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Single crystals of mechanically entwined helical covalent polymers

Double helical conformation of polymer chains is widely observed in biomacromolecules and plays an essential role in exerting their biological functions, such as molecular recognition and information storage. It has remained challenging, however, to prepare synthetic helical polymers, and those that exist have mainly been limited to single-stranded polymers or short oligomeric double helices. In this work, we report the synthesis of covalent helical polymers, with a high molecular weight, from the achiral monomer hexahydroxytriphenylene through to spiroborate formation. Polymerization and crystallization occurred simultaneously under solvothermal conditions to form single crystals of the resulting helical covalent polymers. Characterization by single-crystal X-ray diffraction showed that each crystal consisted of pairs of mechanically entwined polymers. No strong non-covalent interactions were observed between the two helical polymers that formed a pair; instead, each strand interacted with neighbouring pairs through hydrogen bonding. Each individual crystal was made up of helical polymers of the same handedness, but the crystallization process produced a racemic conglomerate, with equal amounts of right-handed and left-handed crystals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Construction of nano slow-release systems for antibacterial active substances and its applications: A comprehensive review

At present, nano-carrier materials with antibacterial activity are of great significance. Due to the widespread resistance of many pathogenic microorganisms, it has seriously threatened human health. The natural antimicrobial substances extracted from fruits and vegetables can significantly improve their stability combined with nano-carrier materials. The resistance of pathogenic microorganisms will be substantially reduced, greatly enhancing the effect of active antimicrobial substances. Nanotechnology has excellent research prospects in the food industry, antibacterial preservation, food additives, food packaging, and other fields. This paper introduces nano-carrier materials and preparation techniques for loading and encapsulating active antibacterial substances in detail by constructing a nano-release system for active antibacterial substances. The antibacterial effect can be achieved by protecting them from adverse external conditions and destroying the membrane of pathogenic microorganisms. The mechanism of the slow release of the bacteriostatic active substance is also described. The mechanism of carrier loading and release is mainly through non-covalent forces between the bacteriostatic active substance and the carrier material, such as hydrogen bonding, π-π stacking, van der Waals forces, electrostatic interactions, etc., as well as the loading and adsorption of the bacteriostatic active substance by the chemical assembly. Finally, its wide application in food and medicine is introduced. It is hoped to provide a theoretical basis and technical support for the efficient utilization and product development of bacteriostatic active substances.

Cao, Jiayong↗

ORNL_AISD-Ex: Quantum chemical prediction of UV/Vis absorption spectra for over 10 million organic molecules

