Automated Molecular Cluster Growing for Explicit Solvation by Efficient Force Field and Tight Binding Methods

Vibrational circular dichroism spectra of proline in water at different pH values

Recording VCD spectra of aqueous solution poses a particular challenge as water is a strong infrared absorber. Likewise, the computational analysis of VCD spectra by means of DFT-based spectral calculations requires the consideration of explicit solvent molecules, thus posing an even greater challenge. Several studies suggested that by modeling the solvent environment with a few water molecules in a micro-solvation approach would be sufficient to describe experimental spectra. For example, using proline at different pH values, we herein show that a change in the relative spatial orientation of a single water molecule in five-fold solvated structures strongly affects the computed VCD spectral signatures and that Boltzmann-weighted spectra do not correctly reproduce the experiment. We thus explored an approach based on molecular dynamics and subsequent DFT-calculations, in which we considered 30 water molecules (about 1.5 solvation shells). Once again, it was found that the Boltzmann-weighted spectra obtained on the basis of several hundred structures did not correctly reproduce experimental signatures, and a simple averaging scheme resulted in well-matching spectra with comparable bandwidths. The rationale behind the procedure was that sampling the configurational space of the solvent molecules is as equally important as the conformational sampling of the solute. For conformationally more flexible molecules, it is assumed that a much larger set of structures will have to be computed in order to properly sample the conformational space of both solute and solvent.

Biomimetic nanoplatforms constructed from dialkylaminostyryl hetarene dyes and phospholipids exhibiting selective fluorescent response to specific proteins

The present work explores the specificity of supramolecular assemblies comprising dialkylaminostyrylhetarene dye molecules incorporated into phosphatidylcholine (PC) or phosphatidylserine (PS) aggregates. In PS-based assemblies, the dyes demonstrate a concentration-dependent fluorescent response, distinguishing anionic proteins such as bovine serum albumin (BSA) and pepsin from lysozyme (LYZ) in aqueous solutions. Conversely, no significant response is observed when the dyes are incorporated into the well-organized bilayers of neutral PC. The fluorescent response arises from the binding of dyes to proteins, leading to the detachment of dye molecules from the assemblies, rather than from the binding of proteins to the assemblies, although the latter process is facilitated by electrostatic attraction. Thus, both the poor ordering of PS molecules and the interfacial arrangement of the dyes are prerequisites for the fluorescent response of dye-PS aggregates. The structure of the dyes significantly impacts the spectral features of dye-PS and dye-protein assemblies. An optimal dye structure has been identified for the recognition of BSA, with a limit of detection (LOD) of 10.8 nM.

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.

A human-machine interface for automatic exploration of chemical reaction networks

Autonomous reaction network exploration algorithms offer a systematic approach to explore mechanisms of complex chemical processes. However, the resulting reaction networks are so vast that an exploration of all potentially accessible intermediates is computationally too demanding. This renders brute-force explorations unfeasible, while explorations with completely pre-defined intermediates or hard-wired chemical constraints, such as element-specific coordination numbers, are not flexible enough for complex chemical systems. Here, we introduce a STEERING WHEEL to guide an otherwise unbiased automated exploration. The STEERING WHEEL algorithm is intuitive, generally applicable, and enables one to focus on specific regions of an emerging network. It also allows for guiding automated data generation in the context of mechanism exploration, catalyst design, and other chemical optimization challenges. The algorithm is demonstrated for reaction mechanism elucidation of transition metal catalysts. We highlight how to explore catalytic cycles in a systematic and reproducible way. The exploration objectives are fully adjustable, allowing one to harness the STEERING WHEEL for both structure-specific (accurate) calculations as well as for broad high-throughput screening of possible reaction intermediates.

GFN-xTB-Based Computations Provide Comprehensive Insights into Emulsion Radiation-Induced Graft Polymerization

In this article, a deep insight into emulsion radiation-induced graft polymerization (RIGP) was obtained by computing explicit solvation free energies, conformational entropy, monomer radius and dipole moments with the state-of-the-art Conformer-Rotamer Ensemble Sampling Tool (CREST) package primarily at semiempirical GFN-xTB level. By leveraging the robustness of the CREST package, above parameters provided dynamic nature of methacrylate monomers with the consideration of realistic emulsion conditions. With the chemical and physical importance of the above results, CREST-determined explanatory variables sufficiently led to the building of the prediction models for the RIGP of methacrylate monomers. The machine learning model building resulted in effective reactivity predictions and unveiled important factors for the radiation-induced graft polymerization in a chemically interpretable fashion.

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.

