INTRODUCTION
Simultaneously determining multiple pharmaceutical compounds without a preconcentration step represents a major analytical challenge [1]. Dopamine, an essential neurotransmitter, requires precise quantification due to its fundamental physiological roles [2]. As a key neurotransmitter, dopamine was initially characterized in 1958 by Carlsson and his team at the Laboratory of Chemical Pharmacology of Sweden’s National Heart Institute [2, 3]. Carlsson later received the Nobel Prize in Physiology or Medicine in 2000 for these foundational discoveries [4]. Neurotransmitters are generally categorized based on their effect on postsynaptic receptors, being either excitatory or inhibitory. Uniquely, dopamine exhibits both actions and holds vital importance within the central nervous, renal, cardiovascular, and endocrine systems [5, 6].
A deviation from normal dopamine concentrations is connected to various disorders. Excessively high levels may induce cardiotoxic effects, including tachycardia, hypertension, heart failure, and addictive behaviors. On the other hand, a deficit of this neurotransmitter correlates with conditions such as stress, Parkinson’s disease (according to Hornykiewicz) [7, 8], schizophrenia [9], Alzheimer’s disease [10, 11], and depression [12, 13]. Therefore, precise measurement of dopamine is crucial for deciphering its functions in biological systems and the related neural signaling routes [14-16]. These pathological associations further underline the analytical demand for sensitive, reproducible, and reliable detection platforms capable of monitoring dopamine fluctuations under physiologically relevant conditions.
According to recent investigations employing analytical and epidemiological strategies beyond descriptive biochemical observation, dopamine concentration in the striatum has been reported to be inversely related to Parkinson’s symptoms [17-19], highlighting the metabolic and clinical relevance of pathway-level interpretation. Approaches such as causal-inference modeling and clinically oriented metabolic assessment have further emphasized that phenylalanine participates in a broader physiological network linked to dopamine regulation rather than acting solely as a precursor. Increasing dopamine concentration is considered as a treatment for Parkinson’s [20, 21]. For this purpose, the L-DOPA medication (3,4-dihydroxyl-phenylalanine, Levodopa), which is a dopamine precursor, L-DOPA is widely recognized as an effective therapeutic strategy [22, 23]. In dopaminergic neurons, dopamine is obtained from the precursor tyrosine, and phenylalanine plays a role in providing tyrosine. This synthesis pathway is in the form of phenylalanine-tyrosine-L-DOPA-dopamine conversion, which provides the dopamine needed by the brain. Thus, it can be concluded that phenylalanine can play a role in brain dopamine levels and Parkinson’s disease. In addition, various studies have shown that phenylalanine deficiency can cause phenylketonuria, attention deficit hyperactivity disorder, schizophrenia, and adverse neurological outcomes [24, 25]. Taken together, this interconnected metabolic framework reinforces the analytical importance of investigating dopamine behavior in the presence of phenylalanine, particularly in studies aimed at developing sensing platforms capable of resolving closely related biochemical species.
The detection of dopamine has been accomplished through multiple analytical techniques. For instance, an Ultra-High-Performance Liquid Chromatography coupled with Electrospray Ionization Quadrupole Time-of-Flight Mass Spectrometry (UHPLC/ESI-Q-TOF-MS) method was established to quantify dopamine in Wistar rat brain tissue. In a comparable study, High-Performance Liquid Chromatography coupled with Tandem Mass Spectrometry (HPLC-MS/MS) was applied for analogous dopamine analysis. Despite their high sensitivity and reliability, these instrumental approaches often require expensive equipments, extensive sample preparation, and lack real-time applicability; therefore, ongoing research seeks alternative analytical strategies capable of overcoming these practical limitations [26, 27].
As a cost-efficient and comfortably available option, electrochemical methods present benefits including portability, user-friendliness, and considerable sensitivity [28]. Electrochemical sensing refers to analytical measurement based on monitoring electrical signals (current, potential, or impedance) generated by redox reactions at an electrode–solution interface, where achieving strong selectivity in the presence of interfering species remains a central design challenge. In this context, Khamlichi et al. developed an L-leucine-modified sol–gel carbon electrode for the voltammetric determination of homovanillic acid and dopamine in urine samples related to neuroblastoma diagnostics. Their approach demonstrated enhanced effective surface area, improved electrocatalytic activity, clear separation of oxidation peaks, and sub-micromolar detection capability, highlighting the potential of amino acid-based surface modification for boosting sensitivity and selectivity while maintaining simple electrode preparation and regeneration [29]. Subsequently, more sophisticated composite sensors incorporating stable and robust materials have been investigated, yet a significant number of these are still confined to operation in simplified buffer media instead of intricate biological samples [30].
Considerable researchs focus has been directed toward improving electrode functionality via modification with nanomaterials [31]. Metal–organic frameworks (MOFs) have emerged as particularly advantageous in this context owing to their unique structural and physicochemical characteristics. Their metal nodes exhibit catalytic and redox activity, while the exceptionally high surface area and porous architecture promote effective adsorption and interaction with target analytes. In addition, the tunable pore size and chemical functionality of MOFs enable tailoring of interfacial properties toward selective sensing applications, positioning them as attractive platforms for advanced sensor design [32].
