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

Abstract

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 p K 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 p K 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 p K 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.

Aqueous pKa prediction for tautomerizable compounds using equilibrium bond lengths

“…For the anti and syn conformers of the keto-enol state, an input geometry for the higher energy anti-conformation was manually generated by rotating the orientation of the O-H bond of the syn conformer by 180°. This process of generating the keto-enol anti state 15,16,[18][19][20][21][22] was repeated for the remaining 61 species.…”

“…Previous work [15][16][17][18][19][20][21][22] from our group, as well as the earlier work of others, has highlighted the utility of bond lengths [23][24][25] and Fig. 1 Structures of 1,3-diketone derivatives and schematic of our workflow.…”

Solving the Problem of Aqueous pKa Prediction for Tautomerizable Compounds Using Equilibrium Bond Lengths

“…The pK a data for the compounds investigated in this work have been procured from various sources. 16 were procured, samples were purchased for all except Clethodim (due to unavailability) and pK a measurements were taken using the same apparatus and experimental procedure as described above and in Technical Section S1. Literature values for 6 tetracycline derivatives (tet1 -tet6) were obtained from literature sources.…”

“…Recently, our approach to pK a prediction, called AIBL-pK a (Ab Initio Bond Lengths), has been proven to provide remarkably accurate prediction of acidity variation across congeneric series of guanidinecontaining species 16 and sulfonamides 17 . The aim of the current work is to bring attention to the issue of pK a prediction for other tautomerizable compounds and to provide a simple solution to this problem for 1,3-CHD and 1,3-CPD derivatives, an important scaffold in pharmaceutical and agrochemical research.…”

“…Scheme for AIBL-pK a model construction. Our proposed method of predicting pK a values [16][17][18][19][20][21][22][23] (Fig. 1C and Methods) makes use of equilibrium bond lengths from Density Functional Theory calculations (B3LYP/6-311G(d,p), Conductor-like Polarizable Continuum Model (CPCM)) as input features for regression models.…”