Role of Explicit Solvation in Computational Modeling of Chemical Reactions: Mechanism of Cu(I) Transfer Between Thiolate-Based Chelators in Water

Solvation plays important roles in controlling the thermodynamic and kinetic aspects of chemical reactions. The conventional approaches to treat solvation via electronic structure methods are likely to become inadequate, when the reacting solutes have strong electrostatic and hydrogen bonding interactions with the solvent and undergo significant structural changes during the course of the reaction. In this article, we present evidence of such solvent and structural effects in the computational study of the Cu(I) transfer reaction between thiolate-based chelators dithiobutylamine (DTBA) and dithiotheritol (DTT) in water, inspired from biological copper trafficking phenomena. We propose a general solution to the problem by combining classical molecular dynamics (MD) simulations of the bulk system and static quantum chemistry calculations. The fluctuating solvation shell was estimated from MD, and energetics was assessed by averaging QM energies of a series of molecular clusters constructed from the MD snapshots. Applying this approach, we propose a reaction pathway with estimates of relative intermediate stabilities and barriers, which suggest the overall reaction to be reversible in nature and likely to go through both two and three coordinated intermediates, confirming previous studies of similar protein analogues. An interesting fact that emerged from our study was the strong indication that the rate-determining step is the deprotonation of initial thiol bound Cu(I) complex, without involving any Cu(I)-S bonds. The proposed method will lead to a better treatment of solvations, and these mechanistic insights will aid our understanding of biological copper(I) trafficking.

Computationally assisted vibrational spectroscopy of nucleic acid bases. 2. Thymine

As in the case of cytosine [Phys. Chem. Chem. Phys. 2023, 25, 24121-24128], Raman and infrared (IR) spectra of aqueous thymine and its N-deuterated derivative, thymine-d2 have been computationally reproduced and interpreted with the use of the recently developed efficient protocol to explicit quantum mechanical modeling of structure and IR spectra of liquids and solutions [J. Phys. Chem. B, 2020, 124, 6664-6670]. A cluster model of a solute surrounded by 30 water molecules is shown to be sufficient to reproduce experimental vibrational frequencies and relative Raman intensities with the use of B3LYP-D3/def2-TZVP or B3LYP-D3/aug-cc-pVDZ simulations. Analogous PBE-D3 computations provided a less good, but still reasonably accurate, modeling of Raman spectra. It is shown that strong changes of frequencies and relative intensities of the Raman bands of thymine, caused by its hydration, can be interpreted mainly as a result of hydrogen bonding with 6 nearest water molecules. Non-negligible improvement of the quality of simulations for larger clusters comprising water molecules that do not have direct contacts with the solute, suggests that spectroscopic effects of hydration should be ascribed to the joined action of solute-solvent and solvent-solvent interactions. Nevertheless, the moderate number of water molecules required for successful simulations of the Raman spectra of aqueous thymine, suggests that the vibrational modes and derivatives of the polarizability of the solute are mainly locally influenced, while the effect of bulk water is rather modest.

Conformational energies of biomolecules in solution: Extending the MPCONF196 benchmark with explicit water molecules

A prerequisite for the computational prediction of molecular properties like conformational energies of biomolecules is a reliable, robust, and computationally affordable method usually selected according to its performance for relevant benchmark sets. However, most of these sets comprise molecules in the gas phase and do not cover interactions with a solvent, even though biomolecules typically occur in aqueous solution. To address this issue, we introduce a with explicit water molecules solvated version of a gas-phase benchmark set containing 196 conformers of 13 peptides and other relevant macrocycles, namely MPCONF196 [J. Řezáč et al., JCTC 2018, 14, 1254-1266], and provide very accurate PNO-LCCSD(T)-F12b/AVQZ' reference values. The novel solvMPCONF196 benchmark set features two additional challenges beyond the description of conformers in the gas phase: conformer-water and water-water interactions. The overall best performing method for this set is the double hybrid revDSDPBEP86-D4/def2-QZVPP yielding conformational energies of almost coupled cluster quality. Furthermore, some (meta-)GGAs and hybrid functionals like B97M-V and ω B97M-D with a large basis set reproduce the coupled cluster reference with an MAD below 1 kcal mol- 1  . If more efficient methods are required, the composite DFT-method r2 SCAN-3c (MAD of 1.2 kcal mol- 1 ) is a good alternative, and when conformational energies of polypeptides or macrocycles with more than 500-1000 atoms are in the focus, the semi-empirical GFN2-xTB or the MMFF94 force field (for very large systems) are recommended.

Two Allogons of an O2 -activating Bis(disiloxido)ferrate(II) Accessible Selectively just by Variation of the Crystallization Temperature

Deprotonation of O(iPr2 SiOH)2 (iPr LH2 ) with LiOtBu followed by reaction with FeCl2 in THF led to the complex [iPr L2 Fe][Li(THF)2 ]2 , 2, which represents a structural and spectroscopic model of the α-Fe sites of Fe/ZSM-5. Reaction with O2 in THF solution proceeds rather fast and is complete within 200 ms; an intermediate O2 adduct could not be identified by stopped-flow methods. Cooling blue solutions of 2 to -80 °C led to the growth of blue crystals of 2⋅THF, the analysis of which by XRD revealed a FeO4 core that is somewhat distorted from planarity towards a tetrahedral structure. By contrast, cooling such solutions to -30 °C led to pink crystals of an allogon featuring a perfectly square planar FeO4 entity. Hence, 2 represents a unique case where two different structural isomers (allogons) can be crystallized from the same solvent selectively, controlled by the temperature. DFT calculations were performed to understand this finding.

