HB a relation as well as in the BE-ρ(r) correlation. We also show that care has to be taken when different hydrogen bond strength measures are compared. The BE is a cumulative hydrogen bond strength measure while k HB a is a local measure of hydrogen bond strength covering different aspects of bonding. A simplified and unified description of hydrogen bonding is not always possible and needs an in-depth understanding of the systems involved.

Theoretical Insights into [NHC]Au(I) Catalyzed Hydroalkoxylation of Allenes: A Unified Reaction Valley Approach Study.

Hydroxylation is an effective approach for the synthesis of carbon-oxygen bonds and allylic ethers. The [NHC]Au(I) catalyzed intermolecular hydroalkoxylation of allene was studied at the DFT and Coupled Cluster level of theory. Using the Unified Reaction Valley Approach (URVA), we carry out a comprehensive mechanistic analysis of [NHC]Au(I)-catalyzed and noncatalyzed reactions. The URVA study of several possible reaction pathways reveal that the [NHC]Au(I) catalyst enables the hydroalkoxylation reaction to occur via a two step mechanism based upon the Au ability to switch between π- and σ-complexation. The first step of the mechanism involves the formation of a CO bond after the transition state with no energy penalty. Following the CO bond breakage, the OH bond breaks and CH bond forms during the second step of the mechanism, as the catalyst transforms into the more stable π-Au complex. The URVA results were complemented with local vibrational mode analysis to provide measures of intrinsic bond strength for Au(I)-allene interactions of all stationary points, and NBO analysis was applied in order to observe charge transfer events along the reaction pathway. Overall, the π-Au C═C interactions of the products are stronger than those of the reactants adding to their exothermicity. Our work on the hydroxylation of allene provides new insights for the design of effective reaction pathways to produce allylic ethers and also unravels new strategies to form C-O bonds by activation of C═C bonds.

Describing Polytopal Rearrangement Processes of Octacoordinate Structures. I. Renewed Insights into Fluxionality of the Rhenium Polyhydride Complex ReH5(PPh3)2(Pyridine).

Hydride ligands of transition metal polyhydride complexes with a high coordination number are prone to fluxionality leading to interesting structural dynamics. However, the underlying polytopal rearrangement pathways have been rarely studied. Based on quantum chemical calculations carried out in this work with density functional theory and coupled-cluster theory, two new fluxional mechanisms have been identified for the rhenium polyhydride complex ReH5(PPh3)2(pyridine) to jointly account for two consecutive coalescence events in the variable-temperature NMR spectra upon heating: lateral and basal three-arm turnstile rotation. The frequently cited pseudorotation in ReH5(PPh3)2(pyridine) (Lee et al. Inorg. Chem. 1996, 35, 695) turns out to be a three-step process including two lateral three-arm turnstile steps and one basal turnstile step in between. The new fluxional mechanisms discovered in this work may also exist in other transition metal polyhydrides.

A revised formulation of the generalized subsystem vibrational analysis (GSVA).

In this work, a simplified formulation of our recently developed generalized subsystem vibrational analysis (GSVA) for obtaining intrinsic fragmental vibrations (J Chem Theory Comput 14:2558, 2018) is presented. In contrast to the earlier implementation, which requires the explicit definition of a non-redundant set of internal coordinate parameters to be constructed for the subsystem, the new implementation circumvents this process by employing massless Eckart conditions to the subsystem fragment paired with a Gram-Schmidt orthogonalization to span the same internal vibration space indirectly. This revised version of GSVA (rev-GSVA) can be applied to equilibrium structure as well as transition state structure, and it has been incorporated into the open-source package UniMoVib (https://github.com/zorkzou/UniMoVib). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00214-021-02727-y.

SSnet: A Deep Learning Approach for Protein-Ligand Interaction Prediction.

Computational prediction of Protein-Ligand Interaction (PLI) is an important step in the modern drug discovery pipeline as it mitigates the cost, time, and resources required to screen novel therapeutics. Deep Neural Networks (DNN) have recently shown excellent performance in PLI prediction. However, the performance is highly dependent on protein and ligand features utilized for the DNN model. Moreover, in current models, the deciphering of how protein features determine the underlying principles that govern PLI is not trivial. In this work, we developed a DNN framework named SSnet that utilizes secondary structure information of proteins extracted as the curvature and torsion of the protein backbone to predict PLI. We demonstrate the performance of SSnet by comparing against a variety of currently popular machine and non-Machine Learning (ML) models using various metrics. We visualize the intermediate layers of SSnet to show a potential latent space for proteins, in particular to extract structural elements in a protein that the model finds influential for ligand binding, which is one of the key features of SSnet. We observed in our study that SSnet learns information about locations in a protein where a ligand can bind, including binding sites, allosteric sites and cryptic sites, regardless of the conformation used. We further observed that SSnet is not biased to any specific molecular interaction and extracts the protein fold information critical for PLI prediction. Our work forms an important gateway to the general exploration of secondary structure-based Deep Learning (DL), which is not just confined to protein-ligand interactions, and as such will have a large impact on protein research, while being readily accessible for de novo drug designers as a standalone package.