Despite these advantages, the intrinsically low electrical conductivity of pristine MOFs have constrained their direct use in electrochemical sensing, motivating the development of hybrid systems that integrate MOFs with conductive matrices. Such integration aims to improve electron-transfer kinetics, structural stability, and dispersion uniformity, ultimately enhancing sensor performance. For instance, Wang et al. reported a carbon paste electrode modified with a MIL-101(Cr)/reduced graphene oxide composite, where the large surface area of the MOF combined with the conductivity of rGO resulted in improved sensitivity and distinct peak separation for the simultaneous detection of catechol and hydroquinone [33]. Their one-pot hydrothermal incorporation strategy enabled partial in-situ reduction of graphene oxide and formation of a conductive porous composite, representing a practical innovation toward overcoming MOF conductivity limitations while maintaining facile electrode fabrication and reproducibility. Also materials such as graphite or multi-walled carbon nanotubes are preferred owing to their minimal toxicity, high electrical conductivity, and capacity to form uniformly dispersed, durable composites with MOF structures. As an illustration, Su et al. developed an electrochemical sensing platform based on an amine-functionalized Zr-MOF (UIO-66-NH₂) integrated with MWCNTs, exploiting the synergistic increase in surface area, reduced interfacial impedance, and enhanced electrocatalytic activity [34, 35]. This design enabled sensitive multi-analyte neurotransmitter detection and, notably, demonstrated real-time monitoring of dopamine release from living cells, highlighting the biocompatibility and translational potential of MOF–carbon nanocomposites for clinical diagnostics.
Collectively, these advancements highlight the increasing promise of electrochemical sensors incorporating MOFs for the selective and sensitive identification of molecules with biological and clinical significance, including dopamine. Both dopamine and phenylalanine are physiologically active substances with vital functions in nervous and metabolic physiology, commonly discussed in clinical and pharmacological contexts. As a primary neurotransmitter, dopamine participates in a wide array of bodily processes such as the regulation of mood, control of movement, reward signaling, and cognitive operations. In contrast, phenylalanine is an essential aromatic amino acid that serves as a precursor for tyrosine, which in turn is metabolized to L‑DOPA and subsequently to dopamine and other catecholamine neurotransmitters. Beyond its role in neurotransmitter biosynthesis, phenylalanine is also critical for protein synthesis and contributes to maintaining normal growth, cognitive performance, and metabolic balance. [36, 37].
Given this metabolic relationship, monitoring dopamine in the presence of phenylalanine provides valuable insight into neurotransmitter homeostasis and metabolic balance. High or low levels of phenylalanine can directly affect dopamine biosynthesis, which in turn may contribute to neurological function and disorders such as Parkinson’s disease, phenylketonuria, or other neuropsychiatric diseases [38]. Therefore, the development of analytical platforms capable of simultaneously resolving these metabolically linked species is of particular importance for advancing biochemical monitoring and clinical diagnostics.
Overcoming these obstacles necessitates the creation of electrochemical sensors with high selectivity and sensitivity. A particularly viable strategy involves modifying electrode surfaces with nanomaterials like metal-organic frameworks (MOFs). MOFs are characterized by their substantial surface area, adjustable pore dimensions, and metal centers capable of redox activity, which collectively improve molecular discrimination and charge transfer efficiency. Integration of such materials into carbon paste electrodes promotes distinct interactions with dopamine versus phenylalanine, allowing for improved resolution of their respective oxidation signals and a reduction in mutual interference [39-41]. Moreover, tailoring MOF composition and electrode architecture offers opportunities to engineer interfacial microenvironments that selectively favor target recognition, thereby addressing limitations associated with conventional unmodified electrodes.
Furthermore, electrodes functionalized with MOFs can leverage variations in the adsorption kinetics, surface binding affinity, and electrochemical reactivity of dopamine compared to phenylalanine [41]. This exploitation ultimately enhances the resolution between their voltammetric peaks and allows for more precise quantitative analysis. Such a capability is especially beneficial in biological samples, where the presence of additional redox-active components and intricate background interferences can otherwise compromise the clarity of the analytical measurement [42]. Accordingly, incorporating MOF-based nanostructures into sensing platforms represents a rational step toward achieving reliable detection in complex matrices and lays the groundwork for the design strategy adopted in the present study.
The NH₂-MIL-88B metal–organic framework (MOF) exhibits a crystalline architecture composed of hexagonal channels and double-conical cages, providing a remarkably high specific surface area that is advantageous for electrochemical applications. Metal–organic frameworks are inherently structurally versatile; variations in precursor composition, stoichiometric ratios, and reaction conditions can yield distinct topologies, pore environments, and electronic properties. This synthetic tunability enables the rational selection of frameworks tailored to specific sensing objectives. In the present work, where enhancing sensor sensitivity through increased faradaic current response was a primary consideration, a framework capable of promoting efficient interfacial electron transfer was required [43, 44].
NH₂-MIL-88B(Fe) fulfills these criteria through its hybrid inorganic–organic architecture. The structure consists of Fe₃-oxo clusters coordinated by the linear ligand 2-aminoterephthalic acid (NH₂-H₂BDC). The aromatic backbone of the ligand contains conjugated π-systems that facilitate partial electron delocalization and promote charge mobility across the framework, while The presence of amine functional groups provides lone-pair electrons that increase the local electron density of the ligand framework and contribute to a higher density of electrochemically active sites within the structure, thereby promoting interfacial charge interaction and facilitating electron transfer processes. These interactions enhance adsorption affinity and improve interfacial charge transfer kinetics. Simultaneously, the Fe-oxo clusters serve as redox-active catalytic centers that mediate electron exchange processes, contributing to reduced charge-transfer resistance and increased oxidation current when incorporated into a conductive carbon matrix. The combined effects of conjugated pathways, electron-donating functional groups, and catalytically active metal sites therefore support improved electrochemical responsiveness and signal amplification [44, 45].
On this basis, NH₂-MIL-88B(Fe) was selected as an electrode modifier to strengthen current response and improve peak discrimination in voltammetric detection. 
In summary, the concurrent and sensitive determination of dopamine and phenylalanine is important for clinical diagnostics, pharmacokinetic investigations, and neurochemical research. Accordingly, this study focuses on the development of a carbon paste electrode modified with NH₂-MIL-88B(Fe) for electrochemical quantification of dopamine and phenylalanine was systematically evaluated in phosphate buffer media as well as in human and pharmaceutical samples.