We performed calculations of electronic excitation energies and associated oscillator strengths based on the time-dependent density-functional tight-binding (TD-DFTB) method [1]. The SMILES (Simplified molecular-input line-entry system) strings of the molecules from the AISD HOMO-LUMO database [2] were converted to a 3D atomistic structure and stored in a PDB file after preliminary geometry optimization using the Merck Molecular Force Field (MMFF94) in RDKit [3,4]. The primary information stored in the PDB file archive consists of Cartesian coordinates for each atom of the molecule in their 3D location in space, along with summary information about the structure, sequence, and experiment. We then performed molecular geometry optimization using the density-functional tight-binding (DFTB) method [5] in the electronic ground state, followed by single-point excited states calculations, as described below. We note that, since RDKit employs a random choice for the generation of molecular conformers, the molecular geometries obtained in this dataset could be different from the ones that were generated when the AISD HOMO-LUMO dataset was generated. The computed excitation energies and associated oscillator strengths can be converted to predict UV/Vis absorption spectra, where excitation energies correspond to absorption peak positions, and oscillator strengths are a good measure of the probability of absorption of visible or UV light in transitions between electronic ground and excited states. The conversion of SMILES strings to 3D Cartesian coordinates of fully DFTB-optimized molecules was successful for 10,502,904 out of 10,502,917 molecules. For these molecules, both geometry optimizations and excited states calculations were successful. The DFTB calculations did not complete for 13 molecules of the original AISD HOMO-LUMO dataset. We still provide information about the geometry of these molecules. The molecules are diverse for chemical compositions (which span 5 non-hydrogen elements: oxygen, carbon, nitrogen, fluorine, sulfur) and molecular size (the smallest molecule contains 5 non-hydrogen atoms, and the largest molecule contains 71 non-hydrogen atoms). The DFTB method [5] is an approximation to density functional theory (DFT), utilizing a minimal basis set in conjunction with a two-center approximation to the electronic Hamiltonian and overlap matrix elements. The DFTB total energy is the sum of an electronic and a repulsive energy contribution, and their calculation requires optimized electronic parameters and diatomic repulsive potential energy functions. All DFTB calculations were performed using the DFTB+ code [6] (version 21.2) and the wrapper for DFTB+ in the Atomic Simulation Environment (ASE) (version 3.22.1) [7], which performed an internal conversion of Cartesian coordinates from PDB to the .gen file format. For the geometry optimizations on the electronic ground state potential energy surface of the molecules, we have chosen the third-order DFTB (DFTB3) method [5c] and employed the matching 3ob set of electronic parameters and repulsive potentials [8]. The empirical γ-damping for hydrogen bond correction, and Grimme's D3 empirical dispersion correction with Becke-Johnson damping (D3(BJ)) [9] dispersion correction was included to improve the description of non-covalent interactions. For excited states single-point energy calculations, we employed the TD-DFTB method in conjunction with the DFTB2 method [5b] and the matching mio [5b,10] and halorg [11] parameter sets. We opted to request the simultaneous calculation of 50 excited states for singlet transition to investigate sufficient number of excited states, based on linear response theory using the Casida equation [Ref: T. A. Niehaus, S. Suhai, F. Della Sala, P Lugli, M. Elstner, G. Seifert, and Th. Frauenheim. Tight-binding approach to time-dependent density-functional response theory. Phys. Rev. B, 63:085108, 2001] and the ARPACK diagonalizer [R. B. Lehoucq, D. C. Sorensen, and C. Yang. Arpack users guide: Solution of large-scale eigenvalue problems by implicitly restarted arnoldi methods, 1997. 46, 51]. The dataset contains 1001 tar.gz files. Tar files are named as “ornl_aisd_ex_1.tar.gz†through “ornl_aisd_ex_1000.tar.gzâ€. Additionally, the 13 failed molecules are in “ornl_aisd_ex_unprocessed.tar.gzâ€. Except for the tar files listed below, each tar file contains 10,500 molecules. Tar files numbered 34, 121, 128, 352, 360, 429, 495, 509, 518, 627, 676, 668, and 862 contain 10,499 molecules each. The last tar file numbered 1000 contains 13,417 molecules. The total size of the uncompressed dataset is over 283 Gigabytes. The code for calculating the electronic excitation energies and statistical analysis of the dataset is provided at the following GitLab repository: https://github.com/ORNL/Analysis-of-Large-Scale-Molecular-Datasets-with-Python Calculating the UV spectrum of a molecule requires performing 3 main operations: 1. Converting the smiles string representation of a molecule into a geometric structure where each atom is assigned XYZ coordinates. The geometric structure is written to the file smiles.pdb. 2. Using smiles.pdb to compute the relaxed geometry of the molecule, which corresponds with the position of the atoms at the position of equilibrium at the ground state. This generates the files band.out, detailed.out, and geo_end.gen. 3. Using geo_end.gen to calculate the UV spectrum of the molecule which is written into the file EXC.DAT. Every molecule in the dataset has its own directory. The files contained in each molecule directory are as follows: 1. geo_end.gen 2. detailed.out 3. band.out 4. EXC.DAT 5. smiles.pdb REFERENCES [1] Niehaus, T. A.; Suhai, S.; Della Salla, F.; Lugli, P.; Elstner, M.; Seifert, G.; Frauenheim, Th. Tight-binding approach to time-dependent density-functional response theory. Phys. Rev. B, 2001, 63, 085108/1-9. [2] Blanchard, A.; Gounley, J.; Metha, K.; Yoo, P.; Irle, S. AISD HOMO-LUMO. DOI: 10.13139/ORNLNCCS/1869409 [3] RDKit: Cheminformatics and Machine Learning Software. 2013, [http://www.rdkit.org] [4] Tosco, P.; Stiefl, N. and Landrum, G. Bringing the MMFF force field to the RDKit: implementation and validation. J Cheminform. 2014, 6, 1–4. [5] a) Porezag, D.; Frauenheim, T.; Kohler, T.; Seifert, G.; Kaschner, Construction of tight-binding-like potentials on the basis of density-functional theory: Application to carbon, R. Phys. Rev. B 1995, 51, 12947-12957; b) Elstner, M.; Porezag, D.; Jungnickel, G.; Elsner, J.; Haugk, M.; Frauenheim, Th.; Suhai, S.; Seifert, G.; Phys. Rev. B 1998, 58, 7260-7268; c) Gaus, M.; Cui, Q.; Elstner, M. DFTB3: Extension of the Self-Consistent-Charge Density-Functional Tight-Binding Method (SCC-DFTB), J. Chem. Theory Comput. 2011, 7, 931-948; d) Cui, Q.; Elstner, M. Density functional tight binding: values of semi-empirical methods in an ab initio era, Phys. Chem. Chem. Phys. 2014, 16, 14368-14377. [6] Hourahine, B. et al. DFTB+, a software package for efficient approximate density functional theory based atomistic simulations, J. Chem. Phys. 2020, 152, 124101/1-19. [7] Larsen, A. H. et al. The atomic simulation environment—a Python library for working with atoms. J. Phys.: Cond. Matter 2017, 29, 273002. [8] Kubillus, M.; Kubar, T.; Gaus, M.; Rezac, J.; Elstner, M. Parameterization of the DFTB3 Method for Br, Ca, Cl, F, I, K, and Na in Organic and Biological Systems, J. Chem. Theory Comput. 2015, 11, 332-342. [9] Brandenburg, J. G.; Grimme, S. Accurate Modeling of Organic Molecular Crystals by Dispersion-Corrected Density Functional Tight Binding (DFTB), J. Phys. Chem. Lett. 2014, 5, 1785−1789. [10] a) Niehaus, T. A.; Elstner, M.; Frauenheim, Th.; Suhai, S. Application of an approximate density-functional method to sulfur containing compounds. J. Mol. Struct.: THEOCHEM 2001, 541, 185-94; b) Elstner, M.; Hobza, P.; Frauenheim, Th.; Suhai, S.; Kaxiras, E. Hydrogen bonding and stacking interactions of nucleic acid base pairs: A density-functional-theory based treatment. J. Chem. Phys. 2001, 114, 5149-55. [11] Kubar, T.; Bodrog, Z.; Gaus, M.; Köhler, C.; Aradi, B.; Frauenheim, Th.; Elstner, M. Parametrization of the SCC-DFTB Method for Halogens. J. Chem. Theory Comput. 2013, 9, 2939-49.

