B97-3c: A revised low-cost variant of the B97-D density functional method

Lentinan-based pH-responsive nanoparticles achieve the combination therapy of tumors

Cancer poses a significant threat to human health, and there is an urgent need for more effective treatments. Combining chemotherapy and immunotherapy is an effective strategy to enhance curative outcomes and holds great potential for widespread application. The natural phytochemical genistein (GEN) exhibits cytotoxicity against tumors and is a potential chemotherapeutic agent. Lentinan (LTN) is a natural polysaccharide with immune-enhancing properties that has been utilized in tumor treatment. This study constructed a pH-responsive nanoparticle GEN@LTN-BDBA with chemotherapy and immunotherapy functions using GEN and LTN. After characterizing the nanoparticles, the molecular mechanism of GEN@LTN-BDBA formation was explored using in silico simulation. GEN@LTN-BDBA can significantly inhibit the proliferation of A549 and HepG2 cells in vitro. The in vivo experiment results demonstrated that treatment with GEN@LTN-BDBA can significantly reduce tumor cell mass and prevent metastasis. In this nanoparticle, GEN induced oxidative stress and apoptosis of tumor cells. Meanwhile, the released LTN initiated an anti-tumor immune response by promoting dendritic cell (DC) maturation and upregulating the expression of costimulatory molecules and major histocompatibility complex. The construction method of GEN@LTN-BDBA can be extended to the preparation of other polysaccharides and hydrophobic chemotherapy molecules, offering a novel strategy to enhance the efficacy of monotherapy.

Predicting redox potentials by graph-based machine learning methods

The evaluation of oxidation and reduction potentials is a pivotal task in various chemical fields. However, their accurate prediction by theoretical computations, which is a complementary task and sometimes the only alternative to experimental measurement, may be often resource-intensive and time-consuming. This paper addresses this challenge through the application of machine learning techniques, with a particular focus on graph-based methods (such as graph edit distances, graph kernels, and graph neural networks) that are reviewed to enlighten their deep links with theoretical chemistry. To this aim, we establish the ORedOx159 database, a comprehensive, homogeneous (with reference values stemming from density functional theory calculations), and reliable resource containing 318 one-electron reduction and oxidation reactions and featuring 159 large organic compounds. Subsequently, we provide an instructive overview of the good practice in machine learning and of commonly utilized machine learning models. We then assess their predictive performances on the ORedOx159 dataset through extensive analyses. Our simulations using descriptors that are computed in an almost instantaneous way result in a notable improvement in prediction accuracy, with mean absolute error (MAE) values equal to 5.6 kcal mol- 1 for reduction and 7.2 kcal mol- 1 for oxidation potentials, which paves a way toward efficient in silico design of new electrochemical systems.

Machine learning-driven investigation of the structure and dynamics of the BMIM-BF4 room temperature ionic liquid

Room-temperature ionic liquids are an exciting group of materials with the potential to revolutionize energy storage. Due to their chemical structure and means of interaction, they are challenging to study computationally. Classical descriptions of their inter- and intra-molecular interactions require time intensive parametrization of force-fields which is prone to assumptions. While ab initio molecular dynamics approaches can capture all necessary interactions, they are too slow to achieve the time and length scales required. In this work, we take a step towards addressing these challenges by applying state-of-the-art machine-learned potentials to the simulation of 1-butyl-3-methylimidazolium tetrafluoroborate. We demonstrate a learning-on-the-fly procedure to train machine-learned potentials from single-point density functional theory calculations before performing production molecular dynamics simulations. Obtained structural and dynamical properties are in good agreement with computational and experimental references. Furthermore, our results show that hybrid machine-learned potentials can contribute to an improved prediction accuracy by mitigating the inherent shortsightedness of the models. Given that room-temperature ionic liquids necessitate long simulations to address their slow dynamics, achieving an optimal balance between accuracy and computational cost becomes imperative. To facilitate further investigation of these materials, we have made our IPSuite-based training and simulation workflow publicly accessible, enabling easy replication or adaptation to similar systems.

Controlling achiral and chiral conformations of benzyl alcohol by ortho-halogenation, collisional relaxation and dimerisation

Ortho-Halogenated benzyl alcohol can exist in two different low energy chiral conformations, only one of them with an OH-X contact (X = Cl, Br, I). A third, achiral conformation is enabled by the halogen substitution. We show by IR spectroscopy in supersonic jets that the achiral monomer is less stable than the chiral conformation with OH-X contact, but both can be produced in similar amounts using helium as a carrier gas. The robust OH transition observed for the achiral monomer is a sensitive benchmark for the conformational energy sequence, since the chiral conformation without OH-X contact is at least an order of magnitude less abundant, although it is often predicted by DFT to be slightly more stable and separated from the achiral conformation by a low barrier. This competing chiral conformation must be energetically higher by at least a few tenths of a kJ mol-1 to be consistent with experimental observations. That is indeed predicted by high-level energy calculations at the DFT-optimised structures. The most stable dimers of ortho-halogenated benzyl alcohols involve torsionally homo- and heterochiral pairings of the two OH groups, where the hydrogen bond-accepting OH group forms a cooperative intramolecular OH-X contact. The achiral monomer conformation is suppressed in these dimers. A homochiral dimer is formed almost exclusively for Cl, whereas its heterochiral variant is progressively co-stabilised with increasing halogen size. The stretching wavenumber of the donor OH in the dimers depends on the relative chirality of the donor and acceptor conformations. The consistent picture that emerges for Cl, Br and I substitution in ortho-position of benzyl alcohol is discussed in the context of interconversion barriers, heavy atom tunneling, π-π stacking, suppression of OH-π bonding, chirality synchronisation, and shortcomings of DFT approaches in reproducing the observations. The homochiral aggregation preference observed for simple benzyl alcohol is conserved and even enhanced upon ortho-halogenation, albeit partly by different interactions.

Massive Assessment of the Geometries of Atmospheric Molecular Clusters

Atmospheric molecular clusters are important for the formation of new aerosol particles in the air. However, current experimental techniques are not able to yield direct insight into the cluster geometries. This implies that to date there is limited information about how accurately the applied computational methods depict the cluster structures. Here we massively benchmark the molecular geometries of atmospheric molecular clusters. We initially assessed how well different DF-MP2 approaches reproduce the geometries of 45 dimer clusters obtained at a high DF-CCSD(T)-F12b/cc-pVDZ-F12 level of theory. Based on the results, we find that the DF-MP2/aug-cc-pVQZ level of theory best resembles the DF-CCSD(T)-F12b/cc-pVDZ-F12 reference level. We subsequently optimized 1283 acid-base cluster structures (up to tetramers) at the DF-MP2/aug-cc-pVQZ level of theory and assessed how more approximate methods reproduce the geometries. Out of the tested semiempirical methods, we find that the newly parametrized atmospheric molecular cluster extended tight binding method (AMC-xTB) is most reliable for locating the correct lowest energy configuration and yields the lowest root mean square deviation (RMSD) compared to the reference level. In addition, we find that the DFT-3c methods show similar performance as the usually employed ωB97X-D/6-31++G(d,p) level of theory at a potentially reduced computational cost. This suggests that these methods could prove to be valuable for large-scale screening of cluster structures in the future.