MATERIALS AND METHODS
Materials in use
All materials used in this study were of laboratory grade and applied without further purification. The following reagents were purchased from Merck: paraffin oil, graphite powder (99% purity), iron(III) chloride hexahydrate (FeCl₃·6H₂O), 2‑aminoterephthalic acid (NH₂‑H₂BDC), N,N‑dimethylformamide (DMF), sodium hydroxide (NaOH, 85%), phosphoric acid (H₃PO₄, 85%), and other high‑purity chemicals. Dopamine and phenylalanine solutions at different concentrations were prepared by diluting a 0.01 M stock solution. Phosphate buffer solution (PBS) was used as the electrolyte, and buffer solutions with pH values ranging from 3.0 to 8.0 were obtained by adjusting with 0.1 M solutions of sodium hydroxide and phosphoric acid.

Analytical instruments
Electrochemical analyses were conducted using μ-Autolab TYPE III Potentiostat/Galvanostat in combination with a conventional three‑electrode arrangement. The modified carbon paste served as the working electrode, a saturated Ag/AgCl electrode (KCl sat.) served as reference and a platinum wire were employed as the counter electrode. Different pH values of phosphate buffer solutions  were prepared and adjusted using a Metrohm pH meter (Switzerland). A scanning electron microscopy (SEM, Mira3 Tescan) was used to characterize the morphology and X‑ray diffraction (XRD, STOE diffractometer, Cu‑Kα radiation) to investigate the crystalline structure of the synthesized NH₂‑MIL‑88B(Fe).