Molecular Gas-Phase Conformational Ensembles

Accurately determining the global minima of a molecular structure is important in diverse scientific fields, including drug design, materials science, and chemical synthesis. Conformational search engines serve as valuable tools for exploring the extensive conformational space of molecules and for identifying energetically favorable conformations. In this study, we present a comparison of Auto3D, CREST, Balloon, and ETKDG (from RDKit), which are freely available conformational search engines, to evaluate their effectiveness in locating global minima. These engines employ distinct methodologies, including machine learning (ML) potential-based, semiempirical, and force field-based approaches. To validate these methods, we propose the use of collisional cross-section (CCS) values obtained from ion mobility-mass spectrometry studies. We hypothesize that experimental gas-phase CCS values can provide experimental evidence that we likely have the global minimum for a given molecule. To facilitate this effort, we used our gas-phase conformation library (GPCL) which currently consists of the full ensembles of 20 small molecules and can be used by the community to validate any conformational search engine. Further members of the GPCL can be readily created for any molecule of interest using our standard workflow used to compute CCS values, expanding the ability of the GPCL in validation exercises. These innovative validation techniques enhance our understanding of the conformational landscape and provide valuable insights into the performance of conformational generation engines. Our findings shed light on the strengths and limitations of each search engine, enabling informed decisions for their utilization in various scientific fields, where accurate molecular structure determination is crucial for understanding biological activity and designing targeted interventions. By facilitating the identification of reliable conformations, this study significantly contributes to enhancing the efficiency and accuracy of molecular structure determination, with particular focus on metabolite structure elucidation. The findings of this research also provide valuable insights for developing effective workflows for predicting the structures of unknown compounds with high precision.

Pitfalls in the Optimization of Conformer Populations to Maximize the Similarity between Predicted and Experimental Chiroptical Spectra

The conformational populations of pantolactone, epichlorohydrin, and N-acetyl-tryptophan methyl ester were investigated by using similarity analysis between their calculated and experimental chiroptical spectra. By performing the analysis on pantolactone using two different chiroptical methods, namely, vibrational circular dichroism and Raman optical activity, it was found that the optimal sets of conformers do not match between the two methods, indicating that the conformational populations obtained by optimizing the similarity between calculated and experimental spectra are unlikely to be more accurate than energy-based Boltzmann populations. Also, it was found for pantolactone, epichlorohydrin, and N-acetyl-tryptophan methyl ester that the similarity between calculated and experimental spectra would often not vary significantly if each of the populated conformers was discarded, one at a time. This observation indicates that more than one set of conformers can provide acceptable similarity between the predicted and experimental spectra. Therefore, the correct set of conformers cannot be accurately determined by similarity analysis.

Influence of microsolvation on vibrational circular dichroism spectra in dimethyl sulfoxide solvent: A Bottom-Up approach using Quantum cluster growth

Chiroptical spectroscopic measurements serve as routine methods to assign the absolute configuration of chiral compounds and interpret their conformational behavior in solution. One common challenge is the use of strongly hydrogen-bonding solvents, which can significantly bias the conformational ensemble and affect the vibrational circular dichroism (VCD) active bands in solution. One such solvent is dimethyl sulfoxide (DMSO)-an excellent solvent for stubborn compounds-that must be explicitly considered in VCD analysis. Explicit consideration of solvent remains a critical challenge in chiroptical spectroscopy due to the need to explore solute-solvent conformational space and the computational expense in modeling these clusters. Interested in the recent development of the Quantum Cluster Growth (QCG) program by the Grimme lab, we set out to model and interpret previously reported VCD spectra for several molecules using their efficient program. Our purposes are two-fold: (1) to investigate the applicability of the QCG program to the problem of reproducing VCD spectra in DMSO solvent and (2) to identify limitations in using this approach. We find that we can conveniently model and analyze the VCD spectra of investigated molecules in DMSO. However, the final set of conformers used for VCD calculations are functional dependent and different sets of conformers can provide satisfactory quantitative agreement between experimental and predicted VCD spectra. We hope that this study provides guidance for future chiroptical studies in the challenging DMSO solvent.

Tracking SF5 I in the Iodopentafluorosulfanylation of Alkynes

In the vibrant field of SF5 chemistry, SF5 X reagents (X=F, Cl, Br) are at the heart of current investigations in radical pentafluorosulfanylation reactions. SF5 I is the missing link whose existence has not been reported despite its potential as SF5 donor. This study reports the formal addition of the hitherto unknown SF5 I reagent to alkynes by means of a combination of SF5 Cl/KI/18-crown-6 ether. The exclusive regio- and stereoselective synthesis of unprecedented (E)-1-iodo-2-(pentafluoro-λ6 -sulfanyl) alkenes was achieved. A consensus was reached through computational and mechanistic studies for the realistic formation of SF5 - anion but not SF5 I in solution and the rational involvement of SF5 ⋅ and iodine radicals in the iodo pentafluorosulfanylation reaction.