36 MATERIALS SCIENCE↗

Anion Binding by Macrocyclic Receptors: Computational Landscape of 1:1 and 2:1 Stoichiometries

Macrocyclic receptors play a crucial role in supramolecular chemistry, enabling the selective binding of guest molecules through non-covalent interactions. This study investigates the anion binding properties of three shape-persistent macrocycles, triazolophane, cyanostar, and tricarb, each featuring preorganized cavities with polarized CH hydrogen bond donors. In the 1:1 binding stoichiometries, the macrocycles preferentially bind anions that fit inside their two-dimensional cavities, with this preference being more pronounced in solution. Specifically, the triazolophane favors smaller anions like chloride and bromide, while the larger cavities offered by cyanostar and tricarb macrocycles preferentially bind the larger iodide. For large, polyatomic anions (SCN − , BF$^{−}_{4}$, ClO$^{−}_{4}$, and PF$^{−}_{6}$), the macrocycles self-assemble to form stable 2:1 sandwich complexes, exhibiting stronger binding. This shift in selectivity highlights the versatility of the macrocycles, making them promising candidates for anion sensing and regulation with various complexation stoichiometries.

Che, Minwei [Indiana University, Bloomington, IN (↗

Supramolecular assemblies of polybenzimidazole and aromatic polycarboxylic acids with superior mechanical and H 2 /CO 2 separation properties

Aromatic polycarboxylic acids complex with imidazoles, forming supramolecular assemblies. Herein, we demonstrate that polybenzimidazole (PBI) can be augmented by aromatic polycarboxylic acids, including phthalic acid (PA), trimesic acid (TMA), and pyromellitic acid (PMA), and the resulting supramolecular assemblies exhibit attractive H 2 /CO 2 separation performance for precombustion carbon capture. The acid doping decreases the free volume and gas permeability but increases H 2 /CO 2 selectivity, which can be correlated with the molar ratio of the protons to PBI repeating units in the assemblies. Increasing the temperature decreases the H 2 /CO 2 selectivity because of weakened interactions. When challenged with model gas mixtures, a supramolecular assembly based on TMA shows H 2 /CO 2 separation properties superior to state-of-the-art materials and above Robeson's upper bound. Furthermore, this study elucidates the fruitful harnessing of dynamic non-covalent bonds to design robust and highly selective membranes for industrial gas separations.

