pKa Data Research Articles

Widespread Misinterpretation of pKa Terminology for Zwitterionic Compounds and Its Consequences.

The acid dissociation constant (pKa), which quantifies the propensity for a solute to donate a proton to its solvent, is crucial for drug design and synthesis, environmental fate studies, chemical manufacturing, and many other fields. Unfortunately, the terminology used for describing acid-base phenomena is sometimes inconsistent, causing large potential for misinterpretation. In this work, we examine a systematic confusion underlying the definition of "acidic" and "basic" pKa values for zwitterionic compounds. Due to this confusion, some pKa data are misrepresented in data repositories, including the widely used and highly trusted ChEMBL database. Such datasets are frequently used to supply training data for pKa prediction models, and hence, confusion and errors in the data make the model performance worse. Herein, we discuss the intricacies of this issue. We make suggestions for describing acid-base phenomena, training pKa prediction models, and stewarding pKa datasets, given the high potential for confusion and potentially high impact in downstream applications.

Thermodynamics of complex formation of silver(I) with substituted pyridines and cyclic amines in non-aqueous solvents

The understanding of the thermodynamic stability and speciation of metal complexes in solution requires access to their enthalpy and entropy of formation. In this work, we specifically focus our investigation on the complexation process of silver(I) ion in acetonitrile (AN) with substituted mono pyridines and cyclic monoamines. The aim of this study is to provide reliable thermodynamic data to obtain insights on metal complex formation, focusing on ligands donor properties and solvation effects. Carefully designed potentiometric and calorimetric experiments allowed to define the species present at different ligand/metal ratios and to obtain the complex formation constants and enthalpies. In general, the enthalpy terms associated with the complex formation are highly exothermic, while the entropy values are always unfavorable. The formation constants of AgLj species for the ligands investigated in AN are compared with those previously obtained in dimethyl sulfoxide (DMSO) and water. The trends in stability constants and enthalpy values are discussed in relation to the pKa data available in the different solvents. Higher pKa values correspond to greater ligand basicity and result in more stable and more enthalpy stabilized complexes.

Utilizing molecular geometry, pKa, NMR, and IR data to assess the accuracy of quantum mechanics-derived thermodynamic parameters in evaluating antioxidant activity

In the current scientific milieu, a plethora of studies explores the intricacies of unravelling the antioxidant capacities inherent in novel compounds, employing the sophisticated tool of quantum chemistry. However, despite the strides made in this field, it is widely acknowledged that quantum chemical computations are not immune to imperfections, particularly when applied to a diverse array of chemical systems. The challenges extend to the critical task of discerning the reliability of suspected thermodynamic data, a pivotal aspect in the assessment of antioxidant candidates.This report endeavours to address the pressing question of how to establish the trustworthiness of thermodynamic data derived from quantum mechanical computations. Rather than solely relying on quantum mechanical approaches, our proposed methodology advocates for an inclusive strategy that incorporates additional experimental parameters to bolster the overall credibility assessment. With a specific focus on nicotine and Trolox, we aim to transcend the limitations of singular computational methods. By juxtaposing quantum-derived data with supplementary experimental evidence, we aspire to forge a comprehensive framework capable of robustly evaluating antioxidant candidates.

Measurement of the pKa Values of Organic Molecules in Aqueous-Organic Solvent Mixtures by 1H NMR without External Calibrants.

Aqueous-organic solvent mixtures are commonly used for reactions or analyses, where the components of a system are insoluble in pure water. The acid dissociation constant is an important property to measure in these media as it determines the charge state, solubility, and reactivity of a molecule. While NMR spectroscopy is an established tool for the measurement of pKa in water, its use in aqueous-organic solvents is greatly hindered by the requirement for external calibrants on which a working pH scale is set. Such calibrants include buffer solutions, "anchor" molecules with known pKa values, and pH electrodes that have undergone lengthy calibration procedures in the solvent mixture of interest. However, such calibrations are often inconvenient to perform, while literature pKa data covering the required range may not be available at the solvent composition or the temperature of interest. Here, we present a method to determine pKa in aqueous-organic solvents directly by NMR. We first determine pKa of an organic acid such as 2,6-dihydroxybenzoic acid (2,6-DHB) by measuring its 1H chemical shift as a function of concentration along a concentration gradient using chemical shift imaging (CSI). Using 2,6-DHB as a reference, we then determine pKa of less acidic molecules in single CSI experiments via the variation of their 1H chemical shifts along pH gradients. As proof of concept, we determine the pKa values of organic acids and bases up to pKa 10 in 50% (v/v) 1-propanol/water, 50% (v/v) dimethyl sulfoxide/water, and 30% (v/v) acetonitrile/water and obtain good agreement with the literature values.

