Efficient Quantum Chemical Calculation of Structure Ensembles and Free Energies for Nonrigid Molecules

molli: A General Purpose Python Toolkit for Combinatorial Small Molecule Library Generation, Manipulation, and Feature Extraction

The construction, management, and analysis of large in silico molecular libraries is critical in many areas of modern chemistry. Herein, we introduce the MOLecular LIibrary toolkit, "molli", which is a Python 3 cheminformatics module that provides a streamlined interface for manipulating large in silico libraries. Three-dimensional, combinatorial molecule libraries can be expanded directly from two-dimensional chemical structure fragments stored in CDXML files with high stereochemical fidelity. Geometry optimization, property calculation, and conformer generation are executed by interfacing with widely used computational chemistry programs such as OpenBabel, RDKit, ORCA, NWChem, and xTB/CREST. Conformer-dependent grid-based feature calculators provide numerical representation and interface to robust three-dimensional visualization tools that provide comprehensive images to enhance human understanding of libraries with thousands of members. The package includes a command-line interface in addition to Python classes to streamline frequently used workflows. Parallel performance is benchmarked on various hardware platforms, and common workflows are demonstrated for different tasks ranging from optimized grid-based descriptor calculation on catalyst libraries to an NMR chemical shift prediction workflow from CDXML files.

A variant on the CREST iMTD algorithm for noncovalent clusters of flexible molecules

Conformational ensemble generation and the search for the global minimum conformation are important problems in computational chemistry. In this work, a variant on the conformer-rotamer ensemble sampling tool (CREST) iterative metadynamics (iMTD) algorithm designed for determining structural ensembles and energetics of noncovalent clusters of flexible molecules is presented. We term this new algorithm a low-energy diversity-enhanced variant on CREST, or LEDE-CREST. As with CREST, the energies are evaluated using the semiempirical GFN2-xTB extended tight binding approach. The utility of the algorithm is highlighted by generating ensembles for a variety of noncovalent clusters of flexible or rigid monomers using both CREST and LEDE-CREST.

Cryptate binding energies towards high throughput chelator design: metadynamics ensembles with cluster-continuum solvation

A tiered forcefield/semiempirical/meta-GGA pipeline together with a thermodynamic scheme designed with error cancellation in mind was developed to calculate binding energies of [2.2.2] cryptate complexes of mono- and divalent cations. Stable complexes of Na, K, Rb, Ca, Zn and Pb were generated, revealing consistent cation-N lengths but highly variable cation-O lengths and an amine stacking mechanism potentially augmenting the cation size selectivity. Metadynamics, used for searching the high-dimensional potential energy surface, together with a cluster-continuum model for affordable - yet accurate - solvation modeling, enabled the discovery of more stable geometries than those previously reported. Similar solvation energy curve shapes for lone vs. coordinated ions enabled rapid solvation convergence via the cancellation of errors stemming from finite cluster sizes. An R2 of 0.850 vs. experimental aqueous binding energies was obtained, validating this scheme as the backbone of a high-throughput workflow for chelator design.

Dyotropic Rearrangement of an Iron-Aluminium Complex

Ligand exchange processes at metal complexes underpin their reactivity and catalytic applications. While mechanisms of ligand exchange at single site complexes are well established, occurring through textbook associative, dissociative and interchange mechanisms, those involving heterometallic complexes are less well developed. Here we report the reactions of a well-defined Fe-Al dihydride complex with exogenous ligands (CO and CNR, R=Me, tBu, Xyl=2,6-Me2C6H3). Based on DFT calculations we suggest that these reactions occur through a dyotropic rearrangement, this involves initial coordination of the exogenous ligand at Al followed by migration to Fe, with simultaneous migration of a hydride ligand from Fe to Al. Such processes are rare for heterometallic complexes. We study the bonding and mechanism of the dyotropic rearrangement through in-depth computational analysis (NBO, IBOs, CLMO analysis, QTAIM, NCIplot, IGMH), shedding new light on how the electronic structure of the heterometallic core responds to the migration of ligands between metal sites. The dyotropic rearrangement fundamentally changes the nature of the hydride ligands, exposing new nucleophilic reactivity as evidenced by insertion reactions with CO2, isocyanates, as well as isocyanides.

Reaction-Free Energies for Complexation of Carbohydrates by Tweezer Diboronic Acids

The accurate calculation of reaction-free energies (ΔrG°) for diboronic acids and carbohydrates is challenging due to reactant flexibility and strong solute-solvent interactions. In this study, these challenges are addressed with a semiautomatic workflow based on quantum chemistry methods to calculate conformational free energies, generate microsolvated solute structural ensembles, and compute ΔrG°. Workflow parameters were optimized for accuracy and precision while controlling computational costs. We assessed the accuracy by studying three reactions of diboronic acids with glucose and galactose, finding that the conformational entropy contributes significantly (by 3-5 kcal/mol at room temperature). Explicit solvent molecules improve the computed ΔrG° accuracy by about 4 kcal/mol compared to experimental data, though using 13 or more water molecules reduced precision and increased computational overhead. After fine-tuning, the workflow demonstrated remarkable accuracy, with an absolute error of about 2 kcal/mol compared to experimental ΔrG° and an average interquartile range of 2.4 kcal/mol. These results highlight the workflow's potential for designing and screening tweezer-like ligands with tailored selectivity for various carbohydrates.

Electrophilic C(sp2)-H Cyanation with Inorganic Cyanate (OCN-) by PIII/PV=O-Catalyzed Phase Transfer Activation

An organophosphorus -catalyzed method for the direct electrophilic cyanation of C(sp2)-H nucleophiles with sodium cyanate (NaOCN) is reported. The catalytic deoxyfunctionalization of the OCN- anion is enabled by the use of a small-ring phosphacyclic (phosphetane) catalyst in combination with a terminal hydrosilane O-atom acceptor and a malonate-derived bromenium donor. In situ spectroscopy under single-turnover conditions demonstrate that insoluble inorganic cyanate anion is activated by bromide displacement on a bromophosphonium catalytic intermediate to give a reactive N-bound isocyanatophosphonium ion, which delivers electrophilic "CN+" equivalents to nucleophilic (hetero)arenes and alkenes with loss of a phosphine oxide. These results demonstrate the feasibility of deoxyfunctionalization of insoluble inorganic salts by PIII/PV=O catalyzed phase transfer activation.

Profoxydim in Focus: A Structural Examination of Herbicide Behavior in Gas and Aqueous Phases

This study investigates the chemical structure of profoxydim, focusing on its E-isomer, the main commercial form. The research aimed to determine the predominant tautomeric forms under various environmental conditions. Using proton and carbon-13 NMR spectroscopy alongside theoretical modeling, we examined tautomers and their conformers in different solvents (MeOD, DMSO, CDCl3, benzene) to mimic gas and aqueous phases. The findings reveal that the enolic form dominates in the gas phase, while the ketonic form prevails in aqueous environments, providing key insights into the herbicide's environmental behavior. We also observed an isomeric transition from E to Z under acidic conditions, which could affect profoxydim's reactivity in natural environments. The theoretical calculations indicated that in acidic conditions, the E and Z forms are nearly degenerate, with the E form remaining dominant in neutral environments. Additionally, QSAR models assessed the toxicity of various tautomers, revealing significant differences that could impact bioactivity and environmental fate. This research offers crucial insights into the structural dynamics of profoxydim, contributing to cyclohexanedione chemistry and the development of more effective herbicides.

