Reliable and accurate prediction of basic pK$$_a$$ values in nitrogen compounds: the pK$$_a$$ shift in supramolecular systems as a case study

Abstract

This article presents a quantitative structure–activity relationship (QSAR) approach for predicting the acid dissociation constant (pK$$_a$$ a ) 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$$^2$$ 2 ) 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$$_a$$ a prediction, offering valuable insights for drug design and supramolecular system optimization. Graphical Abstract

Thiophene Stability in Photodynamic Therapy: A Mathematical Model Approach

“…These findings are in complete alignment with those reported by van Tilborg [ 71 ], who concluded that electron-withdrawing groups reduce thiophene reactivity in the presence of singlet oxygen. This underscores the quantitative significance of electron-withdrawing phenomena through Mulliken electronegativity, a concept that has been endorsed by Taft [ 71 ] and has recently been deemed essential in developing a predictive model for pK a values [ 72 ].…”