Microwave assisted synthesis of modifier nanostructure
The metal–organic framework NH₂-MIL-88(Fe) was synthesized via a rapid microwave-assisted procedure. Iron(III) chloride hexahydrate (FeCl₃·6H₂O) and 2-aminoterephthalic acid were dissolved in a 1:1 molar ratio in 30 mL of N,N-dimethylformamide (DMF) and sonicated for 10 min to obtain a clear yellow solution. The solution was transferred to a glass vessel and heated in a microwave reactor at 120 °C (140 W). During this process, the framework formed through a coordination-driven self-assembly mechanism. Partial hydrolysis of the hydrated Fe³⁺ precursor generated oxo/hydroxo intermediates, while thermal activation promoted deprotonation of the linker carboxylic groups. The resulting carboxylate anions coordinated to Fe³⁺ centers, inducing condensation into μ₃-oxo-bridged trinuclear iron clusters that served as secondary building units (SBUs). Subsequent bidentate coordination between linker carboxylates and neighboring Fe centers interconnected these SBUs, leading to nucleation and growth of the extended crystalline network. The microwave heating environment accelerated hydrolysis, coordination, and cluster organization, enabling rapid formation of the iron-based MOF structure. After cooling to room temperature, the resulting brown precipitate was collected by filtration, washed five times with ethanol to remove residual solvent and unreacted species, and dried overnight at 60 °C to obtain NH₂-MIL-88(Fe) [46, 47].

Method of preparation of working electrode
The working electrode, which was obtained by modifying carbon paste with NH₂-MIL-88(Fe), was obtained by mixing graphite powder (0.99 g) and nanostructure modifier (0.10 g) and adding paraffin oil to this homogeneous mixture at a weight ratio of 70:30. The resulting paste mixture was packed in a glass tube and connected to the rest of the electrical system with the help of a copper wire.

Processing of Real Samples
A volume of 1 mL freshly obtained human plasma or urine was diluted ten times using 0.1 M phosphate buffer solution (PBS, pH 7.0). For pharmaceutical analysis, a precisely weighed portion of a dopamine tablet was first dissolved in deionized water, after which PBS (pH 7.0) was added to adjust the solution to a final volume of 10 mL. Before electrochemical measurements, all sample solutions were passed through a 0.45 μm membrane filter to remove residual particulates.