The Bond Energy of the Carbon Skeleton in Polyaromatic Halohydrocarbon Molecules

We have investigated the thermochemical stability of the carbon skeleton in polycyclic aromatic (halo) hydrocarbons using a systematic collection of molecules (the PAHH343 set). With high-level quantum chemistry methods such as W1X-2, we have obtained chemically accurate (i. e.,±~5 kJ mol-1) "normalized carbon skeleton" bond energies. They are calculated by removing the C-H and C-X (X=F, Cl) bond energies from the total atomization energy, and then normalizing on a per-carbon basis. For species with isomeric halogen-substitution pattern, the energetic variation is generally small, though larger difference can also be seen due to structural distortion from steric repulsion. The skeleton energy becomes smaller with an increasing number of halogen atoms due to the withdrawal of electron density from the bonding orbitals, mainly through the σ-bonds. We have further assessed the performance of some low-cost quantum chemistry methods for the PAHH343 set. The deviations from reference values are largely systematic, and can thus be compensated for, yielding errors that are on average below 10 kJ mol-1. This provides the prospect for the study of an even wider range of PAHH and related systems.

Ultrafast Two-Color X-Ray Emission Spectroscopy Reveals Excited State Landscape in a Base Metal Dyad

Effective photoinduced charge transfer makes molecular bimetallic assemblies attractive for applications as active light-induced proton reduction systems. Developing competitive base metal dyads is mandatory for a more sustainable future. However, the electron transfer mechanisms from the photosensitizer to the proton reduction catalyst in base metal dyads remain so far unexplored. A Fe─Co dyad that exhibits photocatalytic H2 production activity is studied using femtosecond X-ray emission spectroscopy, complemented by ultrafast optical spectroscopy and theoretical time-dependent DFT calculations, to understand the electronic and structural dynamics after photoexcitation and during the subsequent charge transfer process from the FeII photosensitizer to the cobaloxime catalyst. This novel approach enables the simultaneous measurement of the transient X-ray emission at the iron and cobalt K-edges in a two-color experiment. With this methodology, the excited state dynamics are correlated to the electron transfer processes, and evidence of the Fe→Co electron transfer as an initial step of proton reduction activity is unraveled.

Mapping the correlations between bandgap, HOMO, and LUMO trends for meta substituted Zn-MOFs

Bandgap is a key property that determines electrical and optical properties in materials. Modulating the bandgap thus is critical in developing novel materials particularly semiconductors with improved features. This study examines the bandgap, highest occupied molecular orbital (HOMO), and lowest unoccupied molecular orbital (LUMO) energy level trends in a metal organic framework, metal-organic framework 5 (MOF-5), as a function of Hammett substituent effect (with the constant σm in the meta-position of the benzene ring) and solvent dielectric effect (with the constant ε). Specifically, experimental design and response surface methodologies helped to assess the significance of trends and correlations between these molecular properties with σm and ε. While the HOMO and LUMO decrease with increasing σm, the LUMO exhibits greater sensitivity to the substituent's electron withdrawing capability. The relative difference in these trends helps to explain why the bandgap tends to decrease with increasing σm.

A semi-automated quantum-mechanical workflow for the generation of molecular monolayers and aggregates

Organic electronics (OE) such as organic light-emitting diodes or organic solar cells represent an important and innovative research area to achieve global goals like environmentally friendly energy production. To accelerate OE material discovery, various computational methods are employed. For the initial generation of structures, a molecular cluster approach is employed. Here, we present a semi-automated workflow for the generation of monolayers and aggregates using the GFNn-xTB methods and composite density functional theory (DFT-3c). Furthermore, we present the novel D11A8MERO dye interaction energy benchmark with high-level coupled cluster reference interaction energies for the assessment of efficient quantum chemical and force-field methods. GFN2-xTB performs similar to low-cost DFT, reaching DFT/mGGA accuracy at two orders of magnitude lower computational cost. As an example application, we investigate the influence of the dye aggregate size on the optical and electrical properties and show that at least four molecules in a cluster model are needed for a qualitatively reasonable description.

A free radical interlocking co-deposition strategy based on the oxidative pyrolysis mechanism of polyethylene terephthalate to achieve green energy recovery

Accidental combustion and energy recovery of polyethylene terephthalate (PET) result in the formation of harmful organic substances and excessive emissions of CO2 and CO. This paper presents our recent efforts to unravel the formation mechanism of these harmful substances during the PET combustion process using thermal analysis and simulation calculations (DFT, CDFT, and ReaxFF). Our findings reveal that PET oxidative pyrolysis produces free radicals, harmful small molecule gases, and CO2. The interaction between aromatic free radicals and oxygen initiates unstable peroxy bonds, triggering uncontrollable chain exothermic reactions and producing oxygenated polycyclic aromatic hydrocarbon (OPAH) precursors. We propose a straightforward and eco-friendly free radical interlocking co-deposition inhibition strategy for PET by incorporating polycarbonate (PC). This strategy aims to facilitate green energy recovery by curbing OPAH formation and reducing CO2 and CO emissions during PET waste combustion. Our investigation into the oxidative pyrolysis of PET challenges conventional wisdom dominated by C-H bond fracture, paving the way for efficient, low-pollution green energy recovery.

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.

High Rotational Barrier Atropisomers

Atropisomers have attracted a great deal of attention lately due to their numerous applications in organic synthesis and to their employment in drug discovery. However, the synthetic arsenal at our disposal with which to access them remains limited. The research described herein is two-pronged; we both demonstrate the use of MCR chemistry as a synthetic strategy for the de novo synthesis of a class of atropisomers having high barriers to rotation with the simultaneous insertion of multiple chiral elements and we study these unprecedented molecular systems by employing a combination of crystallography, NMR and DFT calculations. By fully exploiting the synthetic capabilities of our chemistry, we have been able to monitor a range of different types of interaction, i. e. π-π, CH-π, heteroatom-π and CD-π, in order to conduct structure-property studies. The results could be applied both to atroposelective synthesis and in drug discovery.

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.

