Search

There is conflicting evidence in the literature concerning the benefits of charge embedding on the convergence of many-body expansions (MBEs). Using a systematic series of water and ion–water clusters of varying size, this study indicates that the effects of charge embedding can be masked by basis set superposition error (BSSE). When BSSE is removed, this study demonstrates that charge embedding can significantly accelerate MBE convergence, where the electrostatically embedded two-body method, EE-MBE(2), can often yield accuracy close to the four-body method, MBE(4). Contrary to previous studies on smaller systems, this work shows that the performance of EE-MBE is highly sensitive to the charge model, with the best performance obtained when the natural population analysis (NPA) charge model is used and generated at the same level of theory used in the subsystem and supersystem calculations. It was demonstrated that the “3c” composite method, PBEh-3c, yields NPA atomic charges that are in excellent agreement with those obtained from supersystem density functional theory calculations. The linear-scaling X-Polarization method provides a more general approach to estimating these supersystem QM atomic charges, but its performance depends on how the fragments are defined.

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.

Per- and polyfluoroalkyl substances (PFAS) are known for their high environmental persistence and potential toxicity. The presence of PFAS has been reported in many dairy products. However, the mechanisms underlying the accumulation of PFAS in these products remain unclear. Here, we used native mass spectrometry and molecular dynamics simulations to probe the interactions between 19 PFAS of environmental concern and two isoforms of the major bovine whey protein β-lactoglobulin (β-LG). We observed that six of these PFAS bound to both protein isoforms with low- to mid-micromolar dissociation constants. Based on quantitative, competitive binding experiments with endogenous ligands, PFAS can bind orthosterically and preferentially to β-LG’s hydrophobic ligand-binding calyx. β-Cyclodextrin can also suppress binding of PFAS to β-LG owing to the ability of β-cyclodextrin to directly sequester PFAS from solution. This research sheds light on PFAS–β-LG binding, suggesting that such interactions could impact lipid-fatty acid transport in bovine mammary glands at high PFAS concentrations. Furthermore, our results highlight the potential use of β-cyclodextrin in mitigating PFAS binding, providing insights toward the development of strategies to reduce PFAS accumulation in dairy products and other biological systems.

The impact of the electrolyte ion size on electrocatalytic reactions that occur within nanoconfined volumes is currently unknown. Herein, the effect of the size of solvated alkali metal ions on the oxygen reduction reaction (ORR) in acidic electrolytes was explored by using nanoparticles that contain isolated Pt nanochannels of 1–2 nm in diameter. The exterior surface of the nanoparticles was passivated to ensure that the ORR occurred only in the nanoconfined volume defined by the nanochannels. A number of alkali metal ions, with different hydrated sizes, were added into the acidic electrolyte, and different electrolyte ionic strengths were used to establish different levels of nanoconfinement. The results show that the ORR activity at comparatively positive applied potentials is not affected by the presence and nature of the alkali metal ions in the electrolyte. At less positive potentials, however, the activity is influenced by the presence of alkali metal ions in the electrolyte, and this is dependent on both the identity of the alkali metal ions and the electrolyte ionic strength. The differences in activities at less positive potentials are attributed to differences in the alkali metal ions’ accessibility to the nanoconfined space with Li+being accessible and decreasing the electrocatalytic activity relative to inaccessible K+ions that cannot enter the nanoconfined channels. This was corroborated by molecular dynamics modeling suggesting that the energy penalty for the alkali metal ions to enter the nanochannels is different for the different alkali metal ions and is affected by the surface charge of the nanochannel walls.

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

Calculation of molecular geometries and harmonic vibrational frequencies are pre-requisites for thermochemistry calculations. Contrary to conventional wisdom, this paper demonstrates that quantum chemical predictions of the thermochemistry of many gas and solution phase chemical reactions appear to be very insensitive to the choice of basis sets. For a large test set of 80 diverse organic and transition-metal-containing reactions, variations in reaction free energy based on geometries and frequencies calculated using a variety of double and triple-zeta basis sets from the Pople, Jensen, Ahlrichs, and Dunning families are typically less than 4 kJ mol–1, especially when the quasiharmonic oscillator correction is applied to mitigate the effects of low-frequency modes. Our analysis indicates that for many organic molecules and their transition states, high-level revDSD-PBEP86-D4 and DLPNO-CCSD(T)/(aug-)cc-pVTZ single-point energies usually vary by less than 2 kJ mol–1on density functional theory geometries optimized using basis sets ranging from 6-31+G(d) to aug-pcseg-2 and aug-cc-pVTZ. In cases where these single-point energies vary significantly, indicating sensitivity of molecular geometries to the choice of basis set, there is often substantial cancellation of errors when the reaction energy or barrier is calculated. The study concludes that the choice of basis set for molecular geometry and frequencies, particularly those considered in this study, is not critical for the accuracy of thermochemistry calculations in the gas or solution phase.