Improved Configurational Sampling Protocol for Large Atmospheric Molecular Clusters

The nucleation process leading to the formation of new atmospheric particles plays a crucial role in aerosol research. Quantum chemical (QC) calculations can be used to model the early stages of aerosol formation, where atmospheric vapor molecules interact and form stable molecular clusters. However, QC calculations heavily depend on the chosen computational method, and when dealing with large systems, striking a balance between accuracy and computational cost becomes essential. We benchmarked the binding energies and structures and found the B97-3c method to be a good compromise between the accuracy and computational cost for studying large cluster systems. Further, we carefully assessed configurational sampling procedures for targeting large atmospheric molecular clusters containing up to 30 molecules (approximately 2 nm in diameter) and proposed a funneling approach with highly improved accuracy. We find that several parallel ABCluster explorations lead to better guesses for the cluster global energy minimum structures than one long exploration. This methodology allows us to bridge computational studies of molecular clusters, which typically reach only around 1 nm, with experimental studies that often measure particles larger than 2 nm. By employing this workflow, we searched for low-energy configurations of large sulfuric acid-ammonia and sulfuric acid-dimethylamine clusters. We find that the binding free energies of clusters containing dimethylamine are unequivocally more stable than those of the ammonia-containing clusters. Our improved configurational sampling protocol can in the future be applied to study the growth and dynamics of large clusters of arbitrary compositions.

Exploration of the Conformational Scenario for α-, β-, and γ-Cyclodextrins in Dry and Wet Conditions, from Monomers to Crystal Structures: A Quantum-Mechanical Study

Cyclodextrins (CDs) constitute a class of cyclic oligosaccharides that are well recognized and largely applied in the drug delivery field, thanks to their biocompatibility, low cost, and the possibility to be derivatized in order to tune and optimize the complexation/release of the specific drug. The conformational flexibility of these systems is one of their key properties and requires a cost-effective methodology to be studied by combining the accuracy of results with the possibility of exploring a large set of conformations. In the present paper, we have explored the conformational potential energy surface of the monomers and dimers of α-, β-, and γ-cyclodextrins (i.e., 6, 7, and 8 monomeric units, respectively) by means of fast but accurate semiempirical methods, which are then refined by state-of-the-art DFT functionals. Moreover, the crystal structure is considered for a more suitable comparison with the IR spectrum experimentally recorded. Calculations are carried out in the gas phase and in water environments, applying both implicit and explicit treatments. We show that the conformation of the studied molecules changes from the gas phase to the water, even if treated implicitly, thus modifying their complexation capability.

Modelling solute-solvent interactions in VCD spectra analysis with the micro-solvation approach

Vibrational circular dichroism (VCD) spectroscopy has become an important part of the (stereo-)chemists' toolbox as a reliable method for the determination of absolute configurations. Being the chiroptical version of infrared spectroscopy, it has also been recognized as being very sensitive to conformational changes and intermolecular interactions. This sensitivity originates from the fact that the VCD spectra of individual conformers are often more different than their IR spectra, so that changes in conformational distributions or band positions and intensities become more pronounced. What is an advantage for studies focussing on intermolecular interactions can, however, quickly turn into a major obstacle during AC determinations: solute-solvent interactions can have a strong influence on spectral signatures and they must be accurately treated when simulating VCD and IR spectra. In this perspective, we showcase selected examples which exhibit particularly pronounced solvent effects. It is demonstrated that it is typically sufficient to model solute-solvent interactions by placing single solvent molecules near hydrogen bonding sites of the solute and subsequently use the optimized structures for spectra simulations. This micro-solvation approach works reasonably well for medium-sized, not too conformationally flexible molecules. We thus also discuss its limitations and outline the next steps that method development needs to take in order to further improve the workflows for VCD spectra predictions.

Infrared and vibrational circular dichroism spectra of methyl β-D-glucopyranose in water: The application of the quantum cluster growth and clusters-in-a-liquid solvation models

The infrared (IR) and vibrational circular dichroism (VCD) spectra of methyl β-D-glucopyranose in water were measured. Both implicit and explicit solvation models were utilized to explain the observed spectra. The vast body of existing experimental and theoretical data suggested that about eight explicit water molecules are needed to account for the solvent effects, supported by the current Quantum Cluster Growth (QCG) analysis. Extensive manual and systematic conformational searches of the molecular target and its water clusters were carried out by using a recently developed conformational searching tool, conformer-rotamer ensemble sampling tool (CREST), and the microsolvation model in the associated QCG code. The Boltzmann averaged IR and VCD spectra of the methyl β-D-glucopyranose-(water)n (n = 8) conformers in the PCM of water provide better agreement with the experimental ones than those with n = 0, 1, and 2. The explicit solvation with eight water molecules was shown to greatly modify the conformational preference of methyl β-D-glucopyranose from its monomeric form. Further analyses show that the result is consistent with the existence of long-lived methyl β-D-glucopyranose monohydrates with the additional explicit water effects being accounted for with the quantum mechanical treatment of the other seven close-by water molecules in the PCM of water.