36 MATERIALS SCIENCE↗

Improved accuracy and transferability of molecular-orbital-based machine learning: Organics, transition-metal complexes, non-covalent interactions, and transition states

We report molecular-orbital-based machine learning (MOB-ML) provides a general framework for the prediction of accurate correlation energies at the cost of obtaining molecular orbitals. The application of Nesbet’s theorem makes it possible to recast a typical extrapolation task, training on correlation energies for small molecules and predicting correlation energies for large molecules, into an interpolation task based on the properties of orbital pairs. We demonstrate the importance of preserving physical constraints, including invariance conditions and size consistency, when generating the input for the machine learning model. Numerical improvements are demonstrated for different datasets covering total and relative energies for thermally accessible organic and transition-metal containing molecules, non-covalent interactions, and transition-state energies. MOB-ML requires training data from only 1% of the QM7b-T dataset (i.e., only 70 organic molecules with seven and fewer heavy atoms) to predict the total energy of the remaining 99% of this dataset with sub-kcal/mol accuracy. This MOB-ML model is significantly more accurate than other methods when transferred to a dataset comprising of 13 heavy atom molecules, exhibiting no loss of accuracy on a size intensive (i.e., per-electron) basis. It is shown that MOB-ML also works well for extrapolating to transition-state structures, predicting the barrier region for malonaldehyde intramolecular proton-transfer to within 0.35 kcal/mol when only trained on reactant/product-like structures. Finally, the use of the Gaussian process variance enables an active learning strategy for extending the MOB-ML model to new regions of chemical space with minimal effort. We demonstrate this active learning strategy by extending a QM7b-T model to describe non-covalent interactions in the protein backbone–backbone interaction dataset to an accuracy of 0.28 kcal/mol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nickel(ii) complexes based on dithiolate–polyamine binary ligand systems: crystal structures, hirshfeld surface analysis, theoretical study, and catalytic activity study on photocatalytic hydrogen generation

To ascertain the influence of binary ligand systems [1,1-dicyanoethylene-2,2-dithiolate (i-mnt -2 ) and polyamine {tetraen = tris(2-aminoethyl)amine, tren = diethylene triamine and opda = o-phenylenediamine}] on the coordination modes of the Ni(II) metal center and resulting supramolecular architectures, a series of nickel(II) thiolate complexes [Ni(tetraen)(i-mnt)](DMSO) (1), [Ni 2 (tren) 2 (i-mnt) 2 ] (2), and [Ni 2 (i-mnt) 2 (opda) 2 ] n (3) have been synthesized in high yield in one step in water and structurally characterized by single crystal X-ray crystallography and spectroscopic techniques. X-ray diffraction studies disclose the diverse i-mnt -2 coordination to the Ni +2 center in the presence of active polyamine ligands, forming a slightly distorted octahedral geometry (NiN 4 S 2 ) in 1, square planar (NiS 4 ) and distorted octahedral geometries (NiN 6 ) in the bimetallic co-crystallized aggregate of cationic [Ni(tren) 2 ] +2 and anionic [Ni(i-mnt) 2 ] -2 in 2, and a one dimensional (1D) polymeric chain along the [100] axis in 3, having consecutive square planar (NiS 4 ) and octahedral (NiN 6 ) coordination kernels. The N–H···O, N–H···S, N–H···N, N–H···S, N–H···N, and N–H···O type hydrogen bonds stabilize the supramolecular assemblies in 1, 2, and 3 respectively imparting interesting graph-set-motifs. The molecular Hirshfeld surface analyses (HS) and 2D fingerprint plots were utilized for decoding all types of non-covalent contacts in the crystal networks. Atomic HS analysis of the Ni +2 centers reveals significant Ni–N metal–ligand interactions compared to Ni–S interactions. We have also studied the unorthodox interactions observed in the solid state structures of 1–3 by QTAIM and NBO analyses. Moreover, all the complexes proved to be highly active water reduction co-catalysts (WRC) in a photo-catalytic hydrogen evolution process involving iridium photosensitizers, wherein 2 and 3 having a square planar arrangement around the nickel center(s) – were found to be the most active ones, achieving 1000 and 1119 turnover numbers (TON), respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multi-scale computational screening and mechanistic insights of cyclic amines as solvents for improved lignocellulosic biomass processing