Inverse folding with RNA-As-Graphs produces a large pool of candidate sequences with target topologies.

We present an RNA-As-Graphs (RAG) based inverse folding algorithm, RAG-IF, to design novel RNA sequences that fold onto target tree graph topologies. The algorithm can be used to enhance our recently reported computational design pipeline (Jain et al., NAR 2018). The RAG approach represents RNA secondary structures as tree and dual graphs, where RNA loops and helices are coarse-grained as vertices and edges, opening the usage of graph theory methods to study, predict, and design RNA structures. Our recently developed computational pipeline for design utilizes graph partitioning (RAG-3D) and atomic fragment assembly (F-RAG) to design sequences to fold onto RNA-like tree graph topologies; the atomic fragments are taken from existing RNA structures that correspond to tree subgraphs. Because F-RAG may not produce the target folds for all designs, automated mutations by RAG-IF algorithm enhance the candidate pool markedly. The crucial residues for mutation are identified by differences between the predicted and the target topology. A genetic algorithm then mutates the selected residues, and the successful sequences are optimized to retain only the minimal or essential mutations. Here we evaluate RAG-IF for 6 RNA-like topologies and generate a large pool of successful candidate sequences with a variety of minimal mutations. We find that RAG-IF adds robustness and efficiency to our RNA design pipeline, making inverse folding motivated by graph topology rather than secondary structure more productive.

Correction to: Effects of probiotics on type II diabetes mellitus: a meta-analysis.

Following publication of the original article [1], the authors reported an error in one of the author names. In this Correction the incorrect and correct author names are listed.

Effects of probiotics on type II diabetes mellitus: a meta-analysis.

OBJECTIVE: The purpose of the present study was to evaluate the effectiveness of probiotics on type II diabetes mellitus (T2DM). METHODS: We performed a comprehensive search on PubMed, Web of Science, China National Knowledge Infrastructure, Chinese Scientific Journal Databases, Wan Fang database and China biology medicine disc for relevant studies published before June 2019. Glycated hemoglobin A1c (HbA1c), homeostasis model assessment of insulin resistance (HOMA-IR) and fasting blood glucose (FBG) were used as indicators for T2DM. Inverse-variance weighted mean difference (WMD) with 95% confidence interval (CI) was calculated for the mean HbA1c, FBG and HOMA-IR changes from baseline. RESULTS: 15 randomized controlled trials (RCT) with a total of 902 participants were included into the meta-analysis. Considering the clinical heterogeneity caused by variation of dosage and duration of probiotic treatment, random-effects model was used to estimate the pooled WMD. Significantly greater reduction in HbA1c% (WMD = - 0.24, 95% CI [- 0.44, - 0.04], p = 0.02), FBG (WMD = - 0.44 mmol/L, 95% CI [- 0.74, - 0.15], p = 0.003) and HOMA-IR (WMD = - 1.07, 95% CI [- 1.58, - 0.56], p < 0.00001) were observed in probiotics treated group. Further sensitivity analysis verified the reliability and stability of our results. CONCLUSION: The results of our meta-analysis indicated that probiotics treatment may reduce HbA1c, FBG and insulin resistance level in T2DM patients. More clinical data and research into the mechanism of probiotics are needed to clarify the role of probiotics in T2DM.

Modeling Hydrogen Release from Water with Borane and Alane Catalysts: A Unified Reaction Valley Approach.