This study examined two pKacalculation approaches (direct and proton exchange schemes) that employ high-level quantum chemical methods and implicit solvent models to predict aqueous Brønsted acidities of a large set of sulfonamides. For gas-phase deprotonation energies, the DSD-PBEP86-D3(BJ) double-hybrid functional provided the best agreement with the LNO-CCSD(T)/CBS benchmark with a mean absolute deviation less than 2 kJ mol–1when the aug-cc-pVTZ or larger basis sets are used. For a large test set of 54 primary and secondary sulfonamides, the use of the DSD-PBEP86-D3(BJ)/aug-cc-pVTZ level of theory in conjunction with SM12 solvation free energies predict their pKavalues with a mean accuracy of 0.9 units. In comparison, the SMD and ADF-COSMO-RS models have slightly higher mean errors of 1.4 and 1.1 pKaunits provided that the proton exchange scheme was employed to cancel the systematic errors in these models. The performance of these protocols was less ideal when applied to sulfonic acids, sulfamates, and N-substituted sulfonamides, indicating that the degree of error cancellation is sensitive to the chemical environment around the −NH2head group. The validated protocols were then used to estimate the pKavalues of arylsulfonamide carbonic anhydrase inhibitors, which are used to correct their experimentally measured binding free energies to account for deprotonation of the sulfonamide group upon binding to the enzyme. These corrected values did not have a significant impact on the correlation with MMGBSA binding free energies obtained from classical MD simulations where the ligand is usually considered in the deprotonated form.

This paper introduces an economical approach for improving the accuracy and convergence of quantum mechanics/molecular mechanics (QM/MM) models. The approach is tested on a series of neutral and charged amino acids embedded in a 160-water cluster, where their intramolecular proton transfer energies (neutral amino acid → zwitterionic amino acid) were previously obtained at the ωB97X-D/6-31G(d) level of theory. When the charges on the MM atoms were replaced with those obtained at the same QM level of theory used to treat the QM atoms, this significantly improved the accuracy and convergence of the QM/MM models. In particular, the QM/MM model converged to within 1.4 kcal mol−1of directly calculated DFT energies for smaller (by as many as 20 waters) QM regions. The use of atomic charges obtained from the natural population analysis yielded the most significant improvement, while other charge schemes such as Mulliken, electrostatic potential, or CM5 led to poorer outcomes. It is further demonstrated that the QM atomic charges can be accurately estimated in a highly efficient manner using an iterative fragmentation approach based on the moving-domain QM/MM method. Similar observations were made when the approach was used to predict the barrier of an SN2 reaction. Thus, the use of QM-quality atomic charges on MM atoms represents a simple and easy-to-implement strategy for improving the accuracy of QM/MM models.

Preexisting serum albumin–polymer bioconjugates have been formed either through covalent conjugation or supramolecular interactions. However, the viability of producing a bioconjugate where both covalent conjugation and supramolecular interactions have been adopted is yet to be explored. In this work, the noncovalent interaction of two polymers bearing fatty acid-based end-functionalities were compared and the superior binder was carried forward for testing with serum albumin that possessed a polymer conjugated to its Cys34 residue. The studies demonstrated that an albumin–polymer bioconjugate equipped with polymers via both covalent and supramolecular interactions can be successfully achieved.