Toward Reliable Conformational Energies of Amino Acids and Dipeptides─The DipCONFS Benchmark and DipCONL Datasets

Simulating peptides and proteins is becoming increasingly important, leading to a growing need for efficient computational methods. These are typically semiempirical quantum mechanical (SQM) methods, force fields (FFs), or machine-learned interatomic potentials (MLIPs), all of which require a large amount of accurate data for robust training and evaluation. To assess potential reference methods and complement the available data, we introduce two sets, DipCONFL and DipCONFS, which cover large parts of the conformational space of 17 amino acids and their 289 possible dipeptides in aqueous solution. The conformers were selected from the exhaustive PeptideCS dataset by Andris et al. [ J. Phys. Chem. B 2022, 126, 5949-5958]. The structures, originally generated with GFN2-xTB, were reoptimized using the accurate r2SCAN-3c density functional theory (DFT) composite method including the implicit CPCM water solvation model. The DipCONFS benchmark set contains 918 conformers and is one of the largest sets with highly accurate coupled cluster conformational energies so far. It is employed to evaluate various DFT and wave function theory (WFT) methods, especially regarding whether they are accurate enough to be used as reliable reference methods for larger datasets intended for training and testing more approximated SQM, FF, and MLIP methods. The results reveal that the originally provided BP86-D3(BJ)/DGauss-DZVP conformational energies are not sufficiently accurate. Among the DFT methods tested as an alternative reference level, the revDSD-PBEP86-D4 double hybrid performs best with a mean absolute error (MAD) of 0.2 kcal mol-1 compared with the PNO-LCCSD(T)-F12b reference. The very efficient r2SCAN-3c composite method also shows excellent results, with an MAD of 0.3 kcal mol-1, similar to the best-tested hybrid ωB97M-D4. With these findings, we compiled the large DipCONFL set, which includes over 29,000 realistic conformers in solution with reasonably accurate r2SCAN-3c reference conformational energies, gradients, and further properties potentially relevant for training MLIP methods. This set, also in comparison to DipCONFS, is used to assess the performance of various SQM, FF, and MLIP methods robustly and can complement training sets for those.

Emerging Conformational-Analysis Protocols from the RTCONF55-16K Reaction Thermochemistry Conformational Benchmark Set

RTCONF55-16K is a new, reactive conformational data set based on cost-efficient methods to assess different conformational analysis protocols. Our reference calculations underpinned the accuracy of the CENSO (Grimme et al. J. Phys. Chem. A, 2021, 125, 4039) procedure and resulted in alternative recipes with different cost-accuracy compromises. Our general-purpose and economical protocols (CENSO-light and zero, respectively) were found to be 10-30 times faster than the original algorithm, adding only 0.4-0.7 kcal/mol absolute error to the relative free energy estimates.

SmartCADD: AI-QM Empowered Drug Discovery Platform with Explainability

Artificial intelligence (AI) has emerged as a pivotal force in enhancing productivity across various sectors, with its impact being profoundly felt within the pharmaceutical and biotechnology domains. Despite AI's rapid adoption, its integration into scientific research faces resistance due to myriad challenges: the opaqueness of AI models, the intricate nature of their implementation, and the issue of data scarcity. In response to these impediments, we introduce SmartCADD, an innovative, open-source virtual screening platform that combines deep learning, computer-aided drug design (CADD), and quantum mechanics methodologies within a user-friendly Python framework. SmartCADD is engineered to streamline the construction of comprehensive virtual screening workflows that incorporate a variety of formerly independent techniques─spanning ADMET property predictions, de novo 2D and 3D pharmacophore modeling, molecular docking, to the integration of explainable AI mechanisms. This manuscript highlights the foundational principles, key functionalities, and the unique integrative approach of SmartCADD. Furthermore, we demonstrate its efficacy through a case study focused on the identification of promising lead compounds for HIV inhibition. By democratizing access to advanced AI and quantum mechanics tools, SmartCADD stands as a catalyst for progress in pharmaceutical research and development, heralding a new era of innovation and efficiency.

Stable Antiaromatic [16]Triphyrin(2.1.1) with Core Modification: Synthesis Using a 16π Electrocyclic Reaction

Antiaromatic porphyrinoids have attracted significant attention owing to their unique electronic properties and potential applications. However, synthesis of antiaromatic contracted porphyrinoids is challenging owing to the inherent instability associated with smaller ring sizes. In this study, we report the synthesis and characterization of the first stable trioxa[16]triphyrin(2.1.1), a novel 16π antiaromatic contracted porphyrinoid. We utilized a core modification approach to stabilize the [16]triphyrin(2.1.1). X-ray crystallographic analysis revealed a nearly planar structure. Electrochemical studies demonstrated reversible oxidation behavior and a small HOMO-LUMO gap, which was consistent with its antiaromatic nature. Chemical oxidation yielded an aromatic [14]triphyrin(2.1.1) dication, highlighting the antiaromaticity-aromaticity switching capability of this system. This synthesis involved the discovery of a key intermediate, dihydrotrioxatriphyrin(2.1.1), which underwent oxidative dehydrogenation to yield the target compound. Theoretical calculations suggested that dihydrotrioxatriphyrin(2.1.1) formed via a rare 16π electrocyclic reaction. The successful synthesis and characterization of this stable trioxa[16]triphyrin(2.1.1) underscores the potential of the core modification strategies for the rational design of novel antiaromatic systems with tunable properties. Moreover, the discovery of the rare 16π electrocyclic reaction advances the understanding of high-order pericyclic processes and may inspire new synthetic strategies for complex macrocyclic compounds.

Probing microhydration-induced effects on carbonyl compounds

Characterizing the microhydration of organic molecules is a crucial step in understanding many phenomena relevant to atmospheric, biological, and industrial applications. However, its precise experimental and theoretical description remains a challenge. For four organic solutes containing a CO bond, and included in the recent HyDRA challenge [T. L. Fischer, M. Bödecker, A. Zehnacker-Rentien, R. A. Mata and M. A. Suhm, Phys. Chem. Chem. Phys., 2022, 24, 11442-11454.], we performed a detailed study of different monohydrate isomers and their properties; these were cyclooctanone (CON), 1,3-dimethyl-2-imidazolidinon (DMI), methyl lactate (MLA), and 2,2,2-trifluoroacetophenone (TPH) molecules. As reported in the literature, the O-H elongation shift of the water molecule appears to be a good candidate for characterizing complexation-induced effects. We also show that CO elongation shift and UV-vis spectroscopy can be successfully used for these purposes. Besides, we present a comparative analysis of the strengths of non-covalent interactions within these monohydrated complexes based on interpretative tools of quantum chemistry, including topological analysis of electron density (ρ), topological analysis of electron pairing function, and analysis of the core-valence bifurcation index (CVBI), which exhibits a close linear dependency on ρ. Accordingly, a classification of intermolecular water-solute interactions is proposed.

