# Application of in-silico docking for green electrochemical quantification of prucalopride succinate in pharmaceutical, urine, and milk matrices

## TL;DR

This paper introduces a green and efficient method using ion-selective sensors to measure prucalopride succinate in various samples, validated by in-silico docking.

## Contribution

The study introduces a novel green electrochemical method using cyclodextrin-based sensors for prucalopride succinate quantification.

## Key findings

- The α-cyclodextrin sensor showed the best performance with a Nernstian slope of 56.87 mV/decade and a detection limit of 7.50 × 10−7 M.
- Prucalopride was successfully quantified in dissolution media, urine, and milk with minimal sample preparation.
- The proposed method outperformed existing techniques in green analytical metrics like GAPI and analytical eco-scale.

## Abstract

The development of ion-selective sensors as green and energy-efficient substitutes is a promising trend in today’s analytical techniques. So, three distinct polyvinyl chloride sensors modulated by ionophores of cyclodextrins (α-, β-, and γ-cyclodextrins) were built, and their composition was optimized for rapid in-situ estimation of prucalopride succinate in different matrices. The experimental work was backed up by applying molecular docking, whose results were consistent with the practical findings, offering a creative strategy to reduce the experiment’s costs and duration. According to findings, the α-cyclodextrin sensor outperformed the other proposed sensors in terms of Nernstian slope (56.87 mV/decade), linearity range (1 × 10−6 M – 1 × 10−2 M), and detection limit (7.50 × 10−7 M). For the first time and with minimal sample pre-treatment, prucalopride was quantified with excellent recoveries in dissolution media, human urine, and formula milk samples employing the proposed α-cyclodextrin sensor. The proposed three sensors were validated following IUPAC guidelines. The proposed technique, represented by the proposed three sensors, has the following merits: high sample throughput, quick analysis, high selectivity, wide linearity ranges, and low detection limits, making it apt for routine prucalopride assessment, either in QC centers or in bioavailability units, at the most affordable price. Concerning the statistical assessment, there weren’t palpable disparities in functioning between the suggested technique and the published one. Concerning green assessment, the proposed technique surpassed the published techniques in both GAPI and analytical eco-scale metrics.

The online version contains supplementary material available at 10.1038/s41598-024-85001-y.