This paper systematically examines the performance of contemporary wavefunction and density functional theory methods to identify robust and cost-efficient methods for predicting gas-phase anion binding energies. This includes the local coupled cluster LNO-CCSD(T) and DLPNO-CCSD(T), as well as double-hybrid DSD-PBEP86-D3(BJ) and various hybrid functionals M06-2X, B3LYP-D3(BJ), ωB97M-V, and ωB97X-V. The focus is on dual-hydrogen-bonding anion receptors that are commonly found in supramolecular chemistry and organocatalysis, namely, (thio)ureas, deltamides, (thio)squaramides, and croconamides as well as the yet-to-be-explored rhodizonamides. Of the methods examined, M06-2X emerged as the overall best performing method as the other functionals including DSD-PBEP86-D3(BJ) and the local coupled cluster DLPNO-CCSD(T) method displayed systematic errors that increase with the degree of carbonylation of the receptors. Hybrid ONIOM models that employed semiempirical methods (PM7, GFN1-xTB, and GFN2-xTB) and “threefold”-corrected small-basis set potentials (HF-3c, B97-3c, and PBEh-3c) were explored, and the best models resulted in 50- to 500-fold reduction in CPU time compared to W1-local. These calculations provide important insight into the structure-binding relationships where there is a direct correlation between Brønsted acidity and anion binding affinity, though the strength of the correlation also depends on other factors such as hydrogen-bonding geometry and the geometrical distortion that the receptor needs to undergo to bind the anion.

Despite recent advances in the development of machine learning potentials (MLPs) for biomolecular simulations, there has been limited effort on developing stable and accurate MLPs for enzymatic reactions. Here we report a protocol for performing machine-learning-assisted free energy simulation of solution-phase and enzyme reactions at the ab initio quantum-mechanical/molecular-mechanical (ai-QM/MM) level of accuracy. Within our protocol, the MLP is built to reproduce the ai-QM/MM energy and forces on both QM (reactive) and MM (solvent/enzyme) atoms. As an alternative strategy, a delta machine learning potential (ΔMLP) is trained to reproduce the differences between the ai-QM/MM and semiempirical (se) QM/MM energies and forces. To account for the effect of the condensed-phase environment in both MLP and ΔMLP, the DeePMD representation of a molecular system is extended to incorporate the external electrostatic potential and field on each QM atom. Using the Menshutkin and chorismate mutase reactions as examples, we show that the developed MLP and ΔMLP reproduce the ai-QM/MM energy and forces with errors that on average are less than 1.0 kcal/mol and 1.0 kcal mol–1Å–1, respectively, for representative configurations along the reaction pathway. For both reactions, MLP/ΔMLP-based simulations yielded free energy profiles that differed by less than 1.0 kcal/mol from the reference ai-QM/MM results at only a fraction of the computational cost.

This work presents a systematic assessment of QM/QM′ and QM/MM models with respect to direct QM calculations for the tautomerization (neutral to zwitterion) reactions of amino acids (glycine, alanine, valine, aspartate, and neutral and protonated histidine) solvated in a 160 water cluster. The effect of varying QM region size and choice of embedding potentials, including fixed-charge and polarizable molecular mechanics force fields (TIP3P and EFP) and various semiempirical QM methods (PM7, GFN2-xTB, DFTBA, DFTB3, HF-3c, and PBEh-3c), on the accuracy of the models was examined. A surprising finding was that molecular mechanics force fields outperformed many of the semiempirical methods. Generally, the errors in the QM/QM′ and QM/MM models converge slowly with respect to the QM region size, requiring 50 or more waters to be included in the QM region before the error in the model falls below 1 kcal mol–1of its pure QM result. Different QM region selection schemes were also compared, and it was found that selection based on Natural Population Analysis (NPA) atomic charges significantly reduced the error in the QM/QM′ and QM/MM models particularly if a low-quality embedding potential was used. It is envisaged that these results will be useful for the development of future hybrid QM models.

The DLPNO-CCSD(T) method is designed to study large molecular systems at significantly reduced cost relative to its canonical counterpart. However, the error in this approach is also size-extensive and relies on cancellation of errors for the calculation of relative energies. This work provides a direct comparison of canonical CCSD(T) and TightPNO DLPNO-CCSD(T) calculations of reaction energies and barriers of a broad range of chemical reactions. The dataset includes acidities, anion binding affinities, enolization, Diels–Alder, nucleophilic substitution, and atom transfer reactions and complements existing theoretical datasets in terms of system size as well as new reaction types (e.g., anion binding affinities and chlorine atom transfer reactions). The performance of DLPNO-CCSD(T) was further examined with respect to systematic variation of basis set and system size and amounts of nonbonded interaction present in the system. The errors in the DLPNO-CCSD(T) were found to be relatively insensitive to the choice of basis set for small systems but increase monotonically with system size. Additionally, calculations of barriers appear to be more challenging than reaction energies with errors exceeding 5 kJ mol–1for many Diels–Alder reactions. Further tests on three realistic organic reactions reveal the impact of the DLPNO approximation in calculating absolute and relative barriers that are important for predictions such as stereoselectivity.