dxtb-An efficient and fully differentiable framework for extended tight-binding

Automatic differentiation (AD) emerged as an integral part of machine learning, accelerating model development by enabling gradient-based optimization without explicit analytical derivatives. Recently, the benefits of AD and computing arbitrary-order derivatives with respect to any variable were also recognized in the field of quantum chemistry. In this work, we present dxtb-an open-source, fully differentiable framework for semiempirical extended tight-binding (xTB) methods. Developed entirely in Python and leveraging PyTorch for array operations, dxtb facilitates extensibility and rapid prototyping while maintaining computational efficiency. Through comprehensive code vectorization and optimization, we essentially reach the speed of compiled xTB programs for high-throughput calculations of small molecules. The excellent performance also scales to large systems, and batch operability yields additional benefits for execution on parallel hardware. In particular, energy evaluations are on par with existing programs, whereas the speed of automatically differentiated nuclear derivatives is only 2 to 5 times slower compared to their analytical counterparts. We showcase the utility of AD in dxtb by calculating various molecular and spectroscopic properties, highlighting its capacity to enhance and simplify such evaluations. Furthermore, the framework streamlines optimization tasks and offers seamless integration of semiempirical quantum chemistry in machine learning, paving the way for physics-inspired end-to-end differentiable models. Ultimately, dxtb aims to further advance the capabilities of semiempirical methods, providing an extensible foundation for future developments and hybrid machine learning applications. The framework is accessible at https://github.com/grimme-lab/dxtb.

Extension of the D3 and D4 London dispersion corrections to the full actinides series

Efficient dispersion corrections are an indispensable component of modern density functional theory, semi-empirical quantum mechanical, and even force field methods. In this work, we extend the well established D3 and D4 London dispersion corrections to the full actinides series, francium, and radium. To keep consistency with the existing versions, the original parameterization strategy of the D4 model was only slightly modified. This includes improved reference Hirshfeld atomic partial charges at the ωB97M-V/ma-def-TZVP level to fit the required electronegativity equilibration charge (EEQ) model. In this context, we developed a new actinide data set called AcQM, which covers the most common molecular actinide compound space. Furthermore, the efficient calculation of dynamic polarizabilities that are needed to construct CAB6 dispersion coefficients was implemented into the ORCA program package. The extended models are assessed for the computation of dissociation curves of actinide atoms and ions, geometry optimizations of crystal structure cutouts, gas-phase structures of small uranium compounds, and an example extracted from a small actinide complex protein assembly. We found that the novel parameterizations perform on par with the computationally more demanding density-dependent VV10 dispersion correction. With the presented extension, the excellent cost-accuracy ratio of the D3 and D4 models can now be utilized in various fields of computational actinide chemistry and, e.g., in efficient composite DFT methods such as r2SCAN-3c. They are implemented in our freely available standalone codes (dftd4, s-dftd3) and the D4 version will be also available in the upcoming ORCA 6.0 program package.

Chemical accuracy for ligand-receptor binding Gibbs energies through multi-level SQM/QM calculations

Calculating the Gibbs energies of binding of ligand-receptor systems with a thermochemical accuracy of ± 1 kcal mol-1 is a challenge to computational approaches. After exploration of the conformational space of the host, ligand and their resulting complexes upon coordination by semi-empirical GFN2 MD and meta-MD simulations, the systematic refinement through a multi-level improvement of binding modes in terms of electronic energies and solvation is able to give Gibbs energies of binding of drug molecules to CB[8] and β-CD macrocyclic receptors with such an accuracy. The accurate treatment of a small number of structures outperforms system-specific force-matching and alchemical transfer model approaches without an extensive sampling and integration.

Overcoming the Pitfalls of Computing Reaction Selectivity from Ensembles of Transition States

The prediction of reaction selectivity is a challenging task for computational chemistry, not only because many molecules adopt multiple conformations but also due to the exponential relationship between effective activation energies and rate constants. To account for molecular flexibility, an increasing number of methods exist that generate conformational ensembles of transition state (TS) structures. Typically, these TS ensembles are Boltzmann weighted and used to compute selectivity assuming Curtin-Hammett conditions. This strategy, however, can lead to erroneous predictions if the appropriate filtering of the conformer ensembles is not conducted. Here, we demonstrate how any possible selectivity can be obtained by processing the same sets of TS ensembles for a model reaction. To address the burdensome filtering task in a consistent and automated way, we introduce marc, a tool for the modular analysis of representative conformers that aids in avoiding human errors while minimizing the number of reoptimization computations needed to obtain correct reaction selectivity.

Theoretical Study of Structural and Electronic Trends of the Sulfonylurea Herbicides Family

The sulfonylurea herbicide family has been extensively studied using computational techniques. The most stable conformer structures of the 34 molecules analyzed in gaseous, aqueous, and octanol phases have been determined. The study employed CREST conformational search methods along with the CENSO script to explore all possible conformational structures. Additional evaluations conducted at the B3LYP-D3/6-311+G(d,p) level have enabled the identification of intramolecular stability patterns across the various compounds. It has been discovered that stability is primarily determined by two factors: intramolecular hydrogen bonding involving an NH group adjacent to the sulfonyl group with either N donors or the nearby carbonyl group and potential π-π interactions between the aromatic rings of the molecules. These have been characterized through QTAIM and NCI population analyses. Furthermore, with the goal of developing predictive models for the physicochemical properties of pesticides that include the sulfonylurea family, a statistical analysis among the different properties of the studied molecules has been conducted. Significant correlations have been found between various properties, predicting a promising future for the prediction of characteristics that could assist laboratories in selecting among different pesticides.

Antiaromaticity of Cycloheptatrienyl Anions: Structure, Acidity, and Magnetic Properties

Investigations of the nature and degree of antiaromaticity of cycloheptatrienyl anion derivatives using both experimental and computational tools are presented. The ground state of cycloheptatrienyl anion in the gas phase is triplet, planar and Baird-aromatic. In DMSO, it assumes a singlet distorted allylic form with a paratropic ring current. The other derivatives in both phases assume either allylic or diallylic conformations depending on the substituent pattern. A combination of experimental and computational methods was used to determine the pKa values of 16 derivatives in DMSO, which ranged from 36 to -10.7. We revealed that the stronger stabilization of the anionic system, which correlates with acidity, does not necessarily imply a lower degree of antiaromaticity in terms of magnetic properties. Conversely, the substitution pattern first affects the geometry of the ring through the bulkiness of the substituents and their better conjugation with a more distorted system. Consequently, the distortion reduces the cyclic conjugation in the π-system and thereby decreases the paratropic current in a magnetic field, which manifests itself as a decrease in the NICS. The triplet-state geometries and magnetic properties are nearly independent on the substitution pattern, which is typical for simple aromatic systems.

