Diprotonation process of meso-tetraphenylporphyrin derivatives designed for Photodynamic Therapy of cancers: From Multivariate Curve Resolution to predictive QSPR modeling

[Display omitted] ► Diprotonation of 17 meso-tetraphenylporphyrin derivatives. ► MCR-ALS resolution of multi-component mixtures. ► Determination of stepwise protonation constants. ► Prediction of protonation constants from ET-State indices. Tetrapyrrole rings possess four nitrogen atoms, two of which act as Bröndsted bases in acidic media. The two protonation steps occur on a close pH range, particularly in the case of meso-tetraphenylporphyrin (TPP) derivatives. If the cause of this phenomenon is well known – a protonation-induced distortion of the porphyrin ring – data on stepwise protonation constants and on electronic absorption spectra of monoprotonated TPPs are sparse. A multivariate approach has been systematically applied to a series of glycoconjugated and hydroxylated TPPs, potential anticancer drugs usable in Photodynamic Therapy. The dual purpose was determination of protonation constants and linking substitution with basicity. Hard-modeling version of MCR-ALS (Multivariate Curve Resolution Alternating Least Squares) has given access to spectra and distribution profile of pure components. Spectra of monoprotonated species (H 3TPP +) in solution resemble those of diprotonated species (H 4TPP 2+), mainly differing by a slight blue-shift of bands. Overlap of H 3TPP + and H 4TPP 2+ spectra reinforces the difficulty to evidence an intermediate form only present in low relative abundance. Depending on macrocycle substitution, p K values ranged from 3.5 ± 0.1 to 5.1 ± 0.1 for the first protonation and from 3.2 ± 0.2 to 4.9 ± 0.1 for the second one. Inner nitrogens’ basicity is affected by position, number and nature of peripheral substituents depending on their electrodonating character. p K values have been used to establish a predictive Multiple Linear Regression (MLR) model, relying on atom-type electrotopological indices. This model accurately describes our results and should be applied to new TPP derivatives in a drug-design perspective.