A computational screening workflow for the efficient deconstruction of cellulose, lignin and hemicellulose fractions of lignocellulosic biomass using cyclic amines as solvents. Lignocellulosic biomass is a promising feedstock for production of affordable fuels and chemicals from renewable resources. Effective solubilization and subsequent deconstruction of its cellulose, hemicellulose, and lignin fractions is essential for the viability of future biorefineries. This study used quantum chemistry-based equilibrium thermodynamics methods to evaluate the potential of 650 cyclic amines to solubilize cellulose, hemicellulose, and lignin. The activity coefficients of solvent - biopolymer interactions were predicted using the COSMO-RS (COnductor-like Screening MOdel for Real Solvents) method and used to identify cyclic amines that can efficiently dissolve and extract selective fractions of biopolymers during biomass pretreatment. Among the 650 cyclic amines, 1-piperazineethanmaine was predicted to be an effective solvent for extracting all three polymers and was experimentally shown to achieve the highest lignin removal (97.1%). Non-covalent interaction, reduced density gradient and quantum chemical calculations were performed to elucidate the dissolution mechanism of lignin, cellulose and hemicellulose and gain further molecular level insights into the interactions between the cyclic amines and biomass polymers that promote efficient solubilization and extraction. These analyses indicated that 1-piperazineethanmaine and 1-methylimidazole make noncovalent van der Waals, electrostatic interactions and hydrogen bonding with lignin, leading to enhanced lignin removal, while the strong intramolecular hydrogen bonding interactions in cellulose and hemicellulose result in weaker solvent-biopolymer interactions. Overall, the computational approach provided an efficient method for identifying cyclic amines tailored for optimal biomass pretreatment and resulted in the identification of a potential new class of solvents for effective biomass pretreatment.

Kumar, Nikhil↗

CryoEM structure of the low-complexity domain of hnRNPA2 and its conversion to pathogenic amyloid

hnRNPA2 is a human ribonucleoprotein (RNP) involved in RNA metabolism. It forms fibrils both under cellular stress and in mutated form in neurodegenerative conditions. Previous work established that the C-terminal low-complexity domain (LCD) of hnRNPA2 fibrillizes under stress, and missense mutations in this domain are found in the disease multisystem proteinopathy (MSP). However, little is known at the atomic level about the hnRNPA2 LCD structure that is involved in those processes and how disease mutations cause structural change. Here we present the cryo-electron microscopy (cryoEM) structure of the hnRNPA2 LCD fibril core and demonstrate its capability to form a reversible hydrogel in vitro containing amyloid-like fibrils. Whereas these fibrils, like pathogenic amyloid, are formed from protein chains stacked into β-sheets by backbone hydrogen bonds, they display distinct structural differences: the chains are kinked, enabling non-covalent cross-linking of fibrils and disfavoring formation of pathogenic steric zippers. Both reversibility and energetic calculations suggest these fibrils are less stable than pathogenic amyloid. Moreover, the crystal structure of the disease-mutation-containing segment (D290V) of hnRNPA2 suggests that the replacement fundamentally alters the fibril structure to a more stable energetic state. These findings illuminate how molecular interactions promote protein fibril networks and how mutation can transform fibril structure from functional to a pathogenic form.

59 BASIC BIOLOGICAL SCIENCES↗

On the mechanism of intermolecular nitrogen-atom transfer from a lattice-isolated diruthenium nitride intermediate

Catalyst confinement within microporous media provides the opportunity to site isolate reactive intermediates, enforce intermolecular functionalization chemistry by co-localizing reactive intermediates and substrates in molecular-scale interstices, and harness non-covalent host–guest interactions to achieve selectivities that are complementary to those accessible in solution. As part of an ongoing program to develop synthetically useful nitrogen-atom transfer (NAT) catalysts, we have demonstrated intermolecular benzylic amination of toluene at a Ru 2 nitride intermediate confined within the interstices of a Ru2-based metal–organic framework (MOF), Ru 3 (btc) 2 X 3 (btc = 1,3,5-benzenetricarboxylate, i.e., Ru-HKUST-1 for X = Cl). Nitride confinement within the extended MOF lattice enabled intermolecular C–H functionalization of benzylic C–H bonds in preference to nitride dimerization, which was encountered with soluble molecular analogues. Detailed study of the kinetic isotope effects (KIEs, i.e., k H /k D ) of C–H amination, assayed both as intramolecular effects using partially labeled toluene and as intermolecular effects using a mixture of per-labeled and unlabeled toluene, provided evidence for restricted substrate mobility on the time scale of interstitial NAT. Analysis of these KIEs as a function of material mesoporosity provided approximate experimental values for functionalization in the absence of mass transport barriers. Here, we disclose a combined experimental and computational investigation of the mechanism of NAT from a Ru 2 nitride to the C–H bond of toluene. Computed kinetic isotope effects for a H-atom abstraction (HAA)/radical rebound (RR) mechanism are in good agreement with experimental data obtained for C–H amination at the rapid diffusion limit. These results provide the first detailed analysis of the mechanism of intermolecular NAT to a C–H bond, bolster the use of KIEs as a probe of confinement effects on NAT within MOF lattices, and provide mechanistic insights unavailable by experiment because rate-determining mass transport obscured the underlying chemical kinetics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The approximate second order coupled-cluster method based on a size-consistent Brillouin–Wigner partitioning