Kinetic Resolution of β-Branched Aldehydes through Peptide-Catalyzed Conjugate Addition Reactions

The catalytic kinetic resolution of racemic β-branched aldehydes offers a straightforward stereoselective entry to aldehydes and addition products. Yet, control over stereoselectivity is difficult due to the conformational flexibility of β-branched aldehydes. Here, we show that the peptide catalyst H-dPro-αMePro-Glu-NH2 resolves β-branched aldehydes through reaction with nitroolefins and provides γ-nitroaldehydes with three consecutive stereogenic centers in high yields and stereoselectivities. Kinetic, NMR spectroscopic, and computational studies provided insights into the selectivity-determining step and origins of the kinetic resolution.

Integrated workflows and interfaces for data-driven semi-empirical electronic structure calculations

Modern software engineering of electronic structure codes has seen a paradigm shift from monolithic workflows toward object-based modularity. Software objectivity allows for greater flexibility in the application of electronic structure calculations, with particular benefits when integrated with approaches for data-driven analysis. Here, we discuss different approaches to create deep modular interfaces that connect big-data workflows and electronic structure codes and explore the diversity of use cases that they can enable. We present two such interface approaches for the semi-empirical electronic structure package, DFTB+. In one case, DFTB+ is applied as a library and provides data to an external workflow; in another, DFTB+receives data via external bindings and processes the information subsequently within an internal workflow. We provide a general framework to enable data exchange workflows for embedding new machine-learning-based Hamiltonians within DFTB+ or enabling deep integration of DFTB+ in multiscale embedding workflows. These modular interfaces demonstrate opportunities in emergent software and workflows to accelerate scientific discovery by harnessing existing software capabilities.

Utilization of 13C NMR Carbon Shifts for the Attribution of Diastereomers in Methyl-Substituted Cyclohexanes

In this report, we address the challenge of assigning diastereomers for methyl cyclohexanes, particularly those with quaternary centers, which remains nontrivial despite modern NMR techniques. By utilizing a HSQC NMR experiment to identify methyl-carbons coupled with a simple conformational analysis, we identified an effective and quite general method for assigning stereochemistry, even in cases where diastereomeric mixtures are inseparable.

SARS-CoV-2 Spike Protein-Derived Cyclic Peptides as Modulators of Spike Interaction with GRP78

The human glucose-regulated protein GRP78 is a human chaperone that translocactes to the cell surface when cells are under stress. Theoretical studies suggested it could be involved in SARS-CoV-2 virus entry to cells. In this work, we used in vitro surface plasmon resonance-based assays to show that human GRP78 indeed binds to SARS-CoV-2 spike protein. We have designed and synthesised cyclic peptides based on the loop structure of amino acids 480-488 of the SARS-CoV-2 spike protein S1 domain from the Wuhan and Omicron variants and showed that both peptides bind to GRP78. Consistent with the greater infectiousness of the Omicron variant, the Omicron-derived peptide displays slower dissociation from the target protein. Both peptides significantly inhibit the binding of wild-type S1 protein to the human protein GRP78 suggesting that further development of these cyclic peptide motifs may provide a viable route to novel anti-SARS-CoV-2 agents.

In Search of the Best Low-Cost Methods for Efficient Screening of Conformers

Locating the lowest energy conformer is crucial for the accurate computation of equilibrium properties of molecular systems. This paper examines the performance of efficient low-cost methods in terms of the alignment and relative energies of their energy minima against the benchmark revDSD-PBEP86-D4/def2-TZVPP//MP2/cc-pVTZ potential energy surface. The low-cost methods considered include GFN-FF, GFN2-xTB, DFTB3, HF-3c, B97-3c, PBEh-3c, and r2SCAN-3c composite methods against a diverse test set of 20 compounds including alkanes, perfluoroalkyl molecules, peptides, open-shell radicals, and Zn(II) complexes of varying sizes. The "3c" composite methods are generally more accurate, but are at least 2-3 orders of magnitude more expensive than tight-binding methods which have energy minima that align well with the benchmark potential energy surface. The findings of this paper were further exploited to introduce a simple strategy involving Grimme's CENSO energy-sorting algorithm that resulted in up to an order of magnitude reduction in computational time for locating the lowest energy conformer on the revDSD-PBEP86-D4/def2-TZVPP//MP2/cc-pVTZ surface.

Scaffold-Oriented Asymmetric Catalysis: Conformational Modulation of Transition State Multivalency during a Catalyst-Controlled Assembly of a Pharmaceutically Relevant Atropisomer

A new class of superbasic, bifunctional peptidyl guanidine catalysts is presented, which enables the organocatalytic, atroposelective synthesis of axially chiral quinazolinediones. Computational modeling unveiled the conformational modulation of the catalyst by a novel phenyl urea N-cap, that preorganizes the structure into the active, folded state. A previously unanticipated noncovalent interaction involving a difluoroacetamide acting as a hybrid mono- or bidentate hydrogen bond donor emerged as a decisive control element inducing atroposelectivity. These discoveries spurred from a scaffold-oriented project inspired from a fascinating investigational BTK inhibitor featuring two stable chiral axes and relies on a mechanistic framework that was foreign to the extant lexicon of asymmetric catalysis.

NBN- and BNB-Phenalenyls: the Yin and Yang of Heteroatom-doped π Systems

NBN- and BNB-doped phenalenyls are isoelectronic to phenalenyl anions and cations, respectively. They represent a pair of complementary molecules that have essentially identical structures but opposite properties as electron donors and acceptors. The NBN-phenalenyls 1-4 considered here were prepared from N,N'-dimethyl-1,8-diaminonaphthalene and readily available boron-containing building blocks (i. e., BH3⋅SMe2 (1), p-CF3-C6H4B(OH)2 (2), C6H5B(OH)2 (3), or MesBCl2/iPr2NEt (4)). Treatment of 1 with 4-Me2N-2,6-Me2-C6H2Li gave the corresponding NBN derivative 5. The BNB-phenalenyl 6 was synthesized from 1,8-naphthalenediyl-bridged diborane(6), PhNH2, and MesMgBr. A computational study reveals that the photoemission of 1, 4, and 5 originates from locally excited (LE) states at the NBN-phenalenyl fragments, while that of 2 is dominated by charge transfer (CT) from the NBN-phenalenyl to the p-CF3-C6H4 fragment. Depending on the dihedral angle θ between its Ph and NBN planes, compound 3 emits mainly from a less polar LE (θ >55°) or more polar CT state (θ <55°). In turn, the energetic preference for either state is governed by the polarity of the solvent used. An equimolar aggregate of the NBN- and BNB-phenalenyls 3 and 6 (in THF/H2O) shows a distinct red-shifted emission compared to that of the individual components, which originates from an intermolecular CT state.