Computational analysis of the vibrational spectra and structure of aqueous cytosine

The recently developed efficient protocol for the explicit quantum mechanical modeling of the structure and IR spectra of liquids and solutions [Katsyuba et al., J. Phys. Chem. B, 2020, 124, 6664-6670] is used to describe aqueous solutions of cytosine. The same cluster model of a solute surrounded by the first solvation shell of solvent molecules was shown to be sufficient to reproduce experimental vibrational frequencies and relative IR and Raman intensities. An equally good quality of Raman spectra was provided by B3LYP-D3/def2-TZVP and B3LYP-D3/aug-cc-pVDZ simulations. Computations using the PBE functional were sufficient for modeling of the IR spectra but failed in the simulations of Raman scattering. It is shown that strong changes of frequencies and relative intensities of Raman and IR bands of cytosine, caused by its hydration, cannot be completely assigned to the influence of hydrogen bonds (HBs) with 7 or 8 closest water molecules. They are rather ascribed to the combined effect of solute-solute and solute-solvent HBs with the participation of at least 30 water molecules separating cytosine from the bulk solvent. This suggests that the vibrational modes and derivatives of the polarizability and dipole moment of the solute are mainly locally influenced by its first hydration shell, while the influence of bulk water is rather modest.

PyConSolv: A Python Package for Conformer Generation of (Metal-Containing) Systems in Explicit Solvent

We introduce PyConSolv, a freely available Python package that automates the generation of conformers of metal- and nonmetal-containing complexes in explicit solvent, through classical molecular dynamics simulations. Using a streamlined workflow and interfacing with widely used computational chemistry software, PyConSolv is an all-in-one tool for the generation of conformers in any solvent. Input requirements are minimal; only the geometry of the structure and the desired solvent in xyz (XMOL) format are needed. The package can also account for charged systems, by including arbitrary counterions in the simulation. A bonded model parametrization is performed automatically, utilizing AmberTools, ORCA, and Multiwfn software packages. PyConSolv provides a selection of preparametrized solvents and counterions for use in classical molecular dynamics simulations. We show the applicability of our package on a number of (transition-metal-containing) systems. The software is provided open source and free of charge.

N-Oxides as Control Element for the Direction of a Sigmatropic Rearrangement: Application as a Switch for Fluorescence

An exceptional level of control over the direction of the (2,3)-sigmatropic rearrangement between N-oxides and alkoxylamine is achieved by simply changing the solvent in which they are dissolved. Protic solvents like water, methanol and hexafluoroisopropanol favour the N-oxide form, while other solvents like acetone, acetonitrile and benzene favour the alkoxylamine. The reaction temperature and nature of the substituents on the alkene affect the rate of rearrangement. A N-oxide fragment was attached to two fluorescent molecules and acted as an on/off switch for their fluorescence. The conversion of alkoxylamines into the corresponding N-oxides has not previously been described and is here termed the 'Reverse Meisenheimer Rearrangement'.

DFT-based analysis of siderophore-metal ion interaction for efficient heavy metal remediation

Siderophores have great application potential in metal pollutant remediation because of their effective cost and friendly impact on the environment. However, the practical use of siderophores in the remediation of specific metals is rather limited because of the weak nonspecific interactions between the siderophores and different metals. Thus, screening for a siderophore with optimal interaction with a specific metal would be necessary. In this study, the interaction between metal ions and moieties that donate the oxygen ligands for the coordination of four types of siderophore (hydroxamates, catecholates, phenolates, and carboxylates) was modeled and analyzed. As revealed by DFT-based analysis, the four types of siderophore generally exhibited selection preference for different metal ions in the order Ga3+  > Al3+  > Fe3+  > Cr3+  > Ni2+  > Cu2+  > Zn2+  > Co2+  > Mn2+  > Hg2+  > Pb2+  > Cd2+, which was determined mainly by the electronegativity of the siderophore functional groups, the electronegativity of the metals, and the ionic radius of the metals, as well as the interaction between the siderophores and the metals. Moreover, the effect of linear or nonlinear (cyclic) structure on the affinity of each siderophore for different metal ions was evaluated. In most situations, metal-bound cyclic siderophores were found to be more stable than their linear counterparts. Thus, proper siderophores for the remediation of metal pollution may be rapidly screened using this model.

Machine Learning for Bridging the Gap between Density Functional Theory and Coupled Cluster Energies

Accurate electronic energies and properties are crucial for successful reaction design and mechanistic investigations. Computing energies and properties of molecular structures has proven extremely useful, and, with increasing computational power, the limits of high-level approaches (such as coupled cluster theory) are expanding to ever larger systems. However, because scaling is highly unfavorable, these methods are still not universally applicable to larger systems. To address the need for fast and accurate electronic energies of larger systems, we created a database of around 8000 small organic monomers (2000 dimers) optimized at the B3LYP-D3(BJ)/cc-pVTZ level of theory. This database also includes single-point energies computed at various levels of theory, including PBE1PBE, ωΒ97Χ, M06-2X, revTPSS, B3LYP, and BP86, for density functional theory as well as DLPNO-CCSD(T) and CCSD(T) for coupled cluster theory, all in conjunction with a cc-pVTZ basis. We used this database to train machine learning models based on graph neural networks using two different graph representations. Our models are able to make energy predictions from B3LYP-D3(BJ)/cc-pVTZ inputs to CCSD(T)/cc-pVTZ outputs with a mean absolute error of 0.78 and to DLPNO-CCSD(T)/cc-pVTZ with an mean absolute error of 0.50 and 0.18 kcal mol^-1 for monomers and dimers, respectively. The model for dimers was further validated on the S22 database, and the monomer model was tested on challenging systems, including those with highly conjugated or functionally complex molecules.