We present a variant of the approximate second order coupled-cluster method (CC2) with a two-parameter size-consistent Brillouin–Wigner (BW-s) partitioning instead of a Møller–Plesset (MP) partitioning for the unperturbed Hamiltonian, which we refer to as BWs-CC2. The computational complexity of this model scales identically to CC2 with molecular size. Conventional CC2 and its regularized BWs-CC2 variants, as well as conventional MP2 and two of its regularized BW-s2 variants, were assessed on a 535 element database spanning thermochemistry, non-covalent interactions, barrier heights, and isomerization energies. To ensure a well-defined model chemistry, the assessment was performed using internally stable spin-polarized Hartree–Fock (HF) orbitals in the finite aug-cc-pVQZ basis without counterpoise corrections. As a result of using stable orbitals, contrary to conventional wisdom, we find that CC2 substantially outperforms MP2 on molecules with significantly spin contaminated reference orbitals without a significant increase in error on systems with a spin-pure reference, showing the value of its single substitutions. While no single choice of regularization parameters can be optimal for all datasets, we find that BWs-CC2 generally outperforms both CC2 and BW-s2 with a single judicious parameter choice. Additional tests on dipole moments and bond lengths of diatomics provide further support for the utility of this choice. Furthermore, the main outliers and poorest performing cases are associated with large amounts of spin-contamination in the HF reference, which is indicative of systems with either strong correlation or extensive artificial symmetry breaking. Overall, these findings argue that the perception of the quality of the CC2 ground state should be reevaluated and that it can be further improved upon by the soundly based BWs-CC2 variant with the recommended parameter choice.

Correlation energy↗

Enhanced Sulfur Dioxide Adsorption in UiO-66 Through Crystal Engineering and Chalcogen Bonding

Adsorption of corrosive SO 2 gas occurs in metal–organic frameworks (MOFs) including UiO-66. Improvements in SO 2 capacity is obtained through the incorporation of residual modulators in the UiO-66 framework by introducing new binding sites in the material, through residual modulators. Four residual modulators were investigated (acetic acid, trifluoroacetic acid, 3-DMAP acid, cyanoacetic acid), and the UiO-66 framework modulated with cyanoacetic acid exhibited nearly twice the SO 2 uptake for the 18:1 modulator/linker synthesis ratio compared with other modulated UiO-66 structures. Density functional theory investigations confirmed that targeted host–guest interactions were maintained after the modulator was incorporated into the framework. The strongest binding energy was between SO 2 and cyanoacetic acid, consistent with dynamic SO 2 adsorption data, and identified contributions from both the SO 2 reacting with the residual modulator and the coordinating linkers. The successful increase in dynamic SO 2 capacity illustrates how often-overlooked non-covalent interactions can be used in targeted adsorption applications. Further investigation into weak electrostatic interactions for adsorption properties is also needed to advance the potential selectivity and capacity in the adsorption sphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DFT Mechanism Studies: Biomimetic 1,4-NADH Chemoselective, Co-factor Regeneration with [Cp*Rh(bpy)H] + , in Tandem with the Biocatalysis Pathways of a Core Model of the (HLADH)-Zn(II) Mediated Enzyme, in the Enantioselective Reduction of Achiral Ketones to Chiral S-Alcohols