Organophosphates (OPs) are used worldwide as pesticides. However, acute and chronic exposure to OPs can cause serious adverse health effects. The mechanism of delayed OP toxicity is thought to involve off-target inhibition of serine proteases, although the precise molecular details remain unclear owing to the lack of an analytical method for global detection of protein targets of OPs. Here, we report the development of a mass spectrometry method to identify OP-adducted proteins from complex mixtures in a nontargeted manner. Human plasma was incubated with the OP dichlorvos that was 50% isotopically labeled and 50% unlabeled. Proteins and protein adducts were extracted, digested, and analyzed by liquid chromatography–tandem mass spectrometry (LC-MS/MS) to detect “twin ions” of peptides that were covalently modified by a chemical reaction with dichlorvos. The LC-MS/MS data were processed by a blended data analytics software (Xenophile) to detect the amino acid residue sites of proteins that were covalently modified by exposure to OPs. We discovered that OPs can transmethylate the N, S, and O side chains of His, Cys, Glu, Asp, and Lys residues. For model systems, such transmethylation reactions were confirmed by LC-MS, nuclear magnetic resonance (NMR), and rationalized using electronic structure calculations. Methylation of the ubiquitous antioxidant glutathione by dichlorvos can decrease the reducing/oxidizing equilibrium of glutathione in liver extracts, which has been implicated in diseases and pathological conditions associated with delayed OP toxicity.

High-level quantum chemical calculations were used to elucidate the gas- and solution-phase conformational equilibria for a series of symmetrically substituted (thio)ureas, (thio)squaramides, and croconamides. Gas-phase calculations predict that the thermodynamic conformer of many of these anion receptors is not the dual-hydrogen-bond-facilitating anti–anti conformer as is commonly assumed. For N,N′-diaryl thiosquaramides and croconamides, the syn–syn conformer is typically the predominant conformer. Solution-phase calculations show that the anti–anti conformer is increasingly stabilized as the polarity of the solvent increases. However, the syn–syn conformer remains the lowest energy conformation for croconamides. These predictions are used to explain the acidity versus chloride binding affinity correlations recently reported for some of these compounds. The chloride binding constants for thioureas and croconamides are significantly lower than expected on the basis of their pKavalues, and this may be due in part to the need for these receptors to reorganize into the anti–anti conformer. Experimental NMR nuclear Overhauser effect (NOE) measurements of an asymmetrically substituted squaramide and its thio analogue are consistent with the syn–syn conformation being predominant at 298 K. The conformational equilibria should therefore be an important consideration for the design and development of future anion receptors and organocatalysts.

Robust quantum chemical methods are employed to predict the pKa’s of several families of dual hydrogen-bonding organocatalysts/anion receptors, including deltamides and croconamides as well as their thio derivatives. The average accuracy of these predictions is ∼1 pKaunit and allows for a comparison of the acidity between classes of receptors and for quantitative studies of substituent effects. These computational insights further explain the relationship between pKaand chloride anion affinity of these receptors that will be important for designing future anion receptors and organocatalysts.

Highly potent heterocyclic drugs are frequently poorly water soluble, leading to limited or abandoned further drug development. Nanoparticle technology offers a powerful delivery approach by enhancing the solubility and bioavailability of hydrophobic therapeutics. However, the common usage of organic solvents causes unwanted toxicity and process complexity, therefore limiting the scale-up of nanomedicine technology for clinical translation. Here, we show that an organic-solvent-free methodology for hydrophobic drug encapsulation can be obtained using polymers based on glucose and tyrosine. An aqueous solution based on a tyrosine-containing glycopolymer is able to dissolve solid dasatinib directly without adding an organic solvent, resulting in the formation of very small nanoparticles of around 10 nm loaded with up to 16 wt % of drug. This polymer is observed to function as both a drug solubilizer and a nanocarrier at the same time, offering a simple route for the delivery of insoluble drugs.