Cryo-EM structures of a mycobacterial ABC transporter that mediates rifampicin resistance

Drug-resistant Tuberculosis (TB) is a global public health problem. Resistance to rifampicin, the most effective drug for TB treatment, is a major growing concern. The etiological agent, Mycobacterium tuberculosis (Mtb), has a cluster of ATP-binding cassette (ABC) transporters which are responsible for drug resistance through active export. Here, we describe studies characterizing Mtb Rv1217c-1218c as an ABC transporter that can mediate mycobacterial resistance to rifampicin and have determined the cryo-electron microscopy structures of Rv1217c-1218c. The structures show Rv1217c-1218c has a type V exporter fold. In the absence of ATP, Rv1217c-1218c forms a periplasmic gate by two juxtaposed-membrane helices from each transmembrane domain (TMD), while the nucleotide-binding domains (NBDs) form a partially closed dimer which is held together by four salt-bridges. Adenylyl-imidodiphosphate (AMPPNP) binding induces a structural change where the NBDs become further closed to each other, which downstream translates to a closed conformation for the TMDs. AMPPNP binding results in the collapse of the outer leaflet cavity and the opening of the periplasmic gate, which was proposed to play a role in substrate export. The rifampicin-bound structure shows a hydrophobic and periplasm-facing cavity is involved in rifampicin binding. Phospholipid molecules are observed in all determined structures and form an integral part of the Rv1217c-1218c transporter system. Our results provide a structural basis for a mycobacterial ABC exporter that mediates rifampicin resistance, which can lead to different insights into combating rifampicin resistance.

Partial to Total Generation of 3D Transition-Metal Complexes

The design of transition-metal complexes (TMCs) has drawn much attention over the years because of their important applications as metallodrugs and functional materials. In this work, we present an extension of our recently reported approach, LigandDiff [Jin et al. J. Chem. Theory Comput. 20, 4377(2024)]. The new model, which we call multi-LigandDiff, is more flexible and greatly outperforms its predecessor. This scaffold-based diffusion model allows de novo ligand design with either existing ligands or without any ligand. Moreover, it allows users to predefine the denticity of the generated ligand. Our results indicate that multi-LigandDiff can generate well-defined ligands and is transferable to multiple transition metals and coordination geometries. In terms of its application, multi-LigandDiff successfully designed 338 Fe(II) spin-crossover (SCO) complexes from only 47 experimentally validated SCO complexes. And these generated complexes are configurationally diverse and structurally reasonable. Overall, the results show that multi-LigandDiff is an ideal tool to design novel TMCs from scratch.

State-of-the-art local correlation methods enable affordable gold standard quantum chemistry for up to hundreds of atoms

In this feature, we review the current capabilities of local electron correlation methods up to the coupled cluster model with single, double, and perturbative triple excitations [CCSD(T)], which is a gold standard in quantum chemistry. The main computational aspects of the local method types are assessed from the perspective of applications, but the focus is kept on how to achieve chemical accuracy (i.e., <1 kcal mol-1 uncertainty), as well as on the broad scope of chemical problems made accessible. The performance of state-of-the-art methods is also compared, including the most employed DLPNO and, in particular, our local natural orbital (LNO) CCSD(T) approach. The high accuracy and efficiency of the LNO method makes chemically accurate CCSD(T) computations accessible for molecules of hundreds of atoms with resources affordable to a broad computational community (days on a single CPU and 10-100 GB of memory). Recent developments in LNO-CCSD(T) enable systematic convergence and robust error estimates even for systems of complicated electronic structure or larger size (up to 1000 atoms). The predictive power of current local CCSD(T) methods, usually at about 1-2 order of magnitude higher cost than hybrid density functional theory (DFT), has become outstanding on the palette of computational chemistry applicable for molecules of practical interest. We also review more than 50 LNO-based and other advanced local-CCSD(T) applications for realistic, large systems across molecular interactions as well as main group, transition metal, bio-, and surface chemistry. The examples show that properly executed local-CCSD(T) can contribute to binding, reaction equilibrium, rate constants, etc. which are able to match measurements within the error estimates. These applications demonstrate that modern, open-access, and broadly affordable local methods, such as LNO-CCSD(T), already enable predictive computations and atomistic insight for complicated, real-life molecular processes in realistic environments.

Halogen-Bonded Organic Frameworks (XOFs) Based on N⋅⋅⋅Br+⋅⋅⋅N Bonds: Robust Organic Networks Constructed by Fragile Bonds

Organic frameworks face a trade-off between the framework stability and the bond dynamics, which necessitates the development of innovative linkages that can generate stable frameworks without hindering efficient synthesis. Although iodine(I)-based halogen-bonded organic frameworks (XOFs) have been developed, constructing XOFs based on bromine(I) is desirable yet challenging due to the high sensitivity of bromine(I) species. In this work, we present the inaugural construction of stable bromine(I)-bridged two-dimensional (2D) halogen-bonded organic frameworks, XOF(Br)-TPy-BF4/OTf, based on sensitive [N⋅⋅⋅Br⋅⋅⋅N]+ halogen bonds. The formation of XOF(Br)-TPy-BF4/OTf was monitored by 1H NMR, XPS, IR, SEM, TEM, HR-TEM, SEAD. Their framework structures were established by the results from PXRD, theoretical simulations and SAXS. More importantly, XOF(Br) displayed excellent chemical and thermal stabilities. They exhibited stable two-dimensional framework structures in various organic solvents and aqueous media, even over a wide pH range (pH 3-12), while the corresponding model compounds BrPy2BF4/OTf decomposed quickly even in the presence of minimal water. Furthermore, the influence of the counterions were investigated by replacing BF4 with OTf, which improved the stability of XOF(Br). This characteristic enabled XOF(Br) to serve as an efficient oxidizing reagent in aqueous environments, in contrast with the sensitivity of BrPy2BF4/OTf, which performed well only in organic media. This study not only deepens our fundamental understanding of organic frameworks but also opens new avenues for the development and application of multifunctional XOFs.

Molecular Interactions of Perfluorinated and Branched Fluorine-Free Surfactants at Interfaces: Insights from a New Reliable Force Field

Per- and polyfluoroalkyl substances (PFAS) constitute a class of synthetic compounds with exceptional interfacial properties. Their widespread use in many industrial applications and consumer products, combined with their remarkable chemical and thermal stability, has led to their ubiquitous presence in environmental matrices, including surface water and groundwater. To replace PFAS with fluorine-free surfactants, it is necessary first to develop a deep molecular-level understanding of the mechanisms responsible for the exceptional properties of PFAS. For instance, it has been shown that fluorine-free surfactants with highly branched or methylated chains can achieve low surface tensions at air-water interfaces and can provide highly hydrophobic surface coatings. Although molecular simulations combined with experiments are promising for uncovering these mechanisms, the reliability of simulation results depends strongly on the accuracy of the force fields implemented. At the moment, atomistic force fields are not available to describe PFAS in a variety of environments. Ab initio methods could help fill this knowledge gap, but they are computationally demanding. As an alternative, ab initio calculations could be used to develop accurate force fields for atomistic simulations. In this work, a new algorithm is proposed, which, built from accurate ab initio calculations, yields force fields for perfluorinated sulfonic and perfluoroalkyl acids. The accuracy of the new force field was benchmarked against solvation free energy and interfacial tension data. The new force fields were then used to probe the interfacial behavior of the PFAS surfactants. The interfacial properties observed in our simulations were compared with those manifested by two branched fluorine-free surfactants. The good agreement achieved with experiments and ab initio calculations suggests that the proposed protocol could be implemented to study other perfluorinated substances and help in the design of fluorine-free surfactants for targeted applications.

