The AIBLHiCoS Method: Predicting Aqueous pKa Values from Gas-Phase Equilibrium Bond Lengths

Easy to Use DFT Approach for Computational pKa Determination of Carboxylic Acids

In pKa computational determination, the challenge in exploring and fostering new methodologies and approaches goes in parallel with the amelioration of computational performances. In this paper a "ready to use methodology" has been compared to other strategies, such as the re-shaping in solvation cavity (Bondi radius re-shaping), wanting to assess its reliability in predicting the pKa of a broad list of carboxylic acids. Thus, the functionals B3LYP and CAM-B3LYP have been selected, using SMD as continuum solvation model. Exploiting our previous results, two water molecules were made explicit on the reaction centre. Data show that our model (CAM-B3LYP/2H2 O) is capable to accurately predict pKa, leading to mean absolute error (MAE) values lower than 0.5. Noteworthy, good results were achieved in computing the pKa of substituents bearing nitro and cyano groups. Focusing on B3LYP, eventually remarkable outputs were obtained only when Bondi correction was applied to the complex with two water molecules. Hence, massive outcomes were obtained in foreseeing the trichloro and trifluoro acetic acid pKa. These findings demonstrated that no complex level of theory nor external factor is required to accurately predict carboxylic acids pKa, with MAE well below 0.5 units.

First biphotochromic fluorescent protein moxSAASoti stabilized for oxidizing environment

Biphotochromic proteins simultaneously possess reversible photoswitching (on-to-off) and irreversible photoconversion (green-to-red). High photochemical reactivity of cysteine residues is one of the reasons for the development of "mox"-monomeric and oxidation resistant proteins. Based on site-saturated simultaneous two-point C105 and C117 mutagenesis, we chose C21N/C71G/C105G/C117T/C175A as the moxSAASoti variant. Since its on-to-off photoswitching rate is higher, off-to-on recovery is more complete and photoconversion rates are higher than those of mSAASoti. We analyzed the conformational behavior of the F177 side chain by classical MD simulations. The conformational flexibility of the F177 side chain is mainly responsible for the off-to-on conversion rate changes and can be further utilized as a measure of the conversion rate. Point mutations in mSAASoti mainly affect the pK_a values of the red form and off-to-on switching. We demonstrate that the microscopic measure of the observed pK_a value is the C-O bond length in the phenyl fragment of the neutral chromophore. According to molecular dynamics simulations with QM/MM potentials, larger C-O bond lengths are found for proteins with larger pK_a. This feature can be utilized for prediction of the pK_a values of red fluorescent proteins.

Enhancing Carbon Acid pKa Prediction by Augmentation of Sparse Experimental Datasets with Accurate AIBL (QM) Derived Values

The prediction of the aqueous pKa of carbon acids by Quantitative Structure Property Relationship or cheminformatics-based methods is a rather arduous problem. Primarily, there are insufficient high-quality experimental data points measured in homogeneous conditions to allow for a good global model to be generated. In our computationally efficient pKa prediction method, we generate an atom-type feature vector, called a distance spectrum, from the assigned ionisation atom, and learn coefficients for those atom-types that show the impact each atom-type has on the pKa of the ionisable centre. In the current work, we augment our dataset with pKa values from a series of high performing local models derived from the Ab Initio Bond Lengths method (AIBL). We find that, in distilling the knowledge available from multiple models into one general model, the prediction error for an external test set is reduced compared to that using literature experimental data alone.

Aqueous pKa prediction for tautomerizable compounds using equilibrium bond lengths

The accurate prediction of aqueous pK_a values for tautomerizable compounds is a formidable task, even for the most established in silico tools. Empirical approaches often fall short due to a lack of pre-existing knowledge of dominant tautomeric forms. In a rigorous first-principles approach, calculations for low-energy tautomers must be performed in protonated and deprotonated forms, often both in gas and solvent phases, thus representing a significant computational task. Here we report an alternative approach, predicting pK_a values for herbicide/therapeutic derivatives of 1,3-cyclohexanedione and 1,3-cyclopentanedione to within just 0.24 units. A model, using a single ab initio bond length from one protonation state, is as accurate as other more complex regression approaches using more input features, and outperforms the program Marvin. Our approach can be used for other tautomerizable species, to predict trends across congeneric series and to correct experimental pK_a values.

Experiment stands corrected: accurate prediction of the aqueous pK a values of sulfonamide drugs using equilibrium bond lengths

We show here for the first time that strongly correlated linear relationships exist between equilibrium bond lengths of the sulfonamide group and aqueous pK a values. Models are constructed for three variants of the SO2NHR group: primary benzene sulfonamide derivatives (e.g. diuretic drugs furosemide and hydrochlorothiazide), N-phenyl substituted 4-amino-N-phenylbenzenesulfonamide analogues (e.g. the sulfa antibiotic sulfadiazine) and phenylsulfonylureas (e.g. insulin secretagogue, glimepiride). In the context of these compounds, we present solutions to some of the more complex challenges in pK a prediction: (i) prediction for multiprotic compounds, (ii) predicting macroscopic values for compounds that tautomerize, and (iii) quantum chemical pK a prediction for compounds with more than 50 atoms. Using bond lengths as a powerful descriptor of ionization feasibility, we also identify that literature values for drug compounds celecoxib, glimepiride and glipizide are inaccurate. Our newly measured experimental values match our initial predictions to within 0.26 pK a units, whereas previous values were found to deviate by up to 1.68 pK a units. For glimepiride, our corrected value denotes a percentage of ionization at intracellular pH, which is only now in excellent agreement with its known therapeutic efficacy. We propose that linear relationships between bond lengths and pK a should emerge for any set of congeners, thus providing a powerful method of pK a prediction in instances where pK a data exist for close congeners, thereby obviating the need for thermodynamic cycles.