Antidepressants enter cells, organelles, and membranes.

We begin by summarizing several examples of antidepressants whose therapeutic actions begin when they encounter their targets in the cytoplasm or in the lumen of an organelle. These actions contrast with the prevailing view that most neuropharmacological actions begin when drugs engage their therapeutic targets at extracellular binding sites of plasma membrane targets-ion channels, receptors, and transporters. We review the chemical, pharmacokinetic, and pharmacodynamic principles underlying the movements of drugs into subcellular compartments. We note the relationship between protonation-deprotonation events and membrane permeation of antidepressant drugs. The key properties relate to charge and hydrophobicity/lipid solubility, summarized by the parameters LogP, pKa, and LogDpH7.4. The classical metric, volume of distribution (Vd), is unusually large for some antidepressants and has both supracellular and subcellular components. A table gathers structures, LogP, PKa, LogDpH7.4, and Vd data and/or calculations for most antidepressants and antidepressant candidates. The subcellular components, which can now be measured in some cases, are dominated by membrane binding and by trapping in the lumen of acidic organelles. For common antidepressants, such as selective serotonin reuptake inhibitors (SSRIs) and serotonin/norepinephrine reuptake inhibitors (SNRIs), the target is assumed to be the eponymous reuptake transporter(s), although in fact the compartment of target engagement is unknown. We review special aspects of the pharmacokinetics of ketamine, ketamine metabolites, and other rapidly acting antidepressants (RAADs) including methoxetamine and scopolamine, psychedelics, and neurosteroids. Therefore, the reader can assess properties that markedly affect a drug's ability to enter or cross membranes-and therefore, to interact with target sites that face the cytoplasm, the lumen of organelles, or a membrane. In the current literature, mechanisms involving intracellular targets are termed "location-biased actions" or "inside-out pharmacology". Hopefully, these general terms will eventually acquire additional mechanistic details.

MF-SuP-pKa: Multi-fidelity modeling with subgraph pooling mechanism for pKa prediction.

Acid-base dissociation constant (pKa) is a key physicochemical parameter in chemical science, especially in organic synthesis and drug discovery. Current methodologies for pKa prediction still suffer from limited applicability domain and lack of chemical insight. Here we present MF-SuP-pKa (multi-fidelity modeling with subgraph pooling for pKa prediction), a novel pKa prediction model that utilizes subgraph pooling, multi-fidelity learning and data augmentation. In our model, a knowledge-aware subgraph pooling strategy was designed to capture the local and global environments around the ionization sites for micro-pKa prediction. To overcome the scarcity of accurate pKa data, low-fidelity data (computational pKa) was used to fit the high-fidelity data (experimental pKa) through transfer learning. The final MF-SuP-pKa model was constructed by pre-training on the augmented ChEMBL data set and fine-tuning on the DataWarrior data set. Extensive evaluation on the DataWarrior data set and three benchmark data sets shows that MF-SuP-pKa achieves superior performances to the state-of-the-art pKa prediction models while requires much less high-fidelity training data. Compared with Attentive FP, MF-SuP-pKa achieves 23.83% and 20.12% improvement in terms of mean absolute error (MAE) on the acidic and basic sets, respectively.