Copper-catalysed electrophilic carboamination of terminal alkynes with benzyne looked at through the computational lens

A detailed computational mechanistic study of the copper-catalysed three-component-type electrophilic carboamination of terminal alkynes with benzyne and an archetypal O-benzoylhydroxylamine electrophile is presented. Probing various plausible pathways for relevant elementary steps and scrutinising performance degradation pathways, with the aid of a reliable computational protocol applied to a realistic catalyst model combined with kinetic analysis, identified the pathways preferably traversed in productive catalysis. It entails rapid alkynylcupration of in situ generated benzyne to deliver the arylcopper nucleophile that undergoes amination with the O-benzoylhydroxylamine electrophile to afford copper benzoate. Umpolung-enabled electrophilic amination favours a multistep SN2-type oxidative addition/N-C bond-forming reductive elimination sequence involving a short-lived formal {P^P}CuIII carboxylate amido aryl intermediate. SN2-type displacement of the benzoate leaving group at the arylcopper nucleophile, which represents the catalyst resting state, is predicted to be the turnover limiting step. Alkynolysis transforms copper benzoate back to catalytically competent alkynylcopper. The computational probe of a wider range of substrates reveals that only severely ring-strained C6-arynes, C6-cycloalkynes and electron-deficient cyclopropenes featuring a highly reactive C≡C linkage could replace benzyne. Moreover, strict control of stationary benzyne concentration is indispensable for electrophilic carboamination to ever become achievable.

Structural flexibility of favipiravir and its structural analogues in solutions: experimental and computational insight

Combined UV-vis and quantum chemical studies of the structural flexibility and tautomerism of 6-R-3-hydroxy-2-pyrazine carboxamides in solutions revealed that their keto-enol transformations are accompanied by the deprotonation of enol tautomers and the formation of the corresponding anionic species. Both the solvent and the 6-R substituent strongly influence the relative abundance of the above forms in solutions. Anions are not formed in 1,2-dichloroethane (DCE), but the probability of deprotonation in neutral water and N,N-dimethylformamide (DMF) increases in the order R = H < F < NO2. Only enol tautomers of all solutes are found in DCE. DMF stabilizes keto forms only moderately and assists much strongly in the deprotonation of all three compounds. Water tends to stabilize both keto tautomers and deprotonated anions: the keto form dominates in the case of R = H (antiviral drug T-1105), the anions are found exclusively for R = NO2, and the aqueous solution of another antiviral drug, favipiravir (R = F), contains both the keto tautomer and the anionic form. The results of quantum chemical free energy calculations are in agreement with the experimental observations.

Sorting drug conformers in enzyme active sites: the XTB way

In the present study, we have used the MEI196 set of interaction energies to investigate low-cost computational chemistry approaches for the calculation of binding between a molecule and its environment. Density functional theory (DFT) methods, when used with the vDZP basis set, yield good agreement with the reference energies. On the other hand, semi-empirical methods are less accurate as expected. By examining different groups of systems within MEI196 that contain species of a similar nature, we find that chemical similarity leads to cancellation of errors in the calculation of relative binding energies. Importantly, the semi-empirical method GFN1-xTB (XTB1) yields reasonable results for this purpose. We have thus further assessed the performance of XTB1 for calculating relative energies of docking poses of substrates in enzyme active sites represented by cluster models or within the ONIOM protocol. The results support the observations on error cancellation. This paves the way for the use of XTB1 in parts of large-scale virtual screening workflows to accelerate the drug discovery process.

Modeling Zinc Complexes Using Neural Networks

Understanding the energetic landscapes of large molecules is necessary for the study of chemical and biological systems. Recently, deep learning has greatly accelerated the development of models based on quantum chemistry, making it possible to build potential energy surfaces and explore chemical space. However, most of this work has focused on organic molecules due to the simplicity of their electronic structures as well as the availability of data sets. In this work, we build a deep learning architecture to model the energetics of zinc organometallic complexes. To achieve this, we have compiled a configurationally and conformationally diverse data set of zinc complexes using metadynamics to overcome the limitations of traditional sampling methods. In terms of the neural network potentials, our results indicate that for zinc complexes, partial charges play an important role in modeling the long-range interactions with a neural network. Our developed model outperforms semiempirical methods in predicting the relative energy of zinc conformers, yielding a mean absolute error (MAE) of 1.32 kcal/mol with reference to the double-hybrid PWPB95 method.

Autobench V1.0: Benchmarking Automation for Electronic Structure Calculations

This work reports on new software for automatic conformer energy benchmarking calculations for flexible molecules. The software workflow consists of four parts: conformational search, preoptimization, optimization, and frequency calculations at a higher level and last calculations using several theoretical levels. The software was written to be user-friendly and versatile to be used by nonexperts in computational chemistry. Any theoretical levels available in either Gaussian 16 or ORCA 5 may be applied in the benchmarking study. The workflow will automatically run conformational search calculations and deal with conformers that converge to the same minimum and those that show a negative frequency. At the end of the workflow, the user will have the mean absolute deviations and the most accurate method/DFT functional and basis set in comparison to the benchmark to be applied for the molecular system of interest. Case examples are given at the end of the paper that may help users to get insight into the software's main features.

Molecular Understanding of the Distinction between Adhesive Failure and Cohesive Failure in Adhesive Bonds with Epoxy Resin Adhesives

In the development of adhesives, an understanding of the fracture behavior of the bonded joints is inevitable. Two typical failure modes are known: adhesive failure and cohesive failure. However, a molecular understanding of the cohesive failure process is not as advanced as that of the adhesive failure process. In this study, research was developed to establish a molecular understanding of cohesive failure using the example of a system in which epoxy resin is bonded to a hydroxyl-terminated self-assembled monolayer (SAM) surface. Adhesive failure was modeled as a process in which an epoxy molecule is pulled away from the SAM surface. Cohesive failure, on the other hand, was modeled as the process of an epoxy molecule separating from another epoxy molecule on the SAM surface or breaking of a covalent bond within the epoxy resin. The results of the simulations based on the models described above showed that the results of the calculations using the model of cohesive failure based on the breakdown of intermolecular interactions agreed well with the experimental results in the literature. Therefore, it was suggested that the cohesive failure of epoxy resin adhesives is most likely due to the breakdown of intermolecular interactions between adhesive molecules. We further analyzed the interactions at the adhesive failure and cohesive failure interfaces and found that the interactions at the cohesive failure interface are mainly accounted for by dispersion forces, whereas the interactions at the adhesive failure interface involve not only dispersion forces but also various chemical interactions, including hydrogen bonds. The selectivity between adhesive failure and cohesive failure was explained by the fact that varying the functional group density affected the chemical interactions but not the dispersion forces.

Multilevel Framework for Analysis of Protein Folding Involving Disulfide Bond Formation

In this study, a three-layered multicenter ONIOM approach is implemented to characterize the naive folding pathway of bovine pancreatic trypsin inhibitor (BPTI). Each layer represents a distinct level of theory, where the initial layer, encompassing the entire protein, is modeled by a general all-atom force-field GFN-FF. An intermediate electronic structure layer consisting of three multicenter fragments is introduced with the state-of-the-art semiempirical tight-binding method GFN2-xTB. Higher accuracy, specifically addressing the breaking and formation of the three disulfide bonds, is achieved at the innermost layer using the composite DFT method r2SCAN-3c. Our analysis sheds light on the structural stability of BPTI, particularly the significance of interlinking disulfide bonds. The accuracy and efficiency of the multicenter QM/SQM/MM approach are benchmarked using the oxidative formation of cystine. For the folding pathway of BPTI, relative stabilities are investigated through the calculation of free energy contributions for selected intermediates, focusing on the impact of the disulfide bond. Our results highlight the intricate trade-off between accuracy and computational cost, demonstrating that the multicenter ONIOM approach provides a well-balanced and comprehensive solution to describe electronic structure effects in biomolecular systems. We conclude that multiscale energy landscape exploration provides a robust methodology for the study of intriguing biological targets.