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.

Measurement of Water Saturation in Soybean Oil

In a previous study, it was observed that survivability was low when attempting to cryopreserve sperm cells in a nanoliter-sized droplet protected under soybean oil, in stark contrast to the high survival rates in milliliter-sized droplets. In this study, infrared spectroscopy was used to provide an estimate of the saturation concentration of water in soybean oil. By following the time evolution of the infrared absorption spectrum of water-oil mixtures, the saturation of water in soybean oil was found to reach equilibrium after 1 h. From the absorption spectra of neat water and neat soybean oil and the application of the Beer-Lambert law to an estimation of the absorption of a mixture from its individual components, it was estimated that the saturation concentration of water is 0.010 M. This estimate was supported by molecular modeling using the latest semiempirical methods (in particular, GFN2-xTB). While for most applications the very low solubility has little impact, the implications in those exceptions were discussed.

The entropic penalty for associative reactions and their physical treatment during routine computations

A systematic study of the entropic penalty for associative reactions is presented. It is shown that computed solution-phase Gibbs free energies typically overestimate entropic contributions. This entropic penalty for associative reactions in solution, i.e., if the number of particles decreases along the reaction coordinate (sum of stoichiometric numbers ), originates from the insufficient treatment of entropic effects by implicit solvent models. We propose an additive correction scheme to Gibbs free energies that is suitable for routine applications by non-expert users. This correction is based on Garza's formalism for the solution-phase entropy [A. J. Garza, J. Chem. Theory Comput., 2019, 15, 3204.] that is physically sound and embedded into an efficient black-box type algorithm. To critically evaluate the entropic penalty and its proposed treatment, we compiled an experimental benchmark set of 31 Δ_rG and 22 in 15 different solvents. Using a representative best-practice computational protocol (at wave function theory (WFT) based DLPNO-CCSD(T) and density functional theory (DFT) based revDSD-PBEP86-D4 level with an implicit solvent model), we determined a sizeable entropic penalty ranging from 2-11 kcal mol^-1. Using the correction scheme presented herein, the entropic penalty is corrected to the chemical accuracy of ≤1 kcal mol^-1 (WFT and DFT). The same applies to at the WFT level. Barriers at the DFT level are overestimated by 2 kcal mol^-1 (classic) and underestimated by 2 kcal mol^-1 (corrected). This effect is attributed to the finding that barriers computed at the DFT level are systematically 2-3 kcal mol^-1 lower than barriers obtained with WFT.

Conformational Distributions of Phenyl β-D-Glucopyranoside and Gastrodin in Solution by Vibrational Optical Activity and Theoretical Calculations

The conformational landscapes of two highly flexible monosaccharide derivatives, namely phenyl β-D-glucopyranoside (ph-β-glu) and 4-(hydroxymethyl)phenyl β-D-glucopyranoside, also commonly known as gastrodin, were explored using a combined experimental and theoretical approach. For the infrared, Raman, and the associated vibrational optical activity (VOA), i.e., vibrational circular dichroism and Raman optical activity, experiments of these two compounds in DMSO and in water were carried out. Extensive and systematic conformational searches were performed using a recently developed conformational searching tool called CREST (conformer-rotamer ensemble sampling tool) in the two solvents. Fourteen and twenty-four low-energy conformers were identified at the DFT level for ph-β-glu and gastrodin, respectively. The spectral simulations of individual conformers were done at the B3LYP-D3BJ/def2-TZVPD level with the polarizable continuum model of the solvents. The VOA spectral features exhibit much higher specificity to conformational differences than their parent infrared and Raman. The excellent agreements achieved between the experimental and simulated VOA spectra allow for the extraction of experimental conformational distributions of these two carbohydrates in solution directly. The experimental percentage abundances based on the hydroxymethyl (at the pyranose ring) conformations G+, G-, and T for ph-β-glu were obtained to be 15%, 75%, and 10% in DMSO and 53%, 40%, and 7% in water, respectively, in comparison to the previously reported gas phase values of 68%, 25%, and 7%, highlighting the important role of solvents in conformational preferences. The corresponding experimental distributions for gastrodin are 56%, 22%, and 22% in DMSO and 70%, 21%, and 9% in water.

Molecular Understanding and Practical In Silico Catalyst Design in Computational Organocatalysis and Phase Transfer Catalysis-Challenges and Opportunities

Through the lens of organocatalysis and phase transfer catalysis, we will examine the key components to calculate or predict catalysis-performance metrics, such as turnover frequency and measurement of stereoselectivity, via computational chemistry. The state-of-the-art tools available to calculate potential energy and, consequently, free energy, together with their caveats, will be discussed via examples from the literature. Through various examples from organocatalysis and phase transfer catalysis, we will highlight the challenges related to the mechanism, transition state theory, and solvation involved in translating calculated barriers to the turnover frequency or a metric of stereoselectivity. Examples in the literature that validated their theoretical models will be showcased. Lastly, the relevance and opportunity afforded by machine learning will be discussed.