Basis for Accurate Protein pKa Prediction with Machine Learning.

pH regulates protein structures and the associated functions in many biological processes via protonation and deprotonation of ionizable side chains where the titration equilibria are determined by pKa's. To accelerate pH-dependent molecular mechanism research in the life sciences or industrial protein and drug designs, fast and accurate pKa prediction is crucial. Here we present a theoretical pKa data set PHMD549, which was successfully applied to four distinct machine learning methods, including DeepKa, which was proposed in our previous work. To reach a valid comparison, EXP67S was selected as the test set. Encouragingly, DeepKa was improved significantly and outperforms other state-of-the-art methods, except for the constant-pH molecular dynamics, which was utilized to create PHMD549. More importantly, DeepKa reproduced experimental pKa orders of acidic dyads in five enzyme catalytic sites. Apart from structural proteins, DeepKa was found applicable to intrinsically disordered peptides. Further, in combination with solvent exposures, it is revealed that DeepKa offers the most accurate prediction under the challenging circumstance that hydrogen bonding or salt bridge interaction is partly compensated by desolvation for a buried side chain. Finally, our benchmark data qualify PHMD549 and EXP67S as the basis for future developments of protein pKa prediction tools driven by artificial intelligence. In addition, DeepKa built on PHMD549 has been proven an efficient protein pKa predictor and thus can be applied immediately to, for example, pKa database construction, protein design, drug discovery, and so on.

A novel method for investigation of the impact of sterilization by gamma radiation on polycaprolactone scaffold

Structural properties of materials irradiated with gamma-rays, such as mechanical and physical properties, may be modified or reduced depending on the displacement damages. Apart from increasing or decreasing that property, damage may be desirable or not. This study investigates the effects of sterilization by gamma radiation on polycaprolactone (PCL) scaffolds. Using a code-based simulation method, MCNPX provides information on primary knock-on atoms, or PKAs, that cause damage. A program has been developed called GAMMATRACK to access PKA information. These PKA data can be used as input for the SRIM code to analyze gamma damage systematically. The rate of damage caused by gamma radiation is calculated on the PCL target. The theoretical calculation method also has been used to confirm the results of the Monte Carlo method (MCNPX + SRIM code). Due to the low-energy PKAs and the thin target possibility of the displacement cascade can be ignored. It is realized that all displacements are due to single vacancies. The total number of hydrogens, carbons, and oxygen PKAs were obtained. It was found that the number of carbons PKA is more than the others, which causes three-dimensional polymer networks to be created. In the experimental analysis, it is necessary to know the appropriate depth of the sample for damage investigation. GAMMATRACK gives the gamma displacement damage graph along the length of the PCL. It shows a uniform distribution of displacement damage. The damage rate for the PCL target is calculated, and the results between the theoretical calculations and the Monte Carlo method (MCNPX + SRIM code) differ by about 17%.

Theoretical Calculations of pKa Values for Substituted Carboxylic Acid

Six different methods of determination have been used for studying ten derivatives of carboxylic compounds. Semi-empirical (AM1 and PM3), Hartree Fock (HF/STO-3G and HF/3-21G), and Density Function Theory (DFT/STO-3G and DFT/6-31G) were employed to calculate many physical theoretical parameters. The calculated data were correlated with experimental values of pKa using different regression(enter, stepwise and simple regression). Depending on the Fisher values, (HF/STO-3G) was shown as the best method for predicted of the pKa data compare to the (PM3) method using enter method. While (HF/3-21G)method has a big value of fisher compared with(PM3) using (stepwise) and (simple) methods. So, Multiple linear regression was performed to obtain the best prediction values using (enter) compare with (stepwise), and the two methods are the best compared with simple regression.

Surface Acidity and As(V) Complexation of Iron Oxyhydroxides: Insights from First-Principles Molecular Dynamics Simulations.

Iron hydroxides are ubiquitous in soils and aquifers and have been adopted as adsorbents for As(V) removal. However, the complexation mechanisms of As(V) have not been well understood due to the lack of information on the reactive sites and acidities of iron hydroxides. In this work, we first calculated the acidity constants (pKas) of surface groups on lepidocrocite (010), (001), and (100) surfaces by using the first-principles molecular dynamics (FPMD)-based vertical energy gap method. Then, the desorption free energies of As(V) on goethite (110) and lepidocrocite (001) surfaces were calculated by using constrained FPMD simulations. The point of zero charges and reactive sites of individual surfaces were obtained based on the calculated pKas. The structures, thermodynamics, and pH dependence for As(V) complexation were derived by integrating the pKas and desorption free energies. The pKa data sets obtained are fundamental parameters that control the charging and adsorption behavior of iron oxyhydroxides and will be very useful in investigating the adsorption processes on these minerals. The pH-dependent complexation mechanisms of As(V) derived in this study would be helpful for the development of effective adsorbent materials and the prediction of the long-term behavior of As(V) in natural environments.