The unified reaction valley approach combined with the local vibrational mode and ring puckering analysis is applied to investigate the hydrogen evolution from water in the presence of small hydrides such as BH3, metal hydrides as AlH3, and their derivatives. We studied a series of reactions involving BH3, AlH3, B2H6, Al2H6, and AlH3BH3 with one- and two-water molecules, considering multiple reaction paths. In addition, the influence of the aqueous medium was examined. A general reaction mechanism was identified for most of the reactions. Those that deviate could be associated with unusually high reaction barriers with no hydrogen release. The charge transfer along the reaction path suggests that a viable hydrogen release is achieved when the catalyst adopts the role of a charge donor during the chemical processes. The puckering analysis showed that twistboat and boat forms are the predominant configurations in the case of an intermediate six-membered ring formation, which influences the activation barrier. The local mode analysis was used as a tool to detect the H-H bond formation as well as to probe catalyst regenerability. Based on the correlation between the activation energy and the change in the charge separation for cleaving O-H and B(Al)-H bonds, two promising subsets of reactions could be identified along with prescriptions for lowering the reaction barrier individually with electron-donating/withdrawing substituents.

Systematic description of molecular deformations with Cremer-Pople puckering and deformation coordinates utilizing analytic derivatives: Applied to cycloheptane, cyclooctane, and cyclo[18]carbon.

The conformational properties of ring compounds such as cycloalkanes determine to a large extent their stability and reactivity. Therefore, the investigation of conformational processes such as ring inversion and/or ring pseudorotation has attracted a lot of attention over the past decades. An in-depth conformational analysis of ring compounds requires mapping the relevant parts of the conformational energy surface at stationary and also at non-stationary points. However, the latter is not feasible by a description of the ring with Cartesian or internal coordinates. We provide in this work, a solution to this problem by introducing a new coordinate system based on the Cremer-Pople puckering and deformation coordinates. Furthermore, analytic first- and second-order derivatives of puckering and deformation coordinates, i.e., B-matrices and D-tensors, were developed simplifying geometry optimization and frequency calculations. The new coordinate system is applied to map the potential energy surfaces and reaction paths of cycloheptane (C7H14), cyclooctane (C8H16), and cyclo[18]carbon (C18) at the quantum chemical level and to determine for the first time all stationary points of these ring compounds in a systematic way.

A Critical Evaluation of Vibrational Stark Effect (VSE) Probes with the Local Vibrational Mode Theory.

Over the past two decades, the vibrational Stark effect has become an important tool to measure and analyze the in situ electric field strength in various chemical environments with infrared spectroscopy. The underlying assumption of this effect is that the normal stretching mode of a target bond such as CO or CN of a reporter molecule (termed vibrational Stark effect probe) is localized and free from mass-coupling from other internal coordinates, so that its frequency shift directly reflects the influence of the vicinal electric field. However, the validity of this essential assumption has never been assessed. Given the fact that normal modes are generally delocalized because of mass-coupling, this analysis was overdue. Therefore, we carried out a comprehensive evaluation of 68 vibrational Stark effect probes and candidates to quantify the degree to which their target normal vibration of probe bond stretching is decoupled from local vibrations driven by other internal coordinates. The unique tool we used is the local mode analysis originally introduced by Konkoli and Cremer, in particular the decomposition of normal modes into local mode contributions. Based on our results, we recommend 31 polyatomic molecules with localized target bonds as ideal vibrational Stark effect probe candidates.

In Situ Assessment of Intrinsic Strength of X-I⋯OA-Type Halogen Bonds in Molecular Crystals with Periodic Local Vibrational Mode Theory.

Periodic local vibrational modes were calculated with the rev-vdW-DF2 density functional to quantify the intrinsic strength of the X-I⋯OA-type halogen bonding (X = I or Cl; OA: carbonyl, ether and N-oxide groups) in 32 model systems originating from 20 molecular crystals. We found that the halogen bonding between the donor dihalogen X-I and the wide collection of acceptor molecules OA features considerable variations of the local stretching force constants (0.1-0.8 mdyn/Å) for I⋯O halogen bonds, demonstrating its powerful tunability in bond strength. Strong correlations between bond length and local stretching force constant were observed in crystals for both the donor X-I bonds and I⋯O halogen bonds, extending for the first time the generalized Badger's rule to crystals. It is demonstrated that the halogen atom X controlling the electrostatic attraction between the σ -hole on atom I and the acceptor atom O dominates the intrinsic strength of I⋯O halogen bonds. Different oxygen-containing acceptor molecules OA and even subtle changes induced by substituents can tweak the n → σ ∗ (X-I) charge transfer character, which is the second important factor determining the I⋯O bond strength. In addition, the presence of the second halogen bond with atom X of the donor X-I bond in crystals can substantially weaken the target I⋯O halogen bond. In summary, this study performing the in situ measurement of halogen bonding strength in crystalline structures demonstrates the vast potential of the periodic local vibrational mode theory for characterizing and understanding non-covalent interactions in materials.