RESULTS AND DISCUSSION
NH2-MIL-88-B(Fe) characterization
Scanning electron microscopy (SEM) analysis was used to investigate the morphology and structural features of NH₂‑MIL‑88(Fe). The SEM images in Fig. 1a, b show that the material exhibits an octahedral geometry in its less developed crystals, while the more mature particles exhibit a distinct hexagonal shape similar to quartz.
The FT‑IR spectrum of NH₂‑MIL‑88(Fe), presented in Fig. 1c, shows symmetric and asymmetric stretching vibrations of the –NH₂ group at around 3460 and 3370 cm⁻¹. Absorption bands corresponding to carboxylate groups are observed at 1580 and 1380 cm⁻¹. The peak at 1257 cm⁻¹ is attributed to the C-N stretching in the aromatic ring, while the vibrations of the C-H bonds from the organic linkers appear near 766 cm⁻¹. In addition, characteristic O-Fe-O vibrational modes associated with Fe(III) coordination are evident at 521 and 412 cm⁻¹ [48].
The XRD profile of NH₂-MIL-88(Fe), presented in Fig. 1d, displays well-defined diffraction peaks located at 2θ values of 9.1° (002), 10.3° (101), 13.1° (102), 16.6° (103), 18.7° (200), 19.4° (201), 20.7° (202), 26.3° (204), and 29.5° (302). These reflections correspond precisely to the simulated diffraction pattern generated from the crystallographic information file (CIF) of NH₂-MIL-88(Fe), archived in the Cambridge Crystallographic Data Centre (CCDC, ref. no. 647646) [49]. The strong agreement between experimental and simulated data provides clear evidence of the successful formation of NH₂-MIL-88(Fe) with excellent crystallinity and robust structural order [50].
Notably, the presence of intense peaks in the low-angle region is indicative of long-range periodic ordering, which is characteristic of porous metal–organic framework architectures and confirms the preservation of the framework topology. Furthermore, no sharp diffraction peaks are observed at higher diffraction angles (2θ > 30°), where crystalline iron oxide phases typically appear. The absence of such reflections suggests that iron species are fully incorporated into the coordination framework rather than forming segregated oxide impurities such as Fe₂O₃.
Overall, the diffraction pattern confirms the formation of a phase-pure NH₂-MIL-88(Fe) structure with good crystallinity and structural integrity, supporting the successful synthesis of the targeted MOF material.[47, 48, 51].