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.

Dynamic and solid-state behaviour of bromoisotrianglimine

Solid-state materials formed from discrete imine macrocycles have potential in industrial separations, but dynamic behaviour during both synthesis and crystallisation makes them challenging to exploit. Here, we explore opportunities for structural control by investigating the dynamic nature of a C-5 brominated isotrianglimine in solution and under crystallisation conditions. In solution, the equilibrium between the [3 + 3] and the less reported [2 + 2] macrocycle was investigated, and both macrocycles were fully characterised. Solvent templating during crystallisation was used to form new packing motifs for the [3 + 3] macrocycle and a previously unreported [4 + 4] macrocycle. Finally, chiral self-sorting was used to demonstrate how crystallisation conditions can not only influence packing arrangements but also shift the macrocycle equilibrium to yield new structures. This work thus exemplifies three strategies for exploiting dynamic behaviour to form isotrianglimine materials, and highlights the importance of understanding the dynamic behaviour of a system when designing and crystallising functional materials formed using dynamic covalent chemistry.

Quantum chemical package Jaguar: A survey of recent developments and unique features

This paper is dedicated to the quantum chemical package Jaguar, which is commercial software developed and distributed by Schrödinger, Inc. We discuss Jaguar's scientific features that are relevant to chemical research as well as describe those aspects of the program that are pertinent to the user interface, the organization of the computer code, and its maintenance and testing. Among the scientific topics that feature prominently in this paper are the quantum chemical methods grounded in the pseudospectral approach. A number of multistep workflows dependent on Jaguar are covered: prediction of protonation equilibria in aqueous solutions (particularly calculations of tautomeric stability and pKa), reactivity predictions based on automated transition state search, assembly of Boltzmann-averaged spectra such as vibrational and electronic circular dichroism, as well as nuclear magnetic resonance. Discussed also are quantum chemical calculations that are oriented toward materials science applications, in particular, prediction of properties of optoelectronic materials and organic semiconductors, and molecular catalyst design. The topic of treatment of conformations inevitably comes up in real world research projects and is considered as part of all the workflows mentioned above. In addition, we examine the role of machine learning methods in quantum chemical calculations performed by Jaguar, from auxiliary functions that return the approximate calculation runtime in a user interface, to prediction of actual molecular properties. The current work is second in a series of reviews of Jaguar, the first having been published more than ten years ago. Thus, this paper serves as a rare milestone on the path that is being traversed by Jaguar's development in more than thirty years of its existence.

Molecular simulations guide immobilization of lipase on nest-like ZIFs with regulatable hydrophilic/hydrophobic surface

The catalytic performance of immobilized lipase is greatly influenced by functional support, which attracts growing interest for designing supports to achieve their promotive catalytic activity. Many lipases bind strongly to hydrophobic surfaces where they undergo interfacial activation. Herein, the behavioral differences of lipases with distinct lid structures on interfaces of varying hydrophobicity levels were firstly investigated by molecular simulations. It was found that a reasonable hydrophilic/hydrophobic surface could facilitate the lipase to undergo interfacial activation. Building on these findings, a novel "nest"-like superhydrophobic ZIFs (ZIFN) composed of hydrophobic ligands was prepared for the first time and used to immobilize lipase from Aspergillus oryzae (AOL@ZIFN). The AOL@ZIFN exhibited 2.0-folds higher activity than free lipase in the hydrolysis of p-Nitrophenyl palmitate (p-NPP). Especially, the modification of superhydrophobic ZIFN with an appropriate amount of hydrophilic tannic acid can significantly improve the activity of the immobilized lipase (AOL@ZIFN-TA). The AOL@ZIFN-TA exhibited 30-folds higher activity than free lipase, and still maintained 82% of its initial activity after 5 consecutive cycles, indicating good reusability. These results demonstrated that nanomaterials with rational arrangement of the hydrophilic/hydrophobic surface could facilitate the lipase to undergo interfacial activation and improve its activity, displaying the potential of the extensive application.

Use of Interfacial Interactions and Complexation of Carbon Dots to Construct Ultra-Robust and Efficient Photothermal Film From Micro-Carbonized Polysaccharides

Solar energy conversion technologies, particularly solar-driven photothermal conversion, are both clean and manageable. Although much progress has been made in designing solar-driven photothermal materials, significant challenges remain, not least the photobleaching of organic dyes. To tackle these issues, micro-carbonized polysaccharide chains, with carbon dots (CDs) suspended from the chains, are conceived, just like grapes or tomatoes hanging from a vine. Carbonization of sodium carboxymethyl cellulose (CMC) produces just such a structure (termed CMC-g-CDs), which is used to produce an ultra-stable, robust, and efficient solar-thermal film by interfacial interactions within the CMC-g-CDs. The introduction of the CDs into the matrix of the photothermal material effectively avoided the problem of photobleaching. Manipulating the interfacial interactions (such as electrostatic interactions, van der Waals interactions, π-π stacking, and hydrogen bonding) between the CDs and the polymer chains markedly enhances the mechanical properties of the photothermal film. The CMC-g-CDs are complexed with Fe3+ to eliminate leakage of the photothermal reagent from the matrix and to solve the problem of poor water resistance. The resulting film (CMC-g-CDs-Fe) has excellent prospects for practical application as a photothermal film.

ΔDFT Predicts Inverted Singlet-Triplet Gaps with Chemical Accuracy at a Fraction of the Cost of Wave Function-Based Approaches

Efficient OLEDs need to quickly convert singlet and triplet excitons into photons. Molecules with an inverted singlet-triplet energy gap (INVEST) are promising candidates for this task. However, typical INVEST molecules have drawbacks like too low oscillator strengths and excitation energies. High-throughput screening could identify suitable INVEST molecules, but existing methods are problematic: The workhorse method TD-DFT cannot reproduce gap inversion, while wave function-based methods are too slow. This study proposes a state-specific method based on unrestricted Kohn-Sham DFT with common hybrid functionals. Tuned on the new INVEST15 benchmark set, this method achieves an error of less than 1 kcal/mol, which is traced back to error cancellation between spin contamination and dynamic correlation. Applied to the larger and structurally diverse NAH159 set in a black-box fashion, the method maintains a small error (1.2 kcal/mol) and accurately predicts gap signs in 83% of cases, confirming its robustness and suitability for screening workflows.