The method of systematic molecular fragmentation by annihilation (SMFA) is modified to apply to the interaction energy between a solute and solvent, where the solute is a pair of reacting molecules. For NH3+ CH3Cl as the solute, it is shown that SMFA can estimate (to chemical accuracy) the average binding energy of the solute in large water clusters containing up to 160 water molecules, at an appropriate level of electronic structure theory. The SMFA calculation can be carried out in a computation time that makes it feasible to estimate the solvation contribution to free energies of activation and reaction by ensemble averaging.

In this work, we examined the performance of contemporary quantum mechanical implicit solvent models (SMD, SM8, SM12, and ADF-COSMO-RS) and empirical fragment-based methods for predicting octanol–water partition coefficients (log Pow). Two test sets were chosen: the first is composed of 34 organic molecules from a recent study by MobleyJ. Chem. Theory Comput, 2016, 12, 4015–4024, and the second set is based on a collection of 55 fluorinated alkanols and carbohydrates from LinclauAngew. Chem., Int. Ed., 2016, 55, 674–678. Our analysis indicates that the errors in the solvation free energies of implicit models are reasonably systematic in both solvents such that there is substantial cancellation of errors in the calculation of transfer free energies. Overall, implicit solvent models performed very well across the two test sets with mean absolute errors (MAEs) of about 0.6 log unit and are superior to explicit solvent simulations (GAFF and GAFF-DC). Interestingly, the best performers were empirical fragment-based methods, including ALOGP and miLOGP with significantly lower MAEs (0.2 to 0.4 log unit). The ALOGP method was further tested against the recent SAMPL6 log Powchallenge consisting of 11 drug-like molecules where it obtained an MAE of 0.32 log unit compared to the best-performing COSMOtherm model (0.31 log unit).

In this work, contemporary quantum mechanical (QM) implicit solvent models (SMD, SM12, and COSMO-RS) and a molecular mechanical (MM) explicit solvent model were used to predict the aqueous free energy barrier of a simple Menschutkin reaction (NH3+ CH3Cl). Surprisingly, the explicit solvent approach performed the worst, while the implicit solvent models yielded reasonably accurate values that are in accord with available experimental data. The origin of the large error in the explicit solvent model was due to the use of a fixed set of Lennard-Jones parameters during the free energy perturbation (FEP) calculations. Further analyses indicate that M06-2X/6-31+G(d,p) yielded solute–solvent interaction energies that are in good agreement with benchmark DLPNO-CCSD(T)/CBS values. When end-state MM to M06-2X/6-31+G(d,p) corrections were added using FEP, it significantly improved the accuracy of the explicit solvent MM result and demonstrated that the accuracy of these models may be systematically improved with end-state corrections based on a validated QM level of theory.

The mechanism associated with the base-promoted conversion of alkoxy-substituted and ring-fused gem-dihalocyclopropanes such as 40into annulated furans has been explored. Treatment of compound 40with potassium tert-butoxide affords a mixture of furans 23/27and 41, an outcome that suggests the intermediacy of the slowly interconverting carbonyl ylides 42and 43that undergo rapid [1,5]-electrocyclizations and subsequent dehydrohalogenation to afford the observed products. This proposal is supported by ab initio MO and DFT calculations that also suggest a vinylcarbene insertion pathway is less likely to be operative.

Understanding the effect of vibronic coupling on electron transfer (ET) rates is a challenge common to a wide range of applications, from electrochemical synthesis and catalysis to biochemical reactions and solar energy conversion. The Marcus–Jortner–Levich (MJL) theory offers a model of ET rates based on a simple analytic expression with a few adjustable parameters. However, the MJL equation in conjunction with density functional theory (DFT) has yet to be established as a predictive first-principles methodology. A framework is presented for calculating transfer rates modulated by molecular vibrations, that circumvents the steep computational cost which has previously necessitated approximations such as condensing the vibrational manifold into a single empirical frequency. Our DFT–MJL approach provides robust and accurate predictions of ET rates spanning over 4 orders of magnitude in the 106–1010s–1range. We evaluate the full MJL equation with a Monte Carlo sampling of the entire active space of thermally accessible vibrational modes, while using no empirical parameters. The contribution to the rate of individual modes is illustrated, providing insight into the interplay between vibrational degrees of freedom and changes in electronic state. The reported findings are valuable for understanding ET rates modulated by multiple vibrational modes, relevant to a broad range of systems within the chemical sciences.