Enhancement of Thermodynamic Gas-Phase Acidity and Basicity of Water by Means of Secondary Interactions

A series of A⋅water, B⋅water complexes (A=acid, B=base) are studied at the G4 level of theory to show that water acidity or basicity can be modulated by non-covalent interactions. Protic and non-protic acids interacting with water form hydrogen bonds or other kinds of non-covalent interactions, respectively, that may dramatically change the acidity of water up to almost 360 kJ ⋅ mol^-1 in terms of enthalpy. Similarly, hydrogen bonds responsible for the interaction between typical small nitrogen-containing Lewis bases and water can enhance the proton affinity of water by almost 300 kJ ⋅ mol^-1 . Our results reveal that these large enhancements are linearly related with the binding energy of the charged complexes, and are determined by the Lewis acid-base properties of the molecule involved in the interaction, allowing a quite precise modulation of the corresponding acid-base properties of water.

Automated techniques in pKa determination: Low, medium and high-throughput screening methods

Drug discovery programs that generate hundreds of new molecular entities need efficient methodologies for physicochemical profiling. Several high-throughput methods for pK_a screening have been developed in the last 15 years to determine this key physicochemical parameter. Separation techniques such as HPLC-MS or capillary electrophoresis are particularly well-suited due to their high throughput and capacity to deal with impure or complex samples. In addition, potentiometric and (mostly) UV-metric-based methods (plate-based and automated systems), find their place as very precise methodologies for pK_a determination despite of somewhat lower throughput. Finally, pK_a prediction software packages are useful estimator tools but, to date, they cannot replace experimental measurements when accurate pK_a values are required.

Prediction of Aqueous pK a Values for Guanidine-Containing Compounds Using Ab Initio Gas-Phase Equilibrium Bond Lengths

In this work, we demonstrate the existence of linear relationships between gas-phase equilibrium bond lengths of the guanidine skeleton of 2-(arylamino)imidazolines and their aqueous pK _a value. For a training set of 22 compounds, in the most stable conformation of their lowest energy tautomeric form, three bonds were found to exhibit r ² and q ² values >0.95 and root-mean-squared-error of estimation values ≤0.25 when regressed individually against pK _a. The equations describing these one-bond-length linear relationships, in addition to a multiple linear regression model using all three bond lengths, were then used to predict the experimental pK _a values of an external test set of further 27 derivatives. The optimal protocol we derive here shows an overall mean absolute error (MAE) of 0.20 and standard deviation of errors of 0.18 for the test set. Predictions for a second test set of diphenyl-based bis(2-iminoimidazolidines) yielded an MAE of 0.27 and a standard deviation of 0.10. The predictive power of the optimal model is further demonstrated by its ability to correct erroneously reported experimental values. Finally, a previously established guanidine model is recalibrated at a new level of theory, and predictions are made for novel phenylguanidine derivatives, showing an MAE of just 0.29. The protocols established and tested here pass both of Roy's modern and stringent MAE-based criteria for a "good" quantitative structure-activity relationship/quantitative structure-property relationship model predictivity. Notably, the ab initio bond length high correlation subset protocol developed in this work demonstrates lower MAE values than the Marvin program by ChemAxon for all test sets.

Weighted Averaging Scheme and Local Atomic Descriptor for pKa Prediction Based on Density Functional Theory

As a continuation of our work on developing a density functional theory-based pK_a predictor, we present conceptual improvements to our previously published shell model, which is a hierarchical organization of pK_a training sets and which, in principle, covers all chemical space. The improvements concern the way the studied chemical compound is associated with the data points from the training sets. By introducing a new descriptor of the local atomic environment which foregoes dependence on chemical bonding and connectivity, we are able to automatically locate molecules from the training set that are most relevant to the proton dissociation equilibrium under study. This new scheme leads to the prediction of a single pK_a value weighted across multiple training sets and thus patches a defect disclosed in the formulation of our previous model. Using the new parametrization approach, the pK_a prediction gets rid of outliers reported in previous applications of our approach, eliminates ambiguity in interpreting the results, and improves the overall accuracy. Our new treatment accounts for multiple conformations both on the level of energetics and parametrization. Illustrative results are shown for several types of chemical structures containing guanidine, amidine, amine, and phenol functional groups, and which are representative of practically important large and flexible drug-like molecules. Our method's performance is compared to the performance of other previously published pK_a prediction methods. Further possible improvements to the organization of the training sets and the potential application of our new local atomic descriptor to other kinds of parametrizations are discussed.

Substituent effects on the basicity (pKa) of aryl guanidines and 2-(arylimino)imidazolidines: correlations of pH-metric and UV-metric values with predictions from gas-phase ab initio bond lengths

The AIBLHiCoS method accurately predicts the pK_a values of 2-(arylimino)imidazolidines using only a single ab initio bond length.