A co-assembly process for high strength and injectable dual network gels with sustained doxorubicin release performance

Adopting a non-covalent co-assembly strategy shows great potential in loading drugs efficiently and safely in drug delivery systems. However, finding an efficient method for developing high strength gels with thixotropic characteristics is still challenging. In this work, by hybridizing the low molecular weight gelator fluorenylmethyloxycarbonyl-phenylalanine (Fmoc-F) (first single network, 1st SN) and alginate (second single network, 2nd SN) into a dual network (DN) gel, gels with high strength as well as thixotropy were prepared efficiently. The DN gels showed high strength (103 Pa in SN gels and 105 Pa in DN gels) and thixotropic characteristics (yield strain <25%; recovery ratio >85% within 100 seconds). The application performance was verified by loading doxorubicin (DOX), showing better encapsulation capacity (77.06% in 1st SN, 59.11% in 2nd SN and 96.71% in DN) and sustained release performance (lasting one week under physiological conditions) than single network gels. Experimental and DFT results allowed the elaboration of the specific non-covalent co-assembly mechanism for DN gel formation and DOX loading. The DN gels were formed by co-assembly driven by H-bond and π-π stacking interactions and then strengthened by Ca2+-coupling. Most DOX molecules co-assembled with Fmoc-F and alginate through π-π stacking and H-bond interactions (DOX-I), with a few free DOX molecules (DOX-II) left. Proven by the release dynamics test, DOX was released through a diffusion-erosion process, in an order of DOX-I first and then DOX-II. This work suggests that non-covalent co-assembly is a useful technique for effective material strengthening and drug delivery.

Reconstruction of zinc-metal battery solvation structures operating from -50 ~ +100 °C

Serious solvation effect of zinc ions has been considered as the cause of the severe side reactions (hydrogen evolution, passivation, dendrites, and etc.) of aqueous zinc metal batteries. Even though the regulation of cationic solvation structure has been widely studied, effects of the anionic solvation structures on the zinc metal were rarely examined. Herein, co-reconstruction of anionic and cationic solvation structures was realized through constructing a new multi-component electrolyte (Zn(BF4)2-glycerol-boric acid-chitosan-polyacrylamide, simplified as ZGBCP), which incorporates double crosslinking network via the esterification, protonation and polymerization reactions, thereby combining multiple advantages of 'liquid-like' high conductivity, 'gel-like' robust interface, and 'solid-like' high Zn2+ transfer number. Based on the ZGBCP electrolyte, the Zn anodes achieve record-low polarization and stable cycling. Furthermore, the ZGBCP electrolyte renders the AZMBs ultrawide working temperature (-50 °C ~ +100 °C) and ultralong cycle life (30000 cycles), which further validates the feasibility of the dual solvation structure strategy and provides a innovative perspective for the development of high-performance AZMBs.

Mutual synergistic regulation of chloride anion and cesium cation binding using a new designed macrocyclic multi-functional sites receptor: A case of DFT computational prediction

The mutual synergistic regulation of the multi-functional sites on a single receptor molecule for ion-binding/recognition is vital for the new receptor design and needs to be well explored from experiment and theory. In this work, a new macrocyclic ion receptor (BEBUR) with three functional zones, including two ether holes and one biurea groups, is designed expecting to mutually enhance the ion-binding performance. The binding behaviors of BEBUR mainly for Cl- and Cs+ are deeply investigated by using density functional theoretical calculations. It is found that Cl-/Cs+ binding can be mutually enhanced and synergistically regulated via corresponding conformational changes of the receptor, well reflecting an electrical complementary matching and mutual reinforcement effect. Moreover, solvent effect calculations indicate that BEBUR may be an excellent candidate structure for Cl--binding with the enhancement of counter ion (Cs+) in water and toluene. In addition, visualization of intermolecular noncovalent interaction is used for analysis on the nature of the binding interactions between receptor and ions.

Air-Stable Arene Manganese Complexes as Catalysts for the Syngas-Assisted Direct Reductive Amination, Cyanation of Aldehyde, and CO2 Fixation by Epoxide with High Functional Groups Tolerance

Manganese complexes [(arene)Mn(CO)3]+ were prepared in one step from arenes and Mn(CO)5Br. They were found to be efficient catalysts in the carbonyl cyanation with TMSCN, CO2 fixation by epoxides, and direct reductive amination in the presence of syngas. The amination reaction tolerated various reducible functional groups. The synergy of carbon monoxide and hydrogen in syngas provides high efficiency of the catalytic system. The developed protocols do not require an inert atmosphere, and the catalysts can be handled in air.

Computational methods for investigating organic radical species

Computational analysis of organic radical species presents significant challenges. This study compares the efficacy of various DFT and wavefunction methods in predicting radical stabilisation energies, bond dissociation energies, and redox potentials for organic radicals. The hybrid meta-GGA M062X-D3(0), and the range-separated hybrids ωB97M-V and ωB97M-D3(BJ) emerged as the most reliable functionals, consistently providing accurate predictions across different basis sets including 6-311G**, cc-pVTZ, and def2-TZVP.

Solubility and Mass Transfer Performance of Ethane and n-Butane in Menthol and Decanoic Acid Deep Eutectic Solvent

The absorption performance and mechanism of the deep eutectic solvent (DES), composed of menthol and decanoic acid, were investigated. The solubility of volatile organic compounds (VOCs) in the DES was studied through saturation solution experiments, wherein the solubility of ethane and n-butane increases with a decrease in temperature and increasing pressure. Henry's law constants of ethane and n-butane in the DES at 288.2 K were 2.089 and 0.136 MPa, respectively, demonstrating the high solubility for light hydrocarbons that surpasses or equals that of ionic liquids. The mass transfer and regeneration performance of the DES were investigated by using dynamic bubbling experiments. Results demonstrated that the removal rate of both ethane and n-butane increased as the gas flow rate decreased and the VOC concentration in the model gas increased. Specifically, the removal rate of ethane reached 99.50% at a temperature of 293.2 K, a VOC concentration VOC of 10,000 μmol/mol, and a gas flow rate of 30 mL/min, while the removal rate of n-butane was higher than that of ethane under the same conditions, achieving a removal rate exceeding 99.99%. Furthermore, no significant decrease in the removal rate for n-butane was observed during the four regeneration processes. Interaction energies between the VOC molecule and DES were calculated using the quantum chemistry method. It was found that the interactions between the VOC molecule and DES are primarily attributed to dispersion attractive effects which belong to weak interactions; therefore, the absorption of light hydrocarbon by the DES belongs to a physical process. The DES has been proven to be effective for the recovery of light hydrocarbons, providing a promising approach to address the key challenge in comprehensive treatment of VOCs in the petrochemical industry.