CREST-A program for the exploration of low-energy molecular chemical space

Conformer-rotamer sampling tool (CREST) is an open-source program for the efficient and automated exploration of molecular chemical space. Originally developed in Pracht et al. [Phys. Chem. Chem. Phys. 22, 7169 (2020)] as an automated driver for calculations at the extended tight-binding level (xTB), it offers a variety of molecular- and metadynamics simulations, geometry optimization, and molecular structure analysis capabilities. Implemented algorithms include automated procedures for conformational sampling, explicit solvation studies, the calculation of absolute molecular entropy, and the identification of molecular protonation and deprotonation sites. Calculations are set up to run concurrently, providing efficient single-node parallelization. CREST is designed to require minimal user input and comes with an implementation of the GFNn-xTB Hamiltonians and the GFN-FF force-field. Furthermore, interfaces to any quantum chemistry and force-field software can easily be created. In this article, we present recent developments in the CREST code and show a selection of applications for the most important features of the program. An important novelty is the refactored calculation backend, which provides significant speed-up for sampling of small or medium-sized drug molecules and allows for more sophisticated setups, for example, quantum mechanics/molecular mechanics and minimum energy crossing point calculations.

Benchmark Study on the Calculation of 207Pb NMR Chemical Shifts

A benchmark set for the computation of 207Pb nuclear magnetic resonance (NMR) chemical shifts is presented. The PbS50 set includes conformer ensembles of 50 lead-containing molecular compounds and their experimentally measured 207Pb NMR chemical shifts. Various bonding motifs at the Pb center with up to seven bonding partners are included. Six different solvents were used in the measurements. The respective shifts lie in the range between +10745 and -5030 ppm. Several calculation settings are assessed by evaluating computed 207Pb NMR shifts for the use with different density functional approximations (DFAs), relativistic approaches, treatment of the conformational space, and levels for geometry optimization. Relativistic effects were included explicitly with the zeroth order regular approximation (ZORA), for which only the spin-orbit variant was able to yield reliable results. In total, seven GGAs and three hybrid DFAs were tested. Hybrid DFAs significantly outperform GGAs. The most accurate DFAs are mPW1PW with a mean absolute deviation (MAD) of 429 ppm and PBE0 with an MAD of 446 ppm. Conformational influences are small as most compounds are rigid, but more flexible structures still benefit from Boltzmann averaging. Including explicit relativistic treatments such as SO-ZORA in the geometry optimization does not show any significant improvement over the use of effective core potentials (ECPs).

Rational Design of a Phosphorus-Centered Disbiradical

Phosphorus-centered disbiradicals, in which the radical sites exist as individual spin doublets with weak spin-spin interaction have not been known so far. Starting from monoradicals of the type [⋅P(μ-NTer)2 P-R], we have now succeeded in linking two such monoradical phosphorus centers by appropriate choice of a linker. To this end, biradical [⋅P(μ-NTer)2 P⋅] (1) was treated with 1,6-dibromohexane, affording the brominated species {Br[P(μ-NTer)]2 }2 C6 H12 (3). Subsequent reduction with KC8 led to the formation of the disbiradical {⋅[P(μ-NTer)]2 }2 C6 H12 (4) featuring a large distance between the radical phosphorus sites in the solid state and formally the highest biradical character observed in a P-centered biradical so far, approaching 100 %. EPR spectroscopy revealed a three-line signal in solution with a considerably larger exchange interaction than would be expected from the molecular structure of the single crystal. Quantum chemical calculations revealed a highly dynamic conformational space; thus, the two radical sites can approach each other with a much smaller distance in solution. Further reduction of 4 resulted in the formation of a potassium salt featuring the first structurally characterized P-centered distonic radical anion (5- ). Moreover, 4 could be used in small molecule activation.

Conformations and Rearrangements of Collinolactone - Experiments and Theory on a Dynamic Cyclodecatriene

Collinolactone A is a microbial specialized metabolite with a unique 6-10-7 tricyclic bislactone skeleton which was isolated from Streptomyces bacteria. The unusual cyclodecatriene motif features dynamic interconversions of two rotamers. Given the biological profiling of collinolactone A as neuroprotective agent, semisynthetic modifications represent an invaluable strategy to enhance its efficacy. Since understanding conformations and reactions of bioactive substances is crucial for rational structure-based design and synthesis of derivatives, we conducted computational studies on conformational behavior as well as experiments on thermal and acid induced rearrangements of the cyclodecatriene. Experimental conformer ratios of collinolactone A and its biosynthetic ketolactone precursor are well reproduced by computations at the PW6B95-D3/def2-QZVPP//r2 SCAN-3c level. Upon heating collinolactone A in anhydrous dioxane at 100 °C, three collinolactone B stereoisomers exhibiting enollactone structures form via Cope rearrangements. Our computations predict the energetic preference for a boat-like transition state in agreement with the stereochemical outcome of the main reaction pathway. Constriction of the ten-membered ring forms collinolactone C with four annulated rings and an exocyclic double bond. Computations and semisynthetic experiments demonstrate strong preference for an acid-catalyzed reaction pathway over an alternative Alder-ene route to collinolactone C with a prohibitive reaction barrier, again in line with stereochemical observations.

Machine learning-based correction for spin-orbit coupling effects in NMR chemical shift calculations

As one of the most powerful analytical methods for molecular and solid-state structure elucidation, NMR spectroscopy is an integral part of chemical laboratories associated with a great research interest in its computational simulation. Particularly when heavy atoms are present, a relativistic treatment is essential in the calculations as these influence also the nearby light atoms. In this work, we present a Δ-machine learning method that approximates the contribution to 13C and 1H NMR chemical shifts that stems from spin-orbit (SO) coupling effects. It is built on computed reference data at the spin-orbit zeroth-order regular approximation (ZORA) DFT level for a set of 6388 structures with 38 740 13C and 64 436 1H NMR chemical shifts. The scope of the methods covers the 17 most important heavy p-block elements that exhibit heavy atom on the light atom (HALA) effects to covalently bound carbon or hydrogen atoms. Evaluated on the test data set, the approach is able to recover roughly 85% of the SO contribution for 13C and 70% for 1H from a scalar-relativistic PBE0/ZORA-def2-TZVP calculation at virtually no extra computational costs. Moreover, the method is transferable to other baseline DFT methods even without retraining the model and performs well for realistic organotin and -lead compounds. Finally, we show that using a combination of the new approach with our previous Δ-ML method for correlation contributions to NMR chemical shifts, the mean absolute NMR shift deviations from non-relativistic DFT calculations to experimental values can be halved.

Straightforward synthesis of chiral sulfonate-based ionic liquids from amino alcohols for chiral recognition

New sulfonate-based chiral salts were prepared from amino alcohols and sodium hydroxymethanesulfonate, vinyl sulfonate, or sultone. The synthesis started with different amino acids from the chiral pool and gave the desired products in just four steps. After cation metathesis, the salts were explored as chiral solvating agents (CSAs) in NMR studies. The new chiral ionic liquids (CILs) were successfully able to interact with different chiral guest molecules and formed diastereomeric aggregates. In some cases, baseline separation was observed. The influence of the structural differences in the CIL as well as the structural requirements of the guest molecule is discussed.