Electrochemical Investigations
Differential pulse voltammetry (DPV) was employed to study the electrochemical oxidation of dopamine (500 μM) at the NH₂‑MIL‑88(Fe)/CPE modified electrode within the pH window of 3–8. As illustrated in Fig. 2a, the oxidation peak current (Ip) gradually increased as the pH rose from 3 to 7, attaining its maximum intensity at pH 7, after which a noticeable decline was observed at more alkaline conditions. Based on this trend, pH 7 was selected as the most favorable environment for subsequent electrochemical investigations. In parallel, the oxidation peak potential (Ep) shifted progressively toward lower (more negative) values with increasing pH, signifying the active involvement of protons in the redox process. This observation highlights that the electrochemical response of dopamine is strongly dependent on the proton concentration at the electrode–solution interface. Fig. 2b further demonstrates a nearly perfect linear correlation between Ep and pH, with a slope of −0.0525 V/pH (R² = 0.9965). Such a slope is in close agreement with the theoretical prediction of the Nernst equation (E=E0-αRT/nF pH), thereby confirming a reaction pathway that involves the coupled transfer of one electron and one proton (n = 1) during dopamine oxidation.
The cyclic voltammetric profile obtained for a 500 μM dopamine solution prepared in 0.1 M phosphate buffer at pH (7.0) reveals a pronounced dependence of the anodic peak current on the applied scan rate. As the potential sweep was varied from 10 to 150 mV/s, a progressive enhancement in the peak current intensity was observed, shown in Fig. 3a. This behavior is in excellent agreement with the theoretical framework of the Randles–Sevcik equation, which predicts that the peak current (Ip) increases proportionally with the square root of the scan rate, reflecting accelerated electron transfer kinetics at the electrode surface under faster potential sweeps.
Fig. 3b,c provide further quantitative validation of this phenomenon. The plot of peak potential against the logarithm of current, as well as the linear relationship between current and the square root of scan rate, both demonstrate a strong correlation, thereby confirming that the electrochemical oxidation of dopamine at the NH₂‑MIL‑88(Fe)/CPE interface is predominantly governed by a diffusion‑controlled mechanism. This indicates that the transport of dopamine molecules from the bulk solution to the electrode surface is the rate‑determining step in the redox process.
In addition, the cyclic voltammograms exhibit a well‑defined cathodic peak corresponding to the reduction of oxidized dopamine species. The presence of this return peak, combined with the absence of any significant negative shift in potential across the range of scan rates studied, provides compelling evidence for the reversible nature of the dopamine redox transformation. Such reversibility underscores the stability of the electron‑proton transfer pathway and highlights the suitability of the modified electrode for sensitive and reproducible electrochemical detection of dopamine. Also, considering that the slope of the Linear plot in Fig. 3b is equal to (2.3RT/n (1-α) F) according to the Tafel plot, the electron transfer coefficient (α) was obtained to be about 0.8 (α = 0.8), which confirmed the existence of a reversible electrooxidation reaction.
Chronoamperometric measurements were performed over a concentration range of dopamine between 100 and 400 μM. The resulting current–time profiles displayed a clear linear dependence when plotted against the inverse square root of time (t⁻¹/²), a trend that is fully consistent with the theoretical prediction of the Cottrell equation. This agreement confirms that the electrochemical oxidation of dopamine under the applied conditions is predominantly governed by diffusion‑controlled kinetics. From the slope of the calibration line, in combination with fundamental electrochemical parameters—including Faraday’s constant (F = 96,485 C·mol⁻¹), the single‑electron transfer number (n = 1), and the defined electrode surface area (A = 0.115 cm²) the diffusion coefficient of dopamine was calculated to be approximately 4.3 × 10⁻⁶ cm²·s⁻¹, reflecting efficient mass transport within the system Fig. 4.
Fig. 5 illustrates the voltammetric behavior of both the unmodified carbon paste electrode (CPE) and the MOF‑modified CPE when tested in a ferri/ferrocyanide redox system containing Fe(II)/Fe(III) at a scan rate of 100 mV/s. The modified electrode produced a remarkably stronger current response than the bare CPE, highlighting its superior electrocatalytic efficiency. This enhancement can be attributed to the cooperative interaction between NH₂‑MIL‑88B(Fe) and graphite, which facilitates faster electron transfer and improves the overall performance of the sensor. To quantitatively assess this improvement, the electrochemically active surface area was estimated using the Randles–Sevcik equation based on cyclic voltammetric data obtained in 5 mM ferri/ferrocyanide solution. The calculated active surface area increased from 0.0106 cm² for the bare CPE to 0.115 cm² for the NH₂-MIL-88B(Fe)/CPE, corresponding to an approximately eleven-fold enhancement after modification. This substantial increase is attributed to the porous framework and high surface accessibility of NH₂-MIL-88B(Fe), which introduce abundant electroactive sites and facilitate electron transport at the electrode–electrolyte interface. Consequently, the cooperative contribution of the MOF structure and graphite matrix leads to improved electrocatalytic efficiency and overall sensor performance.
To further elucidate the interfacial charge transfer characteristics, electrochemical impedance spectroscopy (EIS) was conducted using both the bare CPE and the MOF‑modified CPE electrodes in a redox solution containing 5 mM [Fe(CN)₆]³⁻/⁴⁻ with 0.1 M KCl as the supporting electrolyte. The Nyquist plots revealed a striking difference between the two electrodes Fig. 6a: the MOF/CPE exhibited a substantially smaller semicircular arc compared to the pristine CPE. This reduction in arc diameter corresponds to a lower charge transfer resistance (Rct), indicative of enhanced electrical conductivity and improved electron mobility at the electrode interface. The observed enhancement can be attributed to the nanostructured NH₂‑MIL‑88B(Fe) framework, which not only facilitates rapid electron transport but also increases the electrochemically active surface area (EASA), thereby amplifying the overall electrocatalytic performance of the modified sensor. As illustrated in Fig. 6b, the fitted Nyquist plots together with the corresponding equivalent circuit for both the bare and modified electrodes were obtained using NOVA 2.1 analytical software. The excellent agreement between the experimental data and the fitted curves confirms the reliability of the selected circuit model for describing the interfacial electrochemical behavior. From the fitting results, the charge-transfer resistance (Rct) values were extracted, revealing a pronounced decrease from 323 Ω for the bare electrode to 45.9 Ω after modification. This significant reduction indicates facilitated electron-transfer kinetics at the electrode–electrolyte interface, confirming the beneficial role of the NH₂‑MIL‑88B(Fe) modification    in enhancing conductivity and electrochemical performance.