Interfacial behaviour of short-chain fluorocarbon surfactants at the n-hexane/water interface: a molecular dynamics study

The utilization of long-chain fluorocarbon surfactants is restricted due to environmental regulations, prompting a shift in the focus of research towards short-chain fluorocarbon surfactants. The present study employs molecular dynamics techniques to model the behaviour of potassium perfluorobutylsulfonate (PFBS) at the n-hexane/water interface, aiming to investigate the efficacy of short-chain fluorocarbon surfactants in enhancing oil recovery. The findings suggest that ionized PFBS- has the ability to autonomously migrate to the oil/water interface, forming a layered thin film, with the sulfonic acid group being submerged in water, while the fluorocarbon chain is oriented towards the oil phase. This phenomenon aligns with the fundamental concept of surfactants in reducing interfacial tension between oil and water. The spontaneous dispersion process is supported by changes in the number of water molecules surrounding each PFBS- anion, as is well indicated by the number density distribution within the simulation box. Based on the analysis conducted by IGMH (Independent Gradient Model based on Hirshfeld partition), it was determined that sulfonic acid molecules are capable of forming hydrogen bonds with water molecules, whereas the interaction between fluorocarbon chains and the oil phase is predominantly characterized by weak van der Waals interactions.

Electrophotocatalysis Versus Indirect Electrolysis: Electrochemical Selenocyclization of 3-Aza-1,5-dienes Facilitated by Energy Transfer, Direct Photolysis or N-Hydroxyphthalimide

Three hybrid electrochemical protocols, which involve the energy transfer, direct photolysis and N-hydroxyphthalimide catalyst, respectively, are presented for the selenylation/cyclization of the fragile substrates of 3-aza-1,5-dienes with diorganyl diselenides to afford 3-selenomethyl-4-pyrrolin-2-ones. The two electrophotocatalytic reactions and the indirect electrolysis one are both regioselective and external-oxidant- and transition-metal-free, and are associated with a broad substrate scope and high Se-economy, and all three methods are amenable to gram-scale syntheses, late-stage functionalizations, sunlight-induced experiments and all-solar-driven syntheses.

Will We Witness Enzymatic or Pd-(Oligo)Peptide Catalysis in Suzuki Cross-Coupling Reactions?

Despite the development of numerous advanced ligands for Pd-catalyzed Suzuki cross-coupling reaction, the potential of (oligo)peptides serving as ligands remains unexplored. This study demonstrates via density functional theory (DFT) modeling that (oligo)peptide ligands can drive superior activity compared to classic phosphines in these reactions. The utilization of natural amino acids such as Met, SeMet, and His leads to strong binding of the Pd center, thereby ensuring substantial stability of the system. The increasing sustainability and economic viability of (oligo)peptide synthesis open new prospects for applying Pd-(oligo)peptide systems as greener catalysts. The feasibility of de novo engineering an artificial Pd-based enzyme for Suzuki cross-coupling is discussed, laying the groundwork for future innovations in catalytic systems.

Combining low-cost electronic structure theory and low-cost parallel computing architecture

The computational efficiency of low-cost electronic structure methods can be further improved by leveraging heterogenous computing architectures. The software package TeraChem has been developed since 2008 to make use of graphical processing units (GPUs), particularly their strong single-precision performance, for the acceleration of quantum chemical calculations. Here, we present the implementation of three low-cost methods, namely HF-3c, PBEh-3c, and the recently introduced ωB97X-3c. We show that these can benefit in terms of performance when combined with "consumer grade" GPUs by leveraging the mixed precision integral handling in TeraChem. The current limitation of the latter's GPU integral library is that Gaussian integrals only for functions with angular momentum l < 3 can be computed, which generally restricts the achievable accuracy in terms of the one-particle basis set. Particularly, the implementation of the ωB97X-3c method now enables higher accuracy with this setting which, in turn, provides the most efficient implementation accessible with consumer-grade hardware. We furthermore show that the implemented 3c methods can be combined with the hh-TDA formalism. This gives new and efficient low-cost multi-configurational excited states methods, which are benchmarked for the description of lowest vertical excitation energies in this work. All in all, the combination of these efficient electronic structure theory methods with affordable highly parallelized computing hardware provides an optimal computational and monetary cost to accuracy ratio.

Exploration of the polymorphic solid-state landscape of an amide-linked organic cage using computation and automation

Organic cages can possess complex, functionalised cavities that make them promising candidates for synthetic enzyme mimics. Conformationally flexible, chemically robust structures are needed for adaptable guest binding and catalysis, but rapidly exchanging systems are difficult to resolve in solution. Here, we use low-cost calculations and high-throughput crystallisation to identify accessible conformers of a recently reported organic cage by 'locking' them in the solid state. The conformers exhibit varying distances between the internal carboxylic acid groups, suggesting adaptability for binding a wide array of target guest molecules.

Choice of the Right Supporting Electrolyte in Electrochemical Reductions: A Principal Component Analysis

We present an analysis of a set of molecular, electrical, and electronic properties for a large number of the cations of quaternary ammonium salts usually employed as supporting electrolytes in cathodic reduction reactions. The goal of the present study is to define a measure for the quality of a supporting electrolyte in terms of the yield of the reaction considered. We performed a principal component analysis using the normalized values of the properties in order to lower the number of relevant reaction coordinates and find that the integral variance of 13 properties can well be represented by three principal components. The yield of the electrochemical hydrodimerization of acrylonitrile employing different quaternary ammonium salts as supporting electrolytes was determined in a series of experiments. We found only a very weak correlation between the yield and the values of the properties but a strong correlation between the yield and the values of the most important principal component. Very similar results are obtained for two further existing systematic experimental studies of the impact of the supporting electrolyte on the yield of cathodic reductions. For all three example reactions, a supervised regression using the two most important principal components as variables yields excellent values for the coefficients of determination. For comparison, we also applied our methodology to sets of purely structure-based features that are usually employed in cheminformatics and obtained results of almost similar quality. We therefore conjecture that our methodology in combination with a small number of experiments can be used to predict the yield of a given cathodic reduction on the basis of the properties of the supporting electrolyte.

Limiting factors in the accuracy of DFT calculation for redox potentials

In the present study, we have investigated factors affecting the accuracy of computational chemistry calculation of redox potentials, namely the gas-phase ionization energy (IE) and electron affinity (EA), and the continuum solvation effect. In general, double-hybrid density functional theory methods yield IEs and EAs that are on average within ~0.1 eV of our high-level W3X-L benchmark, with the best performing method being DSD-BLYP/ma-def2-QZVPP. For lower-cost methods, the average errors are ~0.2-0.3 eV, with ωB97X-3c being the most accurate (~0.15 eV). For the solvation component, essentially all methods have an average error of ~0.3 eV, which shows the limitation of the continuum solvation model. Curiously, the directly calculated redox potentials show errors of ~0.3 eV for all methods. These errors are notably smaller than what can be expected from error propagation with the two components (IE and EA, and solvation effect). Such a discrepancy can be attributed to the cancellation of errors, with the lowest-cost GFN2-xTB method benefiting the most, and the most accurate ωB97X-3c method benefiting the least. For organometallic species, the redox potentials show large deviations exceeding ~0.5 eV even for DSD-BLYP. The large errors are attributed to those for the gas-phase IEs and EAs, which represents a major barrier to the accurate calculation of redox potentials for such systems.

