Computational Estimation of the Aqueous Acidities of Alcohols, Hydrates, and Enols

On the influence of solvent on the stereoselectivity of glycosylation reactions

Methodology development in carbohydrate chemistry entails the stereoselective formation of C-O bonds as a key step in the synthesis of oligo- and polysaccharides. The anomeric selectivity of a glycosylation reaction is affected by a multitude of parameters, such as the nature of the donor and acceptor, activator/promotor system, temperature and solvent. The influence of different solvents on the stereoselective outcome of glycosylation reactions employing thioglucopyranosides as glycosyl donors with a non-participating protecting group at position 2 has been studied. A large change in selectivity as a function of solvent was observed and a correlation between selectivity and the Kamlet-Taft solvent parameter π* was found. Furthermore, molecular modeling using density functional theory methodology was conducted to decipher the role of the solvent and possible reaction pathways were investigated.

Accurate Computation of Aqueous pKas of Biologically Relevant Organic Acids: Overcoming the Challenges Posed by Multiple Conformers, Tautomeric Equilibria, and Disparate Functional Groups with the Fully Black-Box pK-Yay Method

The use of static electronic structure calculations to compute solution-phase pKas offers a great advantage in that a macroscopic bulk property could be computed via microscopic computations involving very few molecules. There are various sources of errors in the quantum chemical calculations though. Overcoming these errors to accurately compute pKas of a plethora of acids is an active area of research in physical chemistry pursued by both computational as well as experimental chemists. We recently developed the pK-Yay method in our attempt to accurately compute aqueous pKas of strong and weak acids. The method is fully black-box, computationally inexpensive, and is very easy for even a nonexpert to use. However, the method was thus far tested on very few molecules (only 16 in all). Herein, in order to assess the future applicability of pK-Yay, we study the effect of multiple conformers, the presence of tautomers under equilibrium, and the impact of a wide variety of functional groups (derivatives of acetic acid with substituents at various positions, dicarboxylic acids, aromatic carboxylic acids, amines and amides, phenols and thiols, and fluorine bearing organic acids). Starting with more than 1000 conformers and tautomers, this study establishes that overall errors of ∼ 1.0 pKa units are routinely obtained for a majority of the molecules. Larger errors are noted in cases where multiple charges, intramolecular hydrogen bonding, and several ionizable functional groups are simultaneously present. An important conclusion to emerge from this work is that, the computed pKas are insensitive (difference <0.5) to whether we consider multiple conformers/tautomers or only choose the most stable conformer/tautomer. Further, pK-Yay captures the stereoelectronic effects arising due to differing axial vs equatorial pattern, and is useful to predict the dominant acid-base equilibrium in a system featuring several equilibria. Overall, pK-Yay may be employed in several chemical applications featuring organic molecules and biomonomers.

Reliable and accurate prediction of basic pK[Formula: see text] values in nitrogen compounds: the pK[Formula: see text] shift in supramolecular systems as a case study

This article presents a quantitative structure-activity relationship (QSAR) approach for predicting the acid dissociation constant (pK[Formula: see text]) of nitrogenous compounds, including those within supramolecular complexes based on cucurbiturils. The model combines low-cost quantum mechanical calculations with QSAR methodology and linear regressions to achieve accurate predictions for a broad range of nitrogen-containing compounds. The model was developed using a diverse dataset of 130 nitrogenous compounds and exhibits excellent predictive performance, with a high coefficient of determination (R[Formula: see text]) of 0.9905, low standard error (s) of 0.3066, and high Fisher statistic (F) of 2142. The model outperforms existing methods, such as Chemaxon software and previous studies, in terms of accuracy and its ability to handle heterogeneous datasets. External validation on pharmaceutical ingredients, dyes, and supramolecular complexes based on cucurbiturils confirms the reliability of the model. To enhance usability, a script-like tool has been developed, providing a streamlined process for users to access the model. This study represents a significant advancement in pK[Formula: see text] prediction, offering valuable insights for drug design and supramolecular system optimization.

pKa prediction of per- and polyfluoroalkyl acids in water using in silico gas phase stretching vibrational frequencies and infrared intensities

To successfully understand and model the environmental fate of per- and polyfluoroalkyl substances (PFAS), it is necessary to know key physicochemical properties (PChPs) such as pKa; however, measured PChPs of PFAS are scarce and of uncertain reliability. In this study, quantitative structure-activity relationships (QSARs) were developed by correlating calculated (M062-X/aug-cc-pVDZ) vibrational frequencies (VF) and corresponding infrared intensities (IRInt) to the pKa of carboxylic acids, sulfonic acids, phosphonic acids, sulfonamides, betaines, and alcohols. Antisymmetric stretching VF of the anionic species were used for all subclasses except for alcohols where the OH stretching VF performed better. The individual QSARs predicted the pKa for each subclass mostly within 0.5 pKa units from the experimental values. The inclusion of IRInt as a pKa predictor for carboxylic acids improved the results by decreasing the root-mean-square error from 0.35 to 0.25 (n > 100). Application of the developed QSARs to estimate the pKa of PFAS within each subclass revealed that the length of the perfluoroalkyl chain has minimal effect on the pKa, consistent with other models but in stark contrast with the limited experimental data available.

An Accurate Approach for Computational pKa Determination of Phenolic Compounds

Computational chemistry is a valuable tool, as it allows for in silico prediction of key parameters of novel compounds, such as pKa. In the framework of computational pKa determination, the literature offers several approaches based on different level of theories, functionals and continuum solvation models. However, correction factors are often used to provide reliable models that adequately predict pKa. In this work, an accurate protocol based on a direct approach is proposed for computing phenols pKa. Importantly, this methodology does not require the use of correction factors or mathematical fitting, making it highly practical, easy to use and fast. Above all, DFT calculations performed in the presence two explicit water molecules using CAM-B3LYP functional with 6-311G+dp basis set and a solvation model based on density (SMD) led to accurate pKa values. In particular, calculations performed on a series of 13 differently substituted phenols provided reliable results, with a mean absolute error of 0.3. Furthermore, the model achieves accurate results with -CN and -NO₂ substituents, which are usually excluded from computational pKa studies, enabling easy and reliable pKa determination in a wide range of phenols.

Hybrid hydrogels derived from renewable resources as a smart stimuli responsive soft material for drug delivery applications

The design and synthesis of amphiphilic molecules play a crucial role in fabricating smart functional materials via self-assembly. Especially, biologically significant natural molecules and their structural analogues have inspired chemists and made a major contribution to the development of advanced smart materials. In this report, a series of amphiphilic N-acyl amides were synthesized from natural precursors using a simple synthetic protocol. Interestingly, the self-assembly of amphiphiles 6a and 7a furnished a hydrogel and oleogel in vegetable oils. Morphological analysis of gels revealed the existence of a 3-dimensional fibrous network. Thermoresponsive and thixotropic behavior of these gels were evaluated using rheological analysis. A composite gel prepared by the encapsulation of curcumin in the hydrogel formed from 7a displayed a gel–sol transition in response to pH and could act as a dual channel responsive drug carrier.

The design and synthesis of amphiphilic molecules play a crucial role in fabricating smart functional materials via self-assembly.