Computational Estimation of the Gas-Phase and Aqueous Acidities of Carbon Acids

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.

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.

Computational Estimation of the Acidities of Pyrimidines and Related Compounds

Pyrimidines are key components in the genetic code of living organisms and the pyrimidine scaffold is also found in many bioactive and medicinal compounds. The acidities of these compounds, as represented by their pKas, are of special interest since they determine the species that will prevail under different pH conditions. Here, a quantum chemical quantitative structure-activity relationship (QSAR) approach was employed to estimate these acidities. Density-functional theory calculations at the B3LYP/6-31+G(d,p) level and the SM8 aqueous solvent model were employed, and the energy difference ∆EH2O between the parent compound and its dissociation product was used as a variation parameter. Excellent estimates for both the cation → neutral (pKa1, R2 = 0.965) and neutral → anion (pKa2, R2 = 0.962) dissociations were obtained. A commercial package from Advanced Chemical Design also yielded excellent results for these acidities.

Comparison of two diphenyl polyenes as acid-sensitive additives during the biodegradation of a thermoset polyester polyurethane coating

AIMS

Biochemical hydrolysis and chemical catalysis are involved in the successful biodegradation of polymers. In order to evaluate the potential separation between biochemical and chemical catalysis during the biodegradation process, we report the use of two diphenylpolyenes (DPPs), all trans-1,4-diphenylbutadiene (DPB) and all trans-1,6-diphenylhexatriene (DPH), as potential acid-sensitive indicators in polymers.

METHODS AND RESULTS

1,4-Diphenylbutadiene and DPH (0.1% w/w) were melt-cast successfully with poly(ethylene succinate) hexamethylene (PES-HM) polyurethane (thermoset polyester polyurethane) coatings above 80℃. When these two DPP/PES-HM coatings were exposed to a concentrated supernatant with significant esterase activity resulting from the growth of a recently isolated and identified strain of Tremellomycetes yeast (Naganishia albida 5307AI), the DPB coatings exhibited a measurable and reproducible localized decrease in the blue fluorescence emission in regions below where hydrolytic biodegradation was initiated in contrast with DPH blended coatings. The fluorescence changes observed in the biodegraded DPB coating were similar to exposing them to concentrated acids and not bases.

CONCLUSIONS

Our experiments resulted in (1) a method to blend DPP additives into thermoset coatings, (2) the first report of the biodegradation of polyester polyurethane coating by N. albida, and (3) demonstration that hydrolytic supernatants from this strain generate acidic region within degrading polyester coatings using DPB as the indicator.

SIGNIFICANCE AND IMPACT OF THE STUDY

Our experiments confirm that N. albida is an active polyester degrader and that DPB is a promising acid sensitive polymer coating additive.

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

Alcohols are ubiquitous chemical species, and their acid dissociation constants are critical properties in many applications. It is useful to have a reliable and convenient computational procedure for estimating these acidities. Here we describe a quantitative structure-activity relationship (QSAR) for the pK_as of alcohols in aqueous solution employing density functional theory computations at the B3LYP/6-31+G(d,p) level with the CPCM implicit solvent model for the aqueous solutions. For the pK_as, the energy difference in solution between the parent compound and the anion, ΔE(H₂O), was used as a single descriptor. High quality QSAR equations are obtained both for the gas-phase Gibbs energy changes (ΔG_r⁰s, R² = 0.9764) and the aqueous pK_as (R² = 0.9594). It is shown that the aqueous equation can also be used to estimate the pK_as of fluorinated alcohols, hydrates formed by carbonyl compounds in aqueous solution, and enols that appear as minor components in keto-enol equilibria.

A LSER-based model to predict the solubilizing effect of drugs by inclusion with cucurbit[7]uril

A large number of traditional drugs and the development of new drugs often encounter the problem of poor water solubility. Cucurbit[7]uril, a novel macrocyclic host, has attracted great interest in this field. Investigating the solubilizing effect of drugs by inclusion with cucurbit[7]uril could provide guidance for drug solubilization. In this work, the interactions of drugs with cucurbit[7]uril, drugs with water and the inclusion complexes with water, and the properties of drugs and inclusion complexes, are considered to establish a linear solvation energy relationships (LSER)-based model. This model could be applied to predicting the solubility of drugs with cucurbit[7]uril in water. Density functional theory (DFT) is employed to obtain the properties and interaction parameters. The multi-parameter solubility model obtained by stepwise regression shows good fitting and predicting results. And the surface area of inclusion complexes (A 3), the LUMO energy of inclusion complexes (E 3LUMO), the polarity index of inclusion complexes (I 3), the electronegativity of drugs (χ 1), and the oil-water partition coefficient of drugs (log p 1w) are effective parameters related to the solubilization of drugs with cucurbit[7]uril. Futhermore, the model could be extended to calculate the solubilizing effect of other macrocycles.