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In this article, we are going to report results of one our studies focused on investigation of the binding and inhibition of the calcineurin (CAL) by tacrolimus (TCL) with the help of electrochemical techniques which have been assisted by chemometric methods. Our study was divided to several sections where the first section was focused on recording different instrumental electrochemical data to extract some information. Next section was devoted to the analysis of recorded electrochemical data by hard- and soft-modeling chemometric algorithms for extracting new information and also to verify results obtained by direct analysis of the electrochemical data. The next section was focused on molecular docking techniques to extract theoretical information to verify the information obtained by experimental sections and fortunately, the results of different sections confirmed each other and recommended inhibition of the CAL by TCL. We could compute n and binding constant (Kb) which were 2 and 2.33 × 104 mol−1 L, respectively. Finally, we have developed an amperometric technique based on binding and inhibition of the CAL by TCL to determine CAL.

In this work, inhibitory effects of naringenine (NAR) on cytochrome P450 (CYP450) were investigated by recording different types of electrochemical data including electrochemical impedance spectroscopy (EIS), differential pulse voltammetry (DPV), linear sweep voltammetry (LSV), cyclic voltammetry (CV) and normal pulse voltammetry (NPV). First of all, direct analysis of the electrochemical data helped us to obtain some information about binding of NAR to CYP450 and then, electrochemical data were hard-modeled by EQUISPEC, SPECFIT, SQUAD and REACTLAB to compute binding constant of the NAR to CYP450. Then, DPV, LSV, CV and NPV data were row-wise augmented into a data matrix and analyzed by MCR-ALS to obtain more information about binding of NAR to CYP450. Further investigation of the binding of NAR to CYP450 was investigated by molecular docking and these results were compatible with experimental results. On the whole, our study confirmed a strongly binding of NAR to CYP450 which justified inhibitory effects of NAR to CYP450. Finally, our study was expanded to develop a novel electroanalytical method for determination of the CYP450 based on inhibiting of CYP450 by NAR. Statement All the sections of this work have been performed by Dr. Ali R. Jalalvand.

In this work, for the first time, we have developed a novel and very interesting electroanalytical methodology assisted by first-order multivariate calibration (MVC) for simultaneous determination of doxorubicin (DX), daunorubicin (DN) and idarubicin (ID) as three chemotherapeutic drugs at simulated physiological conditions. A sever overlapping was observed among signals of the three drugs which hindered us for simultaneous determination of them by conventional electroanalytical techniques. Therefore, we had to assist our method by chemometric approaches to develop a novel method for simultaneous determination of DX, DN and ID. Among the existing electroanalytical methods, electrochemical impedance spectroscopy (EIS) due to its high sensitivity was chosen. After individual calibration of the three drugs with the EIS data, a set of calibration samples was designed which was used to develop several first-order MVC models by partial least squares (PLS), continuum power regression (CPR), radial basis function-partial least squares (RBF-PLS), RBF-artificial neural network (RBF-ANN) and least squares-support vector machines (LS-SVM) as linear and non-linear chemometric algorithms. Then, performance of the developed MVC models in predicting concentrations of DX, DN and ID in synthetic samples was compared to choose the best model for the analysis of real samples. Our records confirmed more superiority of RBF-PLS algorithm than the other developed models which motivated us to choose it for the analysis of real samples. Fortunately, the results of the RBF-PLS in the analysis of real samples towards simultaneous determination DX, DN and ID was acceptable.

In this work, we have developed a novel electroanalytical methodology based on generation of third-order differential pulse voltammetric (DPV) data for simultaneous determination of ascorbic acid (AA) and uric acid (UA) in the presence of dopamine (DPA) as uncalibrated interference. To generate third-order DPV data, two instrumental parameters including pulse height and pulse time were changed. Each sample had a three-way data array containing six matrices recorded at six different pulse times and each matrix had six vectors recorded at six different pulse heights. By joining three-way data arrays, we could generate a four-way data array. After data pre-processing, a calibration model was built by augmented parallel factor analysis (APARAFAC) and multivariate curve resolution-alternating least squares (MCR-ALS) and their performance for simultaneous determination of AA and UA in the absence and presence of DPA as uncalibrated interference was examined by predicting concentrations of validation and test set, respectively. Our records confirmed successfulness of MCR-ALS in predicting concentrations of AA and UA in both validation and test sets and then, it was applied to the analysis of real samples. Fortunately, the results of MCR-ALS in analyzing real samples were acceptable which also confirmed development of a novel method. Keywords: Ascorbic acid, Uric acid, Dopamine, Four-way calibration, APARAFAC, MCR-ALS

Sensitivity is a key parameter for an analytical method, because it determines the analytical performance of the method in analyzing low concentration samples. In electroanalytical methods, charging current causes interference with the accurate measurement of the faradaic current and restricts sensitivity and detection limit. How to separate faradaic current from charging current in an electrochemical system has been a challenge in the last several decades. Chemometrics has speeded up the development of electrochemical analysis and with the help of chemometric methods such as multivariate curve resolution alternating least squares (MCR-ALS), iterative target transformation factor analysis (ITTFA) and alternating trilinear decomposition (ATLD) contribution of charging current from total current can be eliminated. In this review, we will focus on applications of chemometrics to separation of charging current from total current to obtain net faradaic current for improving sensitivity of electroanalytical methods based on the literature in this field. Keywords: Chemometrics, Electroanalytical methods, Sensitivity, Detection limit, Charging current, Faradaic current