Concentration calibration curve
Fig. 7a illustrates the electrochemical performance of the fabricated MOF‑modified electrode was systematically examined using differential pulse voltammetry (DPV) across a wide concentration window of dopamine ranging from 0.7 to 900 μM. As the analyte concentration increased, the anodic peak current exhibited a proportional enhancement, clearly defining two separate linear calibration domains that highlight the sensor’s broad dynamic range and reliable quantitative response under varying experimental conditions Fig. 7b.
In addition, the detection capability of the system was rigorously evaluated. The calculated limit of detection (LOD) was found to be 0.18 μM, determined according to the conventional (3Sb/slope) criterion. This remarkably low threshold demonstrates the high sensitivity of the NH₂‑MIL‑88(Fe)/CPE platform and its ability to detect dopamine at trace levels with precision. Such performance underscores the synergistic contribution of the MOF structure in facilitating rapid electron transfer, expanding the electroactive surface area, and thereby enabling accurate quantification of dopamine even within complex biological or pharmaceutical matrices. A comparison of the results of this study with some other studies can be seen in Table 1.

Determination of dopamine in the presence of phenylalanine 
The main goal of this work was to enable the simultaneous detection of dopamine alongside phenylalanine. DPV measurements revealed two very clear oxidation peaks at different potentials corresponding to each analyte, allowing their independent measurement. These distinct voltammetric responses confirm the electrode selectivity and peak resolution, which is characterized by the negligible signal shift of dopamine in the presence of different concentrations of phenylalanine, and it can be said that in the performance of the modified electrode NH₂‑MIL‑88(Fe)/CPE overlap and interference in the simultaneous detection and measurement of dopamine in the presence of phenylalanine have been minimized (Fig. 8).

Selectivity and stability investigations
Selectivity was evaluated by examining the sensor’s response to dopamine in the presence of common biological interfering agents. The addition of glucose, urea, uric acid, ascorbic acid, albumin and ions caused no substantial alteration to the dopamine signal, demonstrating high selectivity (Table 2). Moreover, the sensor maintained more than 98% of its initial response after one month period, which confirms its long-term stability.
To measure the stability of the modified electrode performance, five cyclic voltammetry measurements were used consecutively in the presence of 500 μM dopamine in buffer medium with a scan rate of 100 mV/s. The results of this test showed that there was no significant change in the peak current, indicating the high stability of the NH₂‑MIL‑88(Fe)/CPE electrode. Since the RSD in this measurement was less than 5%, it can be concluded that the working electrode has acceptable repeatability.

Real Sample Analysis
To validate its practical utility, the sensor was employed for dopamine detection in human serum via the standard addition technique. Given the complexity of this biological medium, a pretreatment step was applied to the samples prior to measurement. The obtained recovery values were accurate with negligible signal inhibition, proving that the MOF/CPE-based sensor can reliably quantify dopamine in intricate real-world matrices, including environments containing interferents such as phenylalanine (Table 3).

CONCLUSION
In this study, a carbon paste electrode integrated with a metal–organic framework (MOF) is reported for the first time as a highly sensitive platform capable of simultaneous determination of dopamine and phenylalanine. Comprehensive electrochemical characterization demonstrated that the incorporation of MOF into the carbon matrix markedly improves the intrinsic conductivity, enhances electrocatalytic efficiency, and expands the electroactive surface area of the electrode. These modifications collectively promote faster electron transfer kinetics, thereby enabling efficient detection of both target biomolecules.
Under carefully optimized experimental conditions, the engineered sensor delivers a broad linear response range from 0.7 to 100 μM and 100 to 900.0 μM, coupled with an exceptionally low detection threshold of 0.18 μM for dopamine. Kinetic analysis further revealed valuable parameters, including a transfer coefficient (α) of 0.8 and a diffusion coefficient (D) of 4.3 × 10⁻⁶ cm²/s, in the electrochemical process. Importantly, validation experiments performed in real sample matrices confirmed the sensor’s applicability, demonstrating reliable performance and practical utility for monitoring of dopamine and phenylalanine in complex environments.

CONFLICT OF INTEREST
The authors declare that there is no conflict of interests regarding the publication of this manuscript.