Supramolecular Optimization of Sensory Function of a Hemicurcuminoid through Its Incorporation into Phospholipid and Polymeric Polydiacetylenic Vesicles: Experimental and Computational Insight

This work presents the synthesis of a new representative of hemicurcuminoids with a nonyloxy substituent (HCur) as a fluorescent amphiphilic structural element of vesicular aggregates based on phosphatidylcholine (PC), phosphatidylserine (PS), and 10,12-pentacosadiynoic acid (PCDA). Both X-ray diffraction analysis of the single crystal and ¹H NMR spectra of HCur in organic solvents indicate the predominance of the enol-tautomer of HCur. DFT calculations show the predominance of the enol tautomer HCur in supramolecular assemblies with PC, PS, and PCDA molecules. The results of the molecular modeling show that HCur molecules are surrounded by PC and PS with a rather weak exposure to water molecules, while an exposure of HCur molecules to water is enhanced under its supramolecular assembly with PCDA molecules. This is in good agreement with the higher loading of HCur into PC(PS) vesicles compared to PCDA vesicles converted into polydiacetylene (PDA) ones by photopolymerization. HCur molecules incorporated into HCur-PDA vesicles exhibit greater planarity distortion and hydration effect in comparison with HCur-PC(PS) ones. HCur-PDA is presented as a dual fluorescence-chromatic nanosensor responsive to a change in pH within 7.5-9.5, heavy metal ions and polylysine, and the concentration-dependent fluorescent response is more sensitive than the chromatic one. Thus, the fluorescent response of HCur-PDA allows for the distinguishing between Cd²⁺ and Pb²⁺ ions in the concentration range 0-0.01 mM, while the chromatic response allows for the selective sensing of Pb²⁺ over Cd²⁺ ions at their concentrations above 0.03 mM.

Automated and Efficient Generation of General Molecular Aggregate Structures

Modeling intermolecular interactions of complex non-covalent structures is important in many areas of chemistry. To facilitate the generation of reasonable dimer, oligomer, and general aggregate geometries, we introduce an automated computational interaction site screening (aISS) workflow. This easy-to-use tool combines a genetic algorithm employing the intermolecular force-field xTB-IFF for initial search steps with the general force-field GFN-FF and the semi-empirical GFN2-xTB method for geometry optimizations. Compared with the alternative CREST program, aISS yields similar results but with computer time savings of 1-3 orders of magnitude. This allows for the treatment of systems with thousands of atoms composed of elements up to radon, e.g., metal-organic complexes, or even polyhedra and zeolite cut-outs which were not accessible before. Moreover, aISS can identify reactive sites and provides options like site-directed (user-guided) screening.

Physical and numerical aspects of sodium ion solvation free energies via the cluster-continuum model

Sodium cation solvation Gibbs free energies (ΔG_solv(Na⁺)) have been obtained in water, dimethylformamide, dimethyl sulfoxide, ethanol, acetone, acetonitrile, and methanol through the "monomer cycle" cluster-continuum approach where a solvent reference state is described by infinitely separated molecules. The following steps are vital for obtaining reliable ΔG_solv(Na⁺) values: (a) a meticulous conformational search involving dispersion corrected density functional theory (DFT-D) and the continuum solvation model (CSM); (b) gas-phase DFT-D geometry optimization followed by single-point (SP) domain-based local pair natural orbital coupled clusters including single, double, and partly triple excitation (DLPNO-CCSD(T)) calculations in conjunction with the complete basis set extrapolation; (c) advanced statistical thermodynamic treatment of the low harmonic frequencies (<100 cm^-1) to obtain the robust gas-phase Gibbs free energy correction; (d) gas-phase and dielectric continuum SP with non-electrostatic contributions included in the CSM; (e) an evaluation of the relative thermodynamic stability of the Na⁺(S)_n clusters to identify the number of explicit solvent molecules n to be considered. Our refined computational protocol is promising with a Pearson correlation coefficient between the predicted and experimental data, ρ, of 0.82, and the mean signed and mean unsigned errors of 0.3 and 1.4 kcal mol^-1, respectively.

Quantum chemical calculation of the vapor pressure of volatile and semi volatile organic compounds

The vapor pressure is a specific and temperature-dependent parameter that describes the volatility of a substance and thus its driving force for evaporation or sublimation into the gas phase. Depending on the magnitude of the vapor pressure, there are different methods for experimental determination. However, these are usually associated with a corresponding amount of effort and become less accurate as the vapor pressure decreases. For purposes of vapor pressure prediction, algorithms were developed that are usually based on quantitative structure-activity relationships (QSAR). The quantum mechanical (QM) approach followed here applies an alternative, much less empirical strategy, where the change in Gibbs free energy for the transition from the condensed to the gas phase is obtained from conformer ensembles computed for each phase separately. The results of this automatic, so-called CRENSO workflow are compared with experimentally determined vapor pressures for a large set of environmentally relevant compounds. In addition, comparisons are made with the single structure-based COSMO-RS QM approach, linear-free-energy relationships (LFER) as well as results from the SPARC program. We show that our CRENSO workflow is superior to conventional prediction models and provides reliable vapor pressures for liquids and sub-cooled liquids over a wide pressure range.