We examined the performance of several popular machine learning methods including multiple linear regression (MLR), support vector regression (SVR) and Gaussian process regression (GPR) for quantitative predictions of estrogen receptor (ER) binding affinity. Particular attention is devoted to compiling an accurate and precise dataset of 1589 experimental binding affinities (logRBA) from the Estrogenic Activity Database to train and validate the models. Issues related to accuracy/precision of experimental data, choice of binding affinity data measured on human ER or across species are addressed. The SVR and GPR models performed the best with root-mean-square-errors below 1 log unit that are comparable to experimental precision. We further examined the use of functional group analysis, nearest-neighbour distance and confidence interval estimates to flag large outliers. This work provides a test set of precise experimental data that may be used in future benchmarking studies of other machine learning models or free energy calculations.

We introduce a simple strategy that combines the G3(MP2) composite method and explicitly correlated coupled cluster CCSD(T)-F12 method to efficiently estimate complete basis set CCSD(T) molecular geometries and harmonic vibrational frequencies at the cost of a double-ζ basis set calculation. Based on a large test set of 61 neutral, ionic, and open-shell molecules, and additionally 31 molecules in the HFREQ2014 data set, we demonstrate that this composite strategy has an average accuracy of 2 cm–1or better relative to complete basis set CCSD(T) values. Using this approach, we estimated 696 CCSD(T)/CBS reaction energies of small to medium-sized systems containing up to 6 heavy atoms and confirmed existing approximations that use small basis set density functional theory methods [e.g., M06-2X/6-31+G(d)] to calculate thermal contributions to reaction enthalpies and Gibbs free energies that are accurate to within 0.2 kcal mol–1on average.

Approximate mathematical treatments are commonly taught in undergraduate chemistry, but the validity ranges of these approximations have rarely been properly defined. We present error contour plots of commonly used quadratic approximations for calculating equilibrium proton concentrations of monoprotic acids. Students and instructors can easily read these plots to estimate the error in their approximation of proton concentration (1%, 5%, 10%, and 25%) at a given initial acid concentration [HA]0and dissociation constant Kavalue. In addition, we introduce a new quadratic expression which will always deliver an error no larger than 25% (or 0.1 pH unit) in ideal solution irrespective of the acid strength and concentration. These results extend readily to their analogue of pOH, Kb, and [A–] for bases. Our novel approach here could significantly reduce many different situations students must master into one that can be computed straightforwardly without caveats or conditions.

A rotationally fluid state of α-pinene at fused silica/vapor interfaces is revealed by computational and experimental vibrational sum frequency generation (SFG) studies. We report the first assignment of the vibrational modes in the notoriously congested C–H stretching region of α-pinene and identify its bridge methylene group on the four-membered ring (“βCH2”) as the origin of its dominant spectral feature. We find that the spectra are perfused with Fermi resonances that need to be accounted for explicitly in the computation of vibrational spectra of strained hydrocarbons such as α-pinene. The preferred orientations of α-pinene are consistent with optimization of van der Waals contacts with the silica surface that results in a bimodal distribution of highly fluxional orientations in which the βCH2group points “towards” or “away from” the surface. Classical molecular dynamics simulations further provide rotational diffusion constants of 49 ± 1 ps and 2580 ± 60 ps, which are attributed to two broad types of adsorption modes on silica. The reported findings are particularly relevant to the exposure of α-pinene to primary oxidants in heterogeneous catalytic pathways that exploit α-pinene as a sustainable feedstock for fine chemicals and polymers.