In this study, Quantum Chemical (QC) calculations, utilizing Density Functional Theory (DFT), were performed to investigate the mechanistic aspects of the chemoselective catalyzed reaction of [Cp*Rh(bpy)H] + with the biomimetic NAD + analogues, N-benzylnicotinamide triflate, 1, and β-nicotinamide ribose-5'-methyl phosphate, 2, in the conversion to their 1,4-NADH analogues, 1,4-dihydro-N-benzylnicotinamide, 4, and β-1,4-dihydronicotinamide-5'-ribose methyl phosphate, 5. This reaction was in tandem with the 1,4-NADH dependent HLADH-Zn(II)- catalyzed reduction of achiral ketones to chiral S-alcohols. The [Cp*Rh(bpy)H] + complex, and not its equilibrium tautomer, [η 4 -Cp*HRh(bpy)] + , was found to control the hydride transfer during the biomimetic NAD + /1,4-NADH conversion, through the non-covalent interactions of the biomimetic co-factors with [Cp*Rh(bpy)H] + . The thermodynamics and kinetics for the chiral reduction of the Zn(II) bound ketones, 2-pentanone and 4-phenyl-2-butanone, with co-factor, 4, catalyzed by Zn(SCH 3 ) 2 (Imidazole), a core model of the Zn(II)-based catalytic center of HLADH, was also investigated by the evaluation of two possible reaction pathways: (1) formation of a ZnH from the C4-H hydride transfer of co-factor, 4, followed by reaction of the postulated ZnH with the bound 2-pentanone or 4-phenyl-2-butanone substrate, and (2), the direct C4-H transfer to the bound achiral ketone substrates, to provide the dominant chiral alcohols, S-2-pentanol or S-4-phenyl-2-butanol. The latter pathway was found most viable, and DFT calculations also revealed an essential η 2 -coordination of the 5,6 double bond of co-factor, 4, to the HLADH-Zn(II) metal ion center, upon imidazole decomplexation, providing an asymmetric differentiation of S-η 2 -5,6-1,4-NADH-Zn(II) binding. A proposed new paradigm for the Zn(II)'s non-innocent role in the HLADH-Zn(II) biocatalysis reduction mechanism, for enantioselective hydride transfer to a Zn(II) bound ketone, providing S-alcohols.

1,4 NADH co-factors↗

Preparation and Characterization of Inclusion Complexes of β-Cyclodextrin and Phenolics from Wheat Bran by Combination of Experimental and Computational Techniques

Bitterness often associated with whole wheat products may be related to phenolics in the bran. Cyclodextrins (CDs) are known to form inclusion complexes. The objective was to form inclusion complexes between β-CD and wheat phenolics. Pure phenolic acids (trans-ferulic acid (FA), caffeic acid (CA), and p-coumaric acid (CO)) and phenolic acids from wheat bran were used to investigate complex formation potential. Complexes were characterized by spectroscopy techniques, and a computational and molecular modeling study was carried out. The relative amount of complex formation between β-CD and wheat bran extract was CA > CO > FA. The phenolic compounds formed inclusion complexes with β-CDs by non-covalent bonds. The quantum-mechanical calculations supported the experimental results. The most stable complex was CO/β-CD complex. The ΔH value for CO/β-CD complex was -11.72 kcal/mol and was about 3 kcal/mol more stable than the other complexes. The QSPR model showed good correlation between binding energy and 1H NMR shift for the H5 signal. This research shows that phenolics and β-CD inclusion complexes could be utilized to improve the perception of whole meal food products since inclusion complexes have the potential to mask the bitter flavor and enhance the stability of the phenolics in wheat bran.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NENCI-2021. I. A large benchmark database of non-equilibrium non-covalent interactions emphasizing close intermolecular contacts