A Sodalite-Type Silver Orthophosphate Cluster in a Globular Silver Nanocluster.

The synthesis and structure of a giant 102-silver-atom nanocluster (NC) 1 is presented. X-ray structural analysis reveals that 1 features a multi-shelled metallic core of Ag6 @Ag24 @Ag60 @Ag12 . An octahedral Ag6 core is encaged by a truncated octahedral Ag24 shell. The Ag24 shell is composed of a hitherto unknown sodalite-type silver orthophosphate cluster (SOC) {(Ag3 PO4 )8 }, reminiscent of the Ag3 PO4 photocatalyst. The SOC is capped by six interstitial sulfur atoms, giving a unique anionic cluster [Ag6 @{(Ag3 PO4 )8 }S6 ]6- , which functions as an intricate polyhedral template with abundant surface O and S atoms guiding the formation of a rare rhombicosidodecahedral Ag60 shell. An array of 6 linear Ag2 staples further surround this Ag60 shell. [Ag6 @{(Ag3 PO4 )8 }S6 ]6- is an unusual Ag-based templating anion to induce the assembly of a SOC within silver NC. This finding provides molecular models for bulk Ag3 PO4 , and offers a fresh template strategy for the synthesis of silver NCs with high symmetry.

Correlating the vibrational spectra of structurally related molecules: A spectroscopic measure of similarity.

Using catastrophe theory and the concept of a mutation path, an algorithm is developed that leads to the direct correlation of the normal vibrational modes of two structurally related molecules. The mutation path is defined by weighted incremental changes in mass and geometry of the molecules in question, which are successively applied to mutate a molecule into a structurally related molecule and thus continuously converting their normal vibrational spectra from one into the other. Correlation diagrams are generated that accurately relate the normal vibrational modes to each other by utilizing mode-mode overlap criteria and resolving allowed and avoided crossings of vibrational eigenstates. The limitations of normal mode correlation, however, foster the correlation of local vibrational modes, which offer a novel vibrational measure of similarity. It will be shown how this will open new avenues for chemical studies. © 2017 Wiley Periodicals, Inc.

The Difference Se Makes: A Bio-Inspired Dppf-Supported Nickel Selenolate Complex Boosts Dihydrogen Evolution with High Oxygen Tolerance.

Inspired by the metal active sites of [NiFeSe]-hydrogenases, a dppf-supported nickel(II) selenolate complex (dppf=1,1'-bis(diphenylphosphino)ferrocene) shows high catalytic activity for electrochemical proton reduction with a remarkable enzyme-like H2 evolution turnover frequency (TOF) of 7838 s-1 under an Ar atmosphere, which markedly surpasses the activity of a dppf-supported nickel(II) thiolate analogue with a low TOF of 600 s-1 . A combined study of electrochemical experiments and DFT calculations shed light on the catalytic process, suggesting that selenium atom as a bio-inspired proton relay plays a key role in proton exchange and enhancing catalytic activity of H2 production. For the first time, this type of Ni selenolate-containing electrocatalyst displays a high degree of O2 and H2 tolerance. Our results should encourage the development of the design of highly efficient oxygen-tolerant Ni selenolate molecular catalysts.

Occurrence, Impact, Analysis and Treatment of Metformin and Guanylurea in Coastal Aquatic Environments of Canada, USA and Europe.

This review discusses the occurrence, impact, analysis and treatment of metformin and guanylurea in coastal aquatic environments of Canada, USA and Europe. Metformin, a biguanide in chemical classification, is widely used as one of the most effective first-line oral drugs for type 2 diabetes. It is difficult to be metabolized by the human body and exists in both urine and faeces samples in these regions. Guanylurea is metformin's biotransformation product. Consequently, significant concentrations of metformin and guanylurea have been reported in wastewater treatment plants (WWTPs) and coastal aquatic environments. The maximum concentrations of metformin and guanylurea in surface water samples were as high as 59,000 and 4502ngL-1, respectively. Metformin can be absorbed in non-target organisms by plants and in Atlantic salmon (Salmo salar). Guanylurea has a confirmed mitotic activity in plant cells. Analysis methods of metformin are currently developed based on high-performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS). The removal of metformin from aquatic environments in the target regions is summarized. The review helps to fill a knowledge gap and provides insights for regulatory considerations. The potential options for managing these emerging pollutants are outlined too.