Predicting the Potentiometric Sensitivity of Membrane Sensors Based on Modified Diphenylphosphoryl Acetamide Ionophores with QSPR Modeling

Abstract

While potentiometric, plasticized membrane sensors are known as convenient, portable and inexpensive analytical instruments, their development is time- and resource-consuming, with a poorly predictable outcome. In this study, we investigated the applicability of the QSPR (quantitative structure–property relationship) method for predicting the potentiometric sensitivity of plasticized polymeric membrane sensors, using the ionophore chemical structure as model input. The QSPR model was based on the literature data on sensitivity, from previously studied, structurally similar ionophores, and it has shown reasonably good metrics in relating ionophore structures to their sensitivities towards Cu2+, Cd2+ and Pb2+. The model predictions for four newly synthesized diphenylphosphoryl acetamide ionophores were compared with real potentiometric experimental data for these ionophores, and satisfactory agreement was observed, implying the validity of the proposed approach.

Stability Constant and Potentiometric Sensitivity of Heavy Metal–Organic Fluorescent Compound Complexes: QSPR Models for Prediction and Design of Novel Coumarin-like Ligands

“…Importantly, only data obtained from the same experimental condition, such as temperature and pressure, were considered as having excluded external factors affecting the model. In this study, the data of two sensors’ properties were collected, including the stability constant (logβ) for Cd 2+ [ 36 , 37 , 38 , 39 ], Cu 2+ [ 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 ], and Pb 2+ [ 40 , 58 , 59 ] and the potentiometric sensitivity (PS ML ) [ 29 , 30 ].…”

“…In this sense, the quantitative structure–property relationship (QSPR) method [ 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 ], which is a computational approach composed by statistical models relating the structural features of ligands and their sensing properties, such as the stability constant or potentiometric sensitivity, have been employed to assist in the design and screening of fluorescence sensors [ 16 , 29 , 30 , 31 , 32 ]. Several achievements have been reported in this area, as summarized in Table 1 .…”

“…While the attained precision of the model in prediction was not very high (±0.5 logKsel), the model was able to distinguish reliably between the ligands with high-, medium-, and low-Mg 2+ concentration selectivity. Recently, Vladimirova and colleagues explored the potential of QSPR modeling in the prediction of potentiometric selectivity for plasticized polymeric membrane sensors based on newly synthesized ligands [ 30 ]. Attempts to develop novel QSPR models effectively applied for chemical sensors are ongoing and are needed to address the main issues currently posed in the field: (i) the limited number of data to be used for training together with the weak performance of the developed models and (ii) the lack of models to predict the multiple sensing properties of fluorescent probes and application for the virtual design of potential chemosensors.…”

Mathematical Properties of a Novel Graph-Theoretic Irregularity Index with Potential Applicability in QSPR Modeling

“…These molecular descriptors have been proposed at an accelerating rate; see, for instance, [9][10][11]. Recently, Vladimirova et al [12] employed QSPR modeling in correlating the sensitivity (potentiometric) of sensorial membranes. Topological descriptors are an important family of descriptors lying in the bigger class of molecular descriptors.…”