Force-Field-Based Computational Study of the Thermodynamics of a Large Set of Aqueous Alkanolamine Solvents for Post-Combustion CO2 Capture.

The ability to predict the thermodynamic properties of amine species in CO2-loaded aqueous solutions, including their deprotonation (pKa) and carbamate to bicarbonate reversion (pKc) equilibrium constants and their corresponding standard reaction enthalpies, is of critical importance for the design of improved carbon capture solvents. In this study, we used isocoulombic forms of both reactions to determine these quantities for a large set of aqueous alkanolamine solvent systems. Our hybrid approach involves using classical molecular dynamics simulations with the general amber force field (GAFF) and semi-empirical AM1-BCC charges (GAFF/AM1-BCC) in the solution phase, combined with high-level composite quantum chemical ideal-gas calculations. We first determined a new force field (FF) for the hydronium ion (H3O+) by matching to the single experimental pKa data point for the well-known monoethanolamine system at 298.15 K. We then used this FF to predict the pKa values for 76 other amines at 298.15 K and for all 77 amines at elevated temperatures. Additionally, we indirectly relate the H3O+ hydration free energy to that of H+ and provide expressions for intrinsic hydration free energy and enthalpy of the proton. Using the derived H3O+ FF, we predicted the pKa values of a diverse set of alkanolamines with an overall average absolute deviation of less than 0.72 pKa units. Furthermore, the derived H3O+ FF is able to predict the protonation enthalpy of these amines when used with the GAFF. We also predicted the carbamate reversion constants of the primary and secondary amine species in the data set and their corresponding standard heats of reaction, which we compared with the scarcely available experimental data, which are often subject to significant uncertainty. Finally, we also described the influence of electronic and steric effects of different molecular fragments/groups on the stabilities of the carbamates.

Prediction Models on pKa and Base-Catalyzed Hydrolysis Kinetics of Parabens: Experimental and Quantum Chemical Studies.

Parabens for which the molecules contain hydrolytic and ionizable groups, are emerging pollutants due to their ubiquity in the environment. However, lack of pKa and second-order base-catalyzed hydrolysis kinetics (kB) values limits their environmental persistence assessment. Herein, six parabens were selected as reference compounds for which the pKa and kB values were measured experimentally. A semiempirical quantum chemical (QC) method was selected to calculate pKa of the parabens, and density functional theory (DFT) methods were selected to calculate kB for neutral and anionic forms of the parabens, by comparing the QC-calculated and determined values. Combining the QC-calculated and experimental pKa and kB values, quantitative structure-activity relationships with determination coefficients (R2) being 0.947 and 0.842 for the pKa and kB models, respectively, were developed, which were validated and could be employed to efficiently fill the kB and pKa data gaps of parabens within applicability domains. The base-catalyzed hydrolysis half-lives were estimated to range from 6 h to 1.52 × 106 years (pH 7-9, 25 °C), further necessitating the in silico models due to the tedious and onerous experimental determination, and the huge number of hydrolyzable and ionizable chemicals that may be released into the environment.

On the Accuracy of the Direct Method to Calculate pKa from Electronic Structure Calculations.

The direct method (HA(soln) ⇌ A(soln)– + H(soln)+) for calculating pKa of monoprotic acids is as efficient as thermodynamic cycles. A selective adjustment of proton free energy in solution was used with experimental pKa data. The procedure was analyzed at different levels of theory. The solvent was described by the solvation model density (SMD) model, including or not explicit water molecules, and three training sets were tested. The best performance under any condition was obtained by the G4CEP method with a mean absolute error close to 0.5 units of pKa and an uncertainty around ±1 unit of pKa for any training set including or excluding explicit solvent molecules. PM6 and AM1 performed very well with average absolute errors below 0.75 units of pKa but with uncertainties up to ±2 units of pKa, using only the SMD solvent model. Density functional theory (DFT) results were highly dependent on the basis functions and explicit water molecules. The best performance was observed for the local spin density approximation (LSDA) functional in almost all calculations and under certain conditions, as high as those obtained by G4CEP. Basis set complexity and explicit solvent molecules were important factors to control DFT calculations. The training set molecules should consider the diversity of compounds.