In this work, we present NENCI-2021, a benchmark database of ~8000 Non-Equilibirum Non-Covalent Interaction energies for a large and diverse selection of intermolecular complexes of biological and chemical relevance. To meet the growing demand for large and high-quality quantum mechanical data in the chemical sciences, NENCI-2021 starts with the 101 molecular dimers in the widely used S66 and S101 databases and extends the scope of these works by (i) including 40 cation–π and anion–π complexes, a fundamentally important class of non-covalent interactions that are found throughout nature and pose a substantial challenge to theory, and (ii) systematically sampling all 141 intermolecular potential energy surfaces (PESs) by simultaneously varying the intermolecular distance and intermolecular angle in each dimer. Designed with an emphasis on close contacts, the complexes in NENCI-2021 were generated by sampling seven intermolecular distances along each PES (ranging from 0.7× to 1.1× the equilibrium separation) and nine intermolecular angles per distance (five for each ion–π complex), yielding an extensive database of 7763 benchmark intermolecular interaction energies (E int ) obtained at the coupled-cluster with singles, doubles, and perturbative triples/complete basis set [CCSD(T)/CBS] level of theory. The E int values in NENCI-2021 span a total of 225.3 kcal/mol, ranging from -38.5 to +186.8 kcal/mol, with a mean (median) E int value of -1.06 kcal/mol (-2.39 kcal/mol). In addition, a wide range of intermolecular atom-pair distances are also present in NENCI-2021, where close intermolecular contacts involving atoms that are located within the so-called van der Waals envelope are prevalent—these interactions, in particular, pose an enormous challenge for molecular modeling and are observed in many important chemical and biological systems. A detailed symmetry-adapted perturbation theory (SAPT)- based energy decomposition analysis also confirms the diverse and comprehensive nature of the intermolecular binding motifs present in NENCI-2021, which now includes a significant number of primarily induction-bound dimers (e.g., cation–π complexes). NENCI-2021 thus spans all regions of the SAPT ternary diagram, thereby warranting a new four-category classification scheme that includes complexes primarily bound by electrostatics (3499), induction (700), dispersion (1372), or mixtures thereof (2192). A critical error analysis performed on a representative set of intermolecular complexes in NENCI-2021 demonstrates that the E int values provided herein have an average error of ±0.1 kcal/mol, even for complexes with strongly repulsive E int values, and maximum errors of ±0.2–0.3 kcal/mol (i.e., ~±1.0 kJ/mol) for the most challenging cases. For these reasons, we expect that NENCI-2021 will play an important role in the testing, training, and development of next-generation classical and polarizable force fields, density functional theory approximations, wavefunction theory methods, and machine learning based intra- and inter-molecular potentials.

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Uncovering the mechanism of selective stabilization of high-energy diastereoisomers via inclusion

Abstract Supramolecular systems may be used to stabilize otherwise unstable isomers to find alternative synthetic pathways. It has been reported that cucurbit[8]uril can stabilize trans -I and trans -II Cu $$^{{\textrm{II}}}$$ II cyclam, whereas trans -III is the only non-substituted trans Cu $$^{{\textrm{II}}}$$ II cyclam diastereoisomer found outside of the host molecule experimentally. Quantum chemistry methods can provide valuable insight into the intermolecular interactions involved in these inclusion complexes. All five possible trans diastereoisomers of Cu $$^{{\textrm{II}}}$$ II cyclam were studied within the host molecule to calculate the interaction energy and free energy of association for each complex. The relative free energies of the five free cyclams confirm that trans -I and trans -II are the most energetically accessible diastereoisomers from the initial trans -III starting point. Energy decomposition analysis was used to identify the attractive and repulsive interactions between cyclam and cucurbit[8]uril and showed that trans -II encounters repulsive forces almost three times greater than trans -I, which may explain the 7:3 ratio of trans -I to trans -II within cucurbit[8]uril that occurs experimentally. Optimized complex geometries with trans -III, IV, and V show that the cyclams protrude out of cucurbit[8]uril, whereas trans -I and trans -II become more encapsulated and elongate the host, suggesting that the position of the cyclam is extremely important when forming non-covalent interactions. Our results agree with the experimental findings and provide greater insight into why the most stable isolated cyclam diastereoisomer, trans -III, does not form a complex.

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A Permanently Porous Chalcogen-Bonded Organic Framework

The nature of connectivity between constituent atomic or molecular building blocks is fundamental in shaping the properties and functionality of materials. The extrapolation of emergent interatomic interactions to enable functional materials has driven transformative technological advancements. However, the bonding interactions used in material design have been largely static since the emergence of dynamic covalent chemistry ~30 years ago. Here we demonstrate that non-covalent chalcogen bonding (Ch-bonding) is a distinct mode of interatomic connectivity for constructing functional materials by design. This is established by leveraging self-complementary assembly of 1,2,5-telluradiazole moieties to construct a honeycomb-type permanently porous Ch-bonded organic framework, assembled and stabilized solely through non-covalent Te...N contacts. Empirical and computational studies of electronic structure, structural healing and lattice dynamics highlight the pi-type electronic communication, controlled assembly and modulated lattice dynamics in Trip3Tez-I arising directly from the unique nature of the Te...N Ch-bonding that holds substantial implications for next generation crystalline semiconductors. In addition to introducing a distinct class of permanently porous frameworks, this work establishes Ch-bonding as a programmable molecular tool for constructing functional materials with distinct properties.

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