A generalization of the Moving-Domain Quantum Mechanics/Molecular Mechanics (MoD-QM/MM) hybrid method [Gascon, J. A.; Leung, S. S. F.; Batista, E. R.; Batista, V. S. J. Chem. Theory Comput.2006, 2, 175–186] is introduced to provide a self-consistent computational protocol for structural refinement of extended systems. The method partitions the system into molecular domains that are iteratively optimized as quantum mechanical (QM) layers embedded in their surrounding molecular environment to obtain an ab initio quality description of the geometry and the molecular electrostatic potential of the extended system composed of those constituent fragments. The resulting methodology is benchmarked as applied to model systems that allow for full QM optimization as well as through refinement of the hydrogen bonding geometry in Oxytricha novaguanine quadruplex for which several studies have been reported, including the X-ray structure and NMR data. Calculations of 1H NMR chemical shifts based on the gauge independent atomic orbital (GIAO) method and direct comparisons with experiments show that solvated MoD-QM/MM structures, sampled from explicit solvent molecular dynamics simulations, allow for NMR simulations in much improved agreement with experimental data than models based on the X-ray structure or those optimized using classical molecular mechanics force fields.

In this study, the aqueous pKavalues for 13 neutral, 10 cationic, and 5 anionic carbon acids, including amino acids, peptides, and related species have been calculated using the high level ab initio composite procedure, G3MP2+//BMK, combined with solvation energies that were calculated using the CPCM-(UAKS/UAHF), COSMO-RS, and SM6 continuum models. The pKas were further calculated using three schemes, namely the direct method and the proton exchange method as well as the inclusion of an explicit solvent water molecule. The results of this study indicate that the direct method is unsuitable for computing the pKaof carbon acids, whereas the other two schemes perform significantly better with varying degrees of success, depending on the charge of the carbon acid. Specifically, the combination of the proton exchange scheme and CPCM-UAKS model performed particularly well for neutral species, with mean absolute deviations (MADs) of ∼1 pKaunit. The ionic species were more problematic, though the combination of the proton exchange scheme and the SM6 and CPCM-UAKS models performed reasonably well for the cationic and anionic acids, respectively. The inclusion an explicit water molecule generally improved the calculated values for anionic carbon acids.

Solvents are one of the key variables in the optimization of a synthesis yield or properties of a synthesis product. In this paper, contemporary solvent models are applied to predict the rates of SN2 reactions in a range of aqueous and non-aqueous solvents. High-level CCSD(T)/CBS//M06-2X/6-31+G(d) gas phase energies were combined with solvation free energies from SMD, SM12, and ADF-COSMO-RS continuum solvent models, as well as molecular mechanics (MM) explicit solvent models with different atomic charge schemes to predict the rate constants of three SN2 reactions in eight protic and aprotic solvents. It is revealed that the prediction of rate constants in organic solvents is not necessarily less challenging than in water and popular solvent models struggle to predict their rate constants to within 3 log units of experimental values. Among the continuum solvent models, the ADF-COSMO-RS model performed the best in predicting absolute rate contants while the SM12 model was best at predicting relative rate constants with an average accuracy of about 1.5 and 0.8 log units, respectively. The use of computationally more demanding MM explicit solvent models did not translate to improvements in absolute rate constants but was quite effective at predicting relative rate constants due to systematic error cancellation. Free energy barriers obtained from umbrella sampling with explicit solvent QM/MM simulations led to excellent agreement with experimental values, provided that a validated level of theory is used to treat the QM region.

This article highlights some of the challenges in explaining simple substituent effects on keto–enol equilibria, particularly to an undergraduate audience. Quantum-chemical calculations were performed to identify the role of intramolecular hydrogen bonding, inductive effects due to electron-withdrawing groups, and cross-conjugation on the enolization of β-diketones and β-ketoesters. These insights could be applied by an instructor in order to enrich undergraduate chemistry students’ understanding of this fundamental reaction.

Diaminomethylenemalononitriles (DMMs) and diaminomethyleneindanediones (DMIs) are dual H-bond donors that have previously been used as organocatalysts, but their anion binding ability has not been investigated. We report the synthesis of both alkyl- and aryl-substituted DMMs and DMIs, together with a comparison of their anion binding ability with that of the analogous thioureas. The DMMs display affinity for monovalent anions, with similar anion binding affinities observed to that of the thioureas in acetonitrile, albeit with differing trends for the N,N′-dialkyl versus N,N′-diaryl compounds. In contrast, the DMIs do not bind to monovalent anions under similar conditions as a result of conformational locking through the formation of intramolecular H-bonds. This can be overcome upon addition of sulfate ions, and binding of sulfate is enhanced in a more competitive solvent (DMSO).