Linear free energy relationship models for the retention of partially ionized acid-base compounds in reversed-phase liquid chromatography

The LFER model of Abraham is applied to the retention of the neutral and ionic forms of 94 solutes in a C18 column and 40% v/v acetonitrile/water mobile phase. The results show that polarizability and cavity formation interactions increase retention, whereas dipole and hydrogen bonding interactions favours partition to the mobile phase and thus, they decrease retention. The coefficients of the ionic descriptors measure the effect of the electrostatic interactions and their contribution to partition of the cation or anion between the two mobile and stationary chromatographic phases.A new LFER model for application to the retention of partially dissociated acids and bases is derived averaging the descriptors of the neutral and ionic forms according to their degrees of ionization in the mobile phase. This new LFER model is satisfactorily compared to other literature modified Abraham models for a set of 498 retention data of partially dissociated acids and bases.All tested models require the calculation of the ionization degrees of the compounds at the measuring pH. Calculation of the ionization degrees in the chromatographic mobile phase (i.e. from pH and pKa in the eluent) give good correlations for all tested models. However, estimation of these ionization degrees from pH – pKa data in pure water gives biased estimations of the retention of the partially ionized solutes.

Chromatographic and UV–visible spectrophotometric pKa determination of some purine antimetabolites

In this study, the chromatographic and spectrophotometric behaviors of polar 6-thioguanine (6-TGN) and 6-mercaptopurine (6-MCP) in acetonitrile (ACN)-water binary mixtures were investigated. The effect of pH of the mobile phase on the chromatographic behavior of 6-TGN and 6-MCP structurally related thiopurine analogs and determination of protonation constant/dissociation constant (sspKa) values with reversed-phase liquid chromatography (RPLC) method were determined in ACN-water binary mixtures with ACN percentages of 1, 3, 5, 7 and 10% (v/v). Spectral behavior and pKa value of these two compounds were performed by UV–Visible spectrophotometric methods in ACN-water mixtures containing 3, 5 and 7% (v/v) ACN. Chromatographic and spectrophotometric pKa data were evaluated by Microsoft Excel SOLVER and STAR programs, respectively. Aqueous pKa (wwpKa) values of 6-TGN and 6-MCP were calculated using the linear relationship between the pKa data obtained in ACN-water mixtures and macroscopic parameter values (dielectric constant and mole fraction).

Catalytic Site pKa Values of Aspartic, Cysteine, and Serine Proteases: Constant pH MD Simulations.

Enzymatic function and activity of proteases is closely controlled by the pH value. The protonation states of titratable residues in the active site react to changes in the pH value, according to their pKa, and thereby determine the functionality of the enzyme. Knowledge of the titration behavior of these residues is crucial for the development of drugs targeting the active site residues. However, experimental pKa data are scarce, since the systems’ size and complexity make determination of these pKa values inherently difficult. In this study, we use single pH constant pH MD simulations as a fast and robust tool to estimate the active site pKa values of a set of aspartic, cysteine, and serine proteases. We capture characteristic pKa shifts of the active site residues, which dictate the experimentally determined activity profiles of the respective protease family. We find clear differences of active site pKa values within the respective families, which closely match the experimentally determined pH preferences of the respective proteases. These shifts are caused by a distinct network of electrostatic interactions characteristic for each protease family. While we find convincing agreement with experimental data for serine and aspartic proteases, we observe clear deficiencies in the description of the titration behavior of cysteines within the constant pH MD framework and highlight opportunities for improvement. Consequently, with this work, we provide a concise set of active site pKa values of aspartic and serine proteases, which could serve as reference for future theoretical as well as experimental studies.