Cellulose dissolution and gelation in NaOH(aq) under controlled CO2 atmosphere: supramolecular structure and flow properties

We investigate the interplay between cellulose crystallization and aggregation with interfibrillar interactions, shear forces, and the local changes in the medium's acidity. The latter is affected by the CO2 chemisorbed from the surrounding atmosphere, which, combined with shear forces, explain cellulose gelation. Herein, rheology, nuclear magnetic resonance (NMR), small and wide-angle X-ray scattering (SAXS/WAXS), and focused ion beam scanning electron microscopy (FIB-SEM) are combined to unveil the fundamental factors that limit cellulose gelation and maximize its dissolution in NaOH(aq). The obtained solutions are then proposed for developing green and environmentally friendly cellulose-based materials.

Best-Practice DFT Protocols for Basic Molecular Computational Chemistry

Nowadays, many chemical investigations are supported by routine calculations of molecular structures, reaction energies, barrier heights, and spectroscopic properties. The lion's share of these quantum-chemical calculations applies density functional theory (DFT) evaluated in atomic-orbital basis sets. This work provides best-practice guidance on the numerous methodological and technical aspects of DFT calculations in three parts: Firstly, we set the stage and introduce a step-by-step decision tree to choose a computational protocol that models the experiment as closely as possible. Secondly, we present a recommendation matrix to guide the choice of functional and basis set depending on the task at hand. A particular focus is on achieving an optimal balance between accuracy, robustness, and efficiency through multi-level approaches. Finally, we discuss selected representative examples to illustrate the recommended protocols and the effect of methodological choices.

Conformational energies of microsolvated Na+ clusters with protic and aprotic solvents from GFNn-xTB methods

Performance of contemporary tight-binding semiempirical GFNn-xTB methods for the conformational energies of singly charged sodium clusters Na⁺ (S)_n (n = 4-8) with 3 protic and 8 aprotic solvents is examined against the reference RI-MP2/CBS method. The median Pearson correlation coefficients of ρ = 0.84 (GFN2-xTB) and ρ = 0.82 (GFN1-xTB) do not give the clear preference to any tested approach. GFN1-xTB method demonstrates more stable performance than its GFN2-xTB successor with the average mean absolute errors (MAEs)/mean signed errors (MSEs) of 1.2/0.2 and 2.3/1.6 kcal mol^-1 , respectively. Conformational energies produced by the computationally efficient DFT functional PBE and double-ζ basis set complemented with -D3(BJ) dispersion correction are suitable for the preliminary sampling (median ρ = 0.93), but should be used with a caution for the calculations of the average ensemble properties (MAE/MSE = 1.7/1.1 kcal mol^-1 ). Higher-ranking PBE0-D3(BJ) and ωB97M-V with triple-ζ basis sets yield significantly lower MAEs/MSEs of 0.55/0.20 and 0.51/0.23 kcal mol^-1 , respectively.

Unusually Large Effects of Charge-assisted C-H⋅⋅⋅F Hydrogen Bonds to Anionic Fluorine in Organic Solvents: Computational Study of 19 F NMR Shifts versus Thermochemistry

A comparison of computed ¹⁹ F NMR chemical shifts and experiment provides evidence for large specific solvent effects for fluoride-type anions interacting with the σ*(C-H) orbitals in organic solvents like MeCN or CH₂ Cl₂ . We show this for systems ranging from the fluoride ion and the bifluoride ion [FHF]^- to polyhalogen anions [ClF_x ]^- . Discrepancies between computed and experimental shifts when using continuum solvent models like COSMO or force-field-based descriptions like the 3D-RISM-SCF model show specific orbital interactions that require a quantum-mechanical treatment of the solvent molecules. This is confirmed by orbital analyses of the shielding constants, while less negatively charged fluorine atoms (e. g., in [EF₄ ]^- ) do not require such quantum-mechanical treatments to achieve reasonable accuracy. The larger ¹⁹ F solvent shift of fluoride in MeCN compared to water is due to the larger coordination number in the former. These observations are due to unusually strong charge-assisted C-H⋅⋅⋅F^- hydrogen bonds, which manifest beyond some threshold negative natural charge on fluorine of ca. < -0.6 e. The interactions are accompanied by sizable free energies of solvation, in the order F^- ≫[FHF]^- >[ClF₂ ]^- >[ClF₄ ]^- . COSMO-RS solvation free energies tend to moderately underestimate those from the micro-solvated cluster treatment. Red-shifted and intense vibrational C-H stretching bands, potentially accessible in bulk solution, are further spectroscopic finger prints.

Synthesis and Computationally Assisted Spectroscopic Study of Tautomerism in 3-(Phenyl(2-arylhydrazineylidene)methyl)quinoxalin-2(1H)-ones

The recently developed efficient protocol combining implicit and explicit, accurate quantum mechanical modeling of the condensed state [Katsyuba et al., J. Chem. Phys. 155, 024507 (2021)] is used to describe...

Reliable prediction of association (free) energies of supramolecular complexes with heavy main group elements – the HS13L benchmark set

We introduce a set of 13 supramolecular complexes featuring diverse non-covalent interactions with heavy main group elements (Zn, As, Se, Te, Br, I), high charges (−2 up to +4), and large systems with up to 266 atoms (HS13L).