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.

Stepping-Stone CBH: Benchmark and Application of a Multilayered Isodesmic-Based Correction Scheme

We present a generalization of the connectivity-based hierarchy (CBH) of isodesmic-based correction schemes to a multilayered fragmentation platform for overall cost reduction while retaining high accuracy. The newly developed multilayered CBH approach, called stepping-stone CBH (SSCBH), is benchmarked on a diverse set of 959 medium-sized organic molecules. Applying SSCBH corrections to the PBEh-D3 density functional resulted in an average error of 0.76 kcal/mol for the full test set compared to accurate CCSD(T)-quality enthalpies and an even lower error of 0.44 kcal/mol on a subset containing only acyclic molecules. These results rival the traditional CBH-3 approach at a greatly reduced cost, allowing larger fragment corrections to be made at the MP2 level of theory rather than with G4. Our SSCBH approach will enable more widespread applications of CBH methods to a broader range of organic and biomolecular systems.

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.

Chiral Canoe-Like Pd0 or Pt0 Alloyed Copper Alkynyl Nanoclusters Display Near-Infrared Luminescence

Alloying nanoclusters (NCs) has emerged as a widely explored and versatile strategy for tailoring tunable properties, facilitating in-depth atomic-level investigations of structure-property correlations. In this study, we have successfully synthesized six atomically precise copper NCs alloyed with Group 10 metals (Pd or Pt). Notably, the Pd0 or Pt0 atom situated at the center of the distorted hexagonal antiprism Pd0/Pt0@Cu12 cage, coordinated with twelve Cu+ and two tBuC≡C- ligands. Moreover, ligand exchange strategies demonstrated the potential for Cl- and Br- to replace one or two alkynyl ligands positioned at the top or side of the NCs. The chirality exhibited by these racemic NCs is primarily attributed to the involvement of halogens and a chiral (Pd/Pt)@Cu18 skeleton. Furthermore, all the NCs exhibit near-infrared (NIR) luminescence, characterized by emission peaks at 705-755 nm, lifetimes ranging from 6.630 to 9.662 μs, and absolute photoluminescence quantum yields (PLQYs) of 1.75 %-2.52 % in their crystalline state. The experimental optical properties of these NCs are found to be in excellent agreement with the results of theoretical calculations. These alloy NCs not only offer valuable insights into the synthesis of Pd0/Pt0-Cu alloy NCs, but also bridge the gap in understanding the structure-luminescence relationships of Pd0/Pt0-Cu molecules.

The p-block challenge: assessing quantum chemistry methods for inorganic heterocycle dimerizations

The elements of the p-block of the periodic table are of high interest in various chemical and technical applications like frustrated Lewis-pairs (FLP) or opto-electronics. However, high-quality benchmark data to assess approximate density functional theory (DFT) for their theoretical description are sparse. In this work, we present a benchmark set of 604 dimerization energies of 302 "inorganic benzenes" composed of all non-carbon p-block elements of main groups III to VI up to polonium. This so-called IHD302 test set comprises two classes of structures formed by covalent bonding and by weaker donor-acceptor (WDA) interactions, respectively. Generating reliable reference data with ab initio methods is challenging due to large electron correlation contributions, core-valence correlation effects, and especially the slow basis set convergence. To compute reference values for these dimerization reactions, after thorough testing, we applied a computational protocol using state-of-the-art explicitly correlated local coupled cluster theory termed PNO-LCCSD(T)-F12/cc-VTZ-PP-F12(corr.). It includes a basis set correction at the PNO-LMP2-F12/aug-cc-pwCVTZ level. Based on these reference data, we assess 26 DFT methods in combination with three different dispersion corrections and the def2-QZVPP basis set, five composite DFT approaches, and five semi-empirical quantum mechanical methods. For the covalent dimerizations, the r2SCAN-D4 meta-GGA, the r2SCAN0-D4 and ωB97M-V hybrids, and the revDSD-PBEP86-D4 double-hybrid functional are found to be the best-performing methods among the evaluated functionals of the respective class. However, since def2 basis sets for the 4th period are not associated to relativistic pseudo-potentials, we obtained significant errors in the covalent dimerization energies (up to 6 kcal mol-1) for molecules containing p-block elements of the 4th period. Significant improvements were achieved for systems containing 4th row elements by using ECP10MDF pseudopotentials along with re-contracted aug-cc-pVQZ-PP-KS basis sets introduced in this work with the contraction coefficients taken from atomic DFT (PBE0) calculations. Overall, the IHD302 set represents a challenge to contemporary quantum chemical methods. This is due to a large number of spatially close p-element bonds which are underrepresented in other benchmark sets, and the partial covalent bonding character for the WDA interactions. The IHD302 set may be helpful to develop more robust and transferable approximate quantum chemical methods in the future.

para-Phenylenediamine Dimer as a Redox-Active Guest for Supramolecular Systems

Redox-active components are highly valuable in the construction of molecular devices. We combined two p-phenylenediamines (p-PDA) with a biphenyl (BiPhe) unit to prepare a supramolecular guest 4 consisting of three binding sites for cucurbit[7/8]uril (CBn) and/or cyclodextrins (CD). Supramolecular properties of 4 were investigated using NMR, UV-vis, mass spectrometry and isothermal titration calorimetry. Our analysis revealed that 4 forms higher-order host-guest complexes, wherein a CD unit occupies the central BiPhe site, secured by two CBn units at the terminal p-PDA sites. Additionally, 1 : 1 complexes with α-CD and β-CD, a 1 : 2 complex with γ-CD and 2 : 1 complexes with CB7 and CB8 were identified. Through UV-vis and cyclic voltammetry, redox processes leading to the formation of a stable, deep blue dication diradical of 4 are elucidated. Furthermore, it is demonstrated that CB7 selectively protects oxidised 4 from reduction in the presence of a reducing agent. The supramolecular and redox properties of the structural motif represented by 4 render it an interesting candidate for the construction of supramolecular devices.

Design and Synthesis of Novel Macrocyclic Derivatives as Potent and Selective Cyclin-Dependent Kinase 7 Inhibitors

The duality of function (cell cycle regulation and gene transcription) of cyclin-dependent kinase 7 (CDK7) makes it an attractive oncology target and the discovery of CDK7 inhibitors has been a long-term pursuit by academia and pharmaceutical companies. However, achieving selective leading compounds is still difficult owing to the similarities among the ATP binding pocket. Herein, we detail the design and synthesis of a series of macrocyclic derivatives with pyrazolo[1,5-a]-1,3,5-triazine core structure as potent and selective CDK7 inhibitors. The diverse manners of macrocyclization led to distinguished selectivity profiles of the CDK family. Molecular dynamics (MD) simulation explained the binding difference between 15- and 16-membered macrocyclic compounds. Further optimization generated compound 37 exhibiting good CDK7 inhibitory activity and high selectivity over other CDKs. This work clearly demonstrated macrocyclization is a versatile method to finely tune the selectivity profile of small molecules and MD simulation can be a valuable tool in prioritizing designs of the macrocycle.