The Effect of Ionic Strength on Protonation Constant of Monoethanolamine in Water at 303K

Amine-based absorption is a reactive system in which mass transfer and chemical reaction take place simultaneously. Protonation constant (pKa) is an important equilibrium reaction parameter that can be determined experimentally. The objective of this study is to evaluate the pKa of monoethanolamine (MEA) at different ionic strengths ranging from 0.01 to 6 moles of NaCl/kg of water at 303K by a potentiometric titration method. The results show that the pKa values, in general, increase as the ionic strengths increase. Moreover, the activity coefficients of species were also determined by the extended Debye-Hückel model. The pKa data and the activity coefficients obtained from this work could then be used for the kinetic and thermodynamic modeling in the absorber and desorber design.

PKAD: a database of experimentally measured pKa values of ionizable groups in proteins.

Ionizable residues play key roles in many biological phenomena including protein folding, enzyme catalysis and binding. We present PKAD, a database of experimentally measured pKas of protein residues reported in the literature or taken from existing databases. The database contains pKa data for 1350 residues in 157 wild-type proteins and for 232 residues in 45 mutant proteins. Most of these values are for Asp, Glu, His and Lys amino acids. The database is available as downloadable file as well as a web server (http://compbio.clemson.edu/pkad). The PKAD database can be used as a benchmarking source for development and improvement of pKa’s prediction methods. The web server provides additional information taken from the corresponding structures and amino acid sequences, which allows for easy search and grouping of the experimental pKas according to various biophysical characteristics, amino acid type and others.

Study of pH and temperature effect on lipophilicity of catechol-containing antioxidants by reversed phase liquid chromatography

Lipophilicity of selected antioxidant phytochemicals, including flavonoids, phenolic acids and xanthonoids, was determined by reversed phase high performance liquid chromatography with UV detection (RP-HPLC-UV). The analyses run at different temperature and pH conditions in isocratic mode suggested that lipophilicity as distribution coefficient (logD) between aqueous and organic phase decreases with increasing temperature. For all studied compounds, logD changes slightly at lower pH and much decreases at a given pH range corresponding to the strongest dissociation by which dissociation constant (pKa) was estimated experimentally as well as their bioavailability in gastrointestinal pH conditions were predicted. Thermodynamic parameters (ΔtrH°, ΔtrS°, ΔtrG°) demonstrated the increase in energy of transfer from the aqueous to the organic phase at higher pH thus decrease in lipophilicity. Experimental models of pH and temperature effect obtained by multiple regressions underlined their significant impact (p < 0.05) on lipophilicity. The provided lipophilicity profiles and pKa data are useful descriptors to assess the affinity of the studied compounds for biological membranes, enzymes, carriers and target sites. Furthermore, the obtained result may be useful in the design of functional and medical foods, especially in order to increase the bioavailability of bioactive constituents, such as phenolic compounds, based on their lipophilic and acid-base character.

Primary knock on atom spectra, gas production and displacement cross section for tungsten and chromium irradiated with neutrons at energies up to 14.1 MeV

In the ITER and other proposed fusion reactors, chromium and tungsten are proposed as first wall materials. Fusion of DT plasma will produce neutrons of 14.1 MeV energy. Nuclear reactions of fusion reactor material with such high energy neutrons lead to the displacement cascades and gas production in the reactor materials. All probable reaction channels such as (n,n’), (n,2n), (n,p), (n,α) and (n,d) are open for the interactions of these neutrons with tungsten and chromium. In the present study, energy spectra of recoils or PKA, gas production and displacement cross section for tungsten and chromium at neutrons of up to 14.1 MeV energy have been predicted using the appropriate nuclear models in the TALYS-1.8 code. In the cross section and PKA calculations, the contributions from possible reaction mechanisms such as direct, pre-equilibrium, and compound nuclear mechanisms have been considered. Calculated energy spectra of protons, alpha particles, and outgoing neutrons have been compared with recent ENDF-VIII, JEFF-3.3 and TENDL-2017 data libraries and discrepancies among them have been discussed. PKA data from each reaction channels have been calculated. PKA data have been used to predict the displacement cross-section with the Norgett, Robinson, and Torrens (NRT) approach. Calculated displacement cross section data of chromium and tungsten have been compared with existing data.