A Chiral Titanocene Complex as Regiodivergent Photoredox Catalyst: Synthetic Scope and Mechanism of Catalyst Generation

We describe a combined synthetic, spectroscopic, and computational study of a chiral titanocene complex as a regiodivergent photoredox catalyst (PRC). With Kagan's complex catCl2 either monoprotected 1,3-diols or 1,4-diols can be obtained in high selectivity from a common epoxide substrate in a regiodivergent epoxide opening depending on which enantiomer of the catalyst is employed. Due to the catalyst-controlled regioselectivity of ring opening and the broader substrate scope, the PRC with catCl2 is also a highly attractive branching point for diversity-oriented synthesis. The photochemical processes of cat(NCS)2, a suitable model for catCl2, were probed by time-correlated single-photon counting. The photoexcited complex displays a thermally activated delayed fluorescence as a result of a singlet-triplet equilibration, S1 ⇄ T1, via intersystem crossing and recrossing. Its triplet state is quenched by electron transfer to the T1 state. Computational and cyclic voltammetry studies highlight the importance of our sulfonamide additive. By bonding to sulfonamide additives, chloride abstraction from [catCl2]- is facilitated, and catalyst deactivation by coordination of the sulfonamide group is circumvented.

Chiral Lewis Base-Catalysed Asymmetric Syntheses of Benzo-fused ϵ-Lactones

We herein report a two-step protocol for the asymmetric synthesis of novel chiral benzofused ϵ-lactones starting from O-protected hydroxymethyl-para-quinone methides and activated aryl esters. By using chiral isothiourea Lewis base catalysts a broad variety of differently substituted products could be obtained in yields of around 50 % over both steps with high levels of enantioselectivities, albeit low diastereoselectivities only.

High-throughput screening of spin states for transition metal complexes with spin-polarized extended tight-binding methods

The semiempirical GFNn-xTB ( n = 1 , 2 ) tight-binding methods are extended with a spin-dependent energy term (spin-polarization), enabling the fast and efficient screening of different spin states for transition metal complexes. While GFNn-xTB methods inherently can not differentiate properly between high-spin (HS) and low-spin (LS) states, this shortcoming is corrected with the presented methods termed spGFNn-xTB. The performance of spGFNn-xTB methods for spin state energy splittings is evaluated on a newly compiled benchmark set of 90 complexes (27 HS and 63 LS complexes) containing 3d, 4d, and 5d transition metals (termed TM90S) employing DFT references at the TPSSh-D4/def2-QZVPP level of theory. The challenging TM90S set contains complexes with charges between - 4 and +3, spin multiplicities between 1 and 6, and spin-splitting energies that range from - 47.8 to 146.6 kcal/mol with a mean average of 32.2 kcal/mol. On this set the (sp)GFNn-xTB methods, the PM6-D3H4 method, and the PM7 method are evaluated with spGFN1-xTB yielding the lowest MAD of 19.6 kcal/mol followed by spGFN2-xTB with 24.8 kcal/mol. While for the 4d and 5d subsets small or no improvements are observed with spin-polarization, large improvements are obtained for the 3d subset with spGFN1-xTB yielding the smallest MAD of 14.2 kcal/mol followed by spGFN2-xTB with 17.9 kcal/mol and PM6-D3H4 with 28.4 kcal/mol. The correct sign of the spin state splittings is obtained with spGFN2-xTB in 89% of all cases closely followed by spGFN1-xTB with 88%. On the full set, a pure semiempirical vertical spGFN2-xTB//GFN2-xTB-based workflow for screening purposes yields a slightly better MAD of 22.2 kcal/mol due to error compensation, while being qualitative correct for one additional case. In combination with their low computational cost (scanning spin states in seconds), the spGFNn-xTB methods represent robust tools for pre-screening steps of spin state calculations and high-throughput workflows.

High-Level Quantum Chemical Prediction of C-F Bond Dissociation Energies of Perfluoroalkyl Substances

In this study, 550 C-F bond dissociation energies (BDEs) of a variety of per- and polyfluoroalkyl substances (PFASs) obtained from high-level DLPNO-CCSD(T)/CBS calculations were used to assess the accuracy of contemporary density functional theory (DFT) and semiempirical methods. DLPNO-CCSD(T)/CBS gas phase C-F BDEs fall between 404.9-550.7 kJ mol-1 and M06-2X and ωB97M-V in conjunction with the aug-cc-pVTZ basis set predicted BDEs closest to the benchmark level with a mean absolute deviation (MAD) of 7.3 and 8.3 kJ mol-1, respectively. It was observed that DFT prediction errors increase with the degree of fluorination and system size. As such, previous model chemistry recommendations based on smaller nonfluorinated systems may not be carried over to modeling the energetics of PFASs and related systems.

Mechanistic aspects of reactive metabolite formation in clomethiazole catalyzed biotransformation by cytochrome P450 enzymes

Clomethiazole (CLM), a sedative and anticonvulsant drug, is commonly employed for the treatment of alcohol withdrawal syndrome because it suppresses cytochrome P450 (P450) activity associated with the generation of free radicals and liver damage. The catalyzed biotransformation of thiazole-containing drugs by P450 is known to afford reactive metabolites. These metabolites can alter the biological functions of macromolecules and result in toxicity and adverse drug interactions. Multitargeted molecular modeling and quantum chemical DFT calculations were performed to explore the binding modes and molecular mechanisms underlying the mechanism-based inactivation (MBI) of P450 by CLM. The mechanistic details associated with reactive metabolite formation from further metabolic processes were extensively assessed. Seven possible routes were proposed for CLM-P450 biotransformation including CLM hydroxylation, sulfoxidation, N-oxidation, CN epoxidation (oxaziridine formation), and CC epoxidation. The results revealed a degree of preference for the C-N epoxidation pathway because of the low energy requirements of its rate-determining step (8.74 and 10.07 kcal mol-1 for LS and HS states, respectively). A kinetic competition for the CLM-methyl hydroxylation pathway was detected because the H-abstraction energy barrier was relatively comparable to the thermodynamically prevailing oxaziridine formation rate-determining step (12.58 and 14.52 kcal mol-1 for quartet and doublet states, respectively). Our studies assessed the mechanisms of covalent nucleophilic epoxide adduct formation through nucleophilic addition, hydrolysis of epoxidation products, and nonenzymatic degradation. CLM was shown to display P450-inhibitory activity by forming covalent adducts rather than further metabolization to reactive metabolites. The outcomes of molecular docking allowed assessing the binding profile of CLM with three human P450 isozymes, namely, CYP2E1, CYP3A4, and CYP2D6.