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.

Exploring the Potential Mechanisms of Guanxinshutong Capsules in Treating Pathological Cardiac Hypertrophy based on Network Pharmacology, Computer-Aided Drug Design, and Animal Experiments

Cardiovascular diseases (CVDs) are significant causes of morbidity and mortality worldwide, and pathological cardiac hypertrophy (PCH) is an essential predictor of many heart diseases. Guanxinshutong capsule (GXST) is a Chinese patent medicine widely used in the clinical treatment of CVD, In our previous research, we identified 111 compounds of GXST. In order to reveal the potential molecular mechanisms by which GXST treats PCH, this study employed network pharmacology methods to screen for the active ingredients of GXST in treating PCH and predicted the potential targets. The results identified 26 active ingredients of GXST and 110 potential targets for PCH. Through a protein-protein interaction (PPI) network, gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, we confirmed AKT1, MAPK1, and MAPK3 as the core proteins in GXST treatment of PCH, thus establishing the PI3K/AKT and MAPK signaling pathways as the significant mechanisms of GXST in treating PCH. The results of molecular docking (MD) demonstrate that flavonoid naringenin and diterpenoid tanshinone iia have the highest binding affinity with the core protein. Before performing molecular dynamics simulations (MDSs), the geometric structure of naringenin and tanshinone iia was optimized using density functional theory (DFT) at the B97-3c level, and RESP2 atomic charge calculations were carried out at the B3LYP-D3(BJ)/def2-TZVP level. Further MDS results demonstrated that in the human body environment, the complex of naringenin and tanshinone iii with core proteins exhibited high stability, flexibility, and low binding free energy. Additionally, naringenin and tanshinone iia showed favorable absorption, distribution, metabolism, excretion, and toxicity (ADMET) characteristics and passed the drug similarity (DS) assessment. Ultrasound cardiograms and cardiac morphometric measurements in animal experiments demonstrate that GXST can improve the PCH induced by isoproterenol (ISO). Protein immunoblotting results indicate that GXST increases the expression of P-eNOS and eNOS by activating the PI3K/AKT signaling pathway and the MAPK signaling pathway, further elucidating the mechanism of action of GXST in treating PCH. This study contributes to the elucidation of the key ingredients and molecular mechanisms of GXST in treating PCH.

Predicting valence tautomerism in diverse cobalt-dioxolene complexes: elucidation of the role of ligands and solvent

The ability of molecular switches to reversibly interconvert between different forms promises potential applications at the scale of single molecules up to bulk materials. One type of molecular switch comprises cobalt-dioxolene compounds that exhibit thermally-induced valence tautomerism (VT) interconversions between low spin Co(iii)-catecholate (LS-CoIII-cat) and high spin Co(ii)-semiquinonate (HS-CoII-sq) forms. Two families of these compounds have been investigated for decades but have generally been considered separately: neutral [Co(diox)(sq)(N2L)] and cationic [Co(diox)(N4L)]+ complexes (diox = generic dioxolene, N2L/N4L = bidentate/tetradentate N-donor ancillary ligand). Computational identification of promising new candidate compounds prior to experimental exploration is beneficial for environmental and cost considerations but requires a thorough understanding of the underlying thermochemical parameters that influence the switching. Herein, we report a robust approach for the analysis of both cobalt-dioxolene families, which involved a quantitative density functional theory-based study benchmarked with reliable quasi-experimental references. The best-performing M06L-D4/def2-TZVPP level of theory has subsequently been verified by the synthesis and experimental investigation of three new complexes, two of which exhibit thermally-induced VT, while the third remains in the LS-CoIII-cat form across all temperatures, in agreement with prediction. Valence tautomerism in solution is markedly solvent-dependent, but the origin of this has not been definitively established. We have extended our computational approach to elucidate the correlation of VT transition temperature with solvent stabilisation energy and change in dipole moment. This new understanding may inform the development of VT compounds for applications in soft materials including films, gels, and polymers.

Investigating the diastereoselective synthesis of a macrocycle under Curtin-Hammett control

This work sheds new light on the stereoselective synthesis of chiral macrocycles containing twisted aromatic units, valuable π-conjugated materials for recognition, sensing, and optoelectronics. For the first time, we use the Curtin-Hammett principle to investigate a chiral macrocyclisation reaction, revealing the potential for supramolecular π-π interactions to direct the outcome of a dynamic kinetic resolution, favouring the opposite macrocyclic product to that expected under reversible, thermodynamically controlled conditions. Specifically, a dynamic, racemic perylene diimide dye (1 : 1 P : M) is strapped with an enantiopure (S)-1,1'-bi-2-naphthol group (P-BINOL) to form two diastereomeric macrocyclic products, the homochiral macrocycle (PP) and the heterochiral species (PM). We find there is notable selectivity for the PM macrocycle (dr = 4 : 1), which is rationalised by kinetic templation from intramolecular aromatic non-covalent interactions between the P-BINOL π-donor and the M-PDI π-acceptor during the macrocyclisation reaction.

Toward Post-Hartree-Fock Accuracy for Protein-Ligand Affinities Using the Molecules-in-Molecules Fragmentation-Based Method

The complexity and size of large molecular systems, such as protein-ligand complexes, pose computational challenges for accurate post-Hartree-Fock calculations. This study delivers a thorough benchmarking of the Molecules-in-Molecules (MIM) method, presenting a clear and accessible strategy for layer/theory selections in post-Hartree-Fock computations on substantial molecular systems, notably protein-ligand complexes. An approach is articulated, enabling augmented computational efficiency by strategically canceling out common subsystem energy terms between complexes and proteins within the supermolecular equation. Employing DLPNO-based post-Hartree-Fock methods in conjunction with the three-layer MIM method (MIM3), this study demonstrates the achievement of protein-ligand binding energies with remarkable accuracy (errors <1 kcal mol-1), while significantly reducing computational costs. Furthermore, noteworthy correlations between theoretically computed interaction energies and their experimental equivalents were observed, with R2 values of approximately 0.90 and 0.78 for CDK2 and BZT-ITK sets, respectively, thus validating the efficacy of the MIM method in calculating binding energies. By highlighting the crucial role of diffuse or small Pople-style basis sets in the middle layer for reducing energy errors, this work provides valuable insights and practical methodologies for interaction energy computations in large molecular complexes and opens avenues for their application across a diverse range of molecular systems.