Density Functional Theory Calculations for Multiple Conformers Explaining the Regio- and Stereoselectivity of Ti-Catalyzed Hydroaminoalkylation Reactions

Hybrid Density Functional Theory (DFT) calculations for multiple conformers of the insertion reactions of a methylenecyclopropane into the Ti-C bond of two differently α-substituted titanaaziridines explain the experimentally observed differences in regioselectivity between catalytic hydroaminoalkylation reactions of methylenecyclopropanes with α-phenyl-substituted secondary amines and corresponding stoichiometric reactions of a methylenecyclopropane with titanaaziridines, which can only be achieved with α-unsubstituted titanaaziridines. In addition, the lack of reactivity of α-phenyl-substituted titanaaziridines as well as the diastereoselectivity of the catalytic and stoichiometric reactions can be understood.

Dispersion Energy-Stabilized Boron and Phosphorus Lewis Pairs

An isostructural series of boron/phosphorus Lewis pairs was systematically investigated. The association constants of the Lewis pairs were determined at variable temperatures, enabling the extraction of thermodynamic parameters. The stabilization of the Lewis adduct increased with increasing size of the dispersion energy donor groups, although the donor and acceptor properties of the Lewis pairs remained largely unchanged. This data was utilized to challenge state-of-the-art quantum chemical methods, which finally led to an enhanced workflow for the determination of thermochemical properties of weakly bound Lewis pairs within an accuracy of 0.6 to 1.0 kcal mol-1 for computed association free energies.

Enantio- and Diastereomerically Pure Titanocenes by Dynamic Conformational Locking

The synthesis of enantiomerically pure titanocenes is limited to cases with enantiomerically pure substituents at the cyclopentadienyl ligands and to ansa-titanocenes. For the latter complexes, the use of achiral ligands requires a resolution of enantiomers and frequently also a separation of the diastereoisomers obtained after metalation. Here, we introduce a new synthetic method that relies on the use of enantiomerically pure camphorsulfonate (CSA) ligands as control elements for the absolute and relative configuration of titanocene complexes. Starting from the conformationally flexible (RC5 H4 )2 TiCl2 , the desired conformationally locked and hence enantio- and diastereomerically pure complexes (RC5 H4 )2 Ti(CSA)2 are obtained in just two steps. According to X-ray crystallography the (RC5 H4 )2 Ti fragment is essentially C2 -symmetric and nuclear magnetic resonance displays overall C2 -symmetry. We applied density functional theory methods to unravel the dynamics of the complexes and the mechanisms and selectivities of their formation.

Extended Conductor-like Polarizable Continuum Solvation Model (CPCM-X) for Semiempirical Methods

We have developed a new method to accurately account for solvation effects in semiempirical quantum mechanics based on a polarizable continuum model (PCM). The extended conductor-like polarizable continuum model (CPCM-X) incorporates a computationally efficient domain decomposition conductor-like screening model (ddCOSMO) for extended tight binding (xTB) methods and uses a post-processing approach based on established solvation models, like the conductor-like screening model for real solvents (COSMO-RS) and the universal solvent model based on solute electron density (SMD). According to various benchmarks, the approach performs well across a broad range of systems and applications, including hydration free energies, non-aqueous solvation free energies, and large supramolecular association reactions of neutral and charged species. Our method for computing solvation free energies is much more accurate than the current methods in the xtb program package. It improves the accuracy of solvation free energies by up to 40% for larger supramolecular association reactions to match even the accuracy of higher-level DFT-based solvation models like COSMO-RS and SMD while being computationally more than 2 orders of magnitude faster. The proposed method and the underlying ddCOSMO model are readily available for a wide variety of solvents and are accessible in xtb for use in various computational applications.

Exploring Cuneanes as Potential Benzene Isosteres and Energetic Materials: Scope and Mechanistic Investigations into Regioselective Rearrangements from Cubanes

Cuneane is a strained hydrocarbon that can be accessed via metal-catalyzed isomerization of cubane. The carbon atoms of cuneane define a polyhedron of the C2v point group with six faces─two triangular, two quadrilateral, and two pentagonal. The rigidity, strain, and unique exit vectors of the cuneane skeleton make it a potential scaffold of interest for the synthesis of functional small molecules and materials. However, the limited previous synthetic efforts toward cuneanes have focused on monosubstituted or redundantly substituted systems such as permethylated, perfluorinated, and bis(hydroxymethylated) cuneanes. Such compounds, particularly rotationally symmetric redundantly substituted cuneanes, have limited potential as building blocks for the synthesis of complex molecules. Reliable, predictable, and selective syntheses of polysubstituted cuneanes bearing more complex substitution patterns would facilitate the study of this ring system in myriad applications. Herein, we report the regioselective, AgI-catalyzed isomerization of asymmetrically 1,4-disubstituted cubanes to cuneanes. In-depth DFT calculations provide a charge-controlled regioselectivity model, and direct dynamics simulations indicate that the nonclassical carbocation invoked is short-lived and dynamic effects augment the charge model.

Strategy of Choosing Templates in Molecular Imprinting to Expand the Recognition Width for Family-Selectivity

The class-selective molecular-imprinted polymers (MIPs) have shown the recognition ability to multiple targeted molecules through using one or multiple templates. However, choosing the right templates, the core problem, still lacks a systemic guide and decision-making. In this work, we propose a strategy of selecting templates through expanding the recognition width for the improvement of class-selectivity. First, three families of genotoxic impurity (GTI) were selected as model objects, and the spatial size and binding energy of each GTI-monomer complexes were obtained and compared by computational simulation. The two indexes of energy width (W_E) and size width (W_L) were introduced to compare the similarity and differences on the two recognition factors, binding strength and spatial size, among these GTIs in each family. Through shortening the width to increase similarity on binding energy and size, the dual templates in the aromatic amines (AI) family and sulfonic acid esters (SI) family were successfully selected. Correspondingly, the prepared dual-template MIPs in the two GTI families can simultaneously recognize all the GTIs comparing with that of single template MIP, respectively. Meanwhile, through comparing the adsorption capacity of the selected template and its analogues in one GTI family, the recognition efficiency of the dual-template MIPs was higher than that of the single-template MIP. This indicates that though using the selected right templates, the higher class-selectivity and the larger recognition width can be realized. Thus, this work can solve the problem of blind template selection, and provide the useful theoretical guidance for designing family-selective molecular imprinting.

ONIOM meets : efficient, accurate, and robust multi-layer simulations across the periodic table

The computational treatment of large molecular structures is of increasing interest in fields of modern chemistry. Accordingly, efficient quantum chemical approaches are needed to perform sophisticated investigations on such systems. This engaged the development of the well-established "Our own N-layered integrated molecular orbital and molecular mechanics" (ONIOM) multi-layer scheme [L. W. Chung et al., Chem. Rev., 2015, 115, 5678-5796]. In this work, we present the specific implementation of the ONIOM scheme into the xtb semi-empirical extended tight-binding program package and its application to challenging transition-metal complexes. The efficient and broadly applicable GFNn-xTB and -FF methods are applied in the ONIOM framework to elucidate reaction energies, geometry optimizations, and explicit solvation effects for metal-organic systems with up to several hundreds of atoms. It is shown that an ONIOM-based combination of density functional theory, semi-empirical, and force-field methods can be used to drastically reduce the computational costs and thus enable the investigation of huge systems at almost no significant loss in accuracy.