Next Article in Journal
Determination of the Most Influential Factors on the Quality of Resin Gears Manufacturing
Previous Article in Journal
Extreme Dual-Parameter Optical Fiber Sensor Composed of MgO Fabry–Perot Composite Cavities for Simultaneous Measurement of Temperature and Pressure
Previous Article in Special Issue
Polynitrogen Bicyclic and Tricyclic Compounds as PDE4 Inhibitors
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Modelling of Cathinone–Carbon Nanotube Complexes’ Stability: Theory with a Cancer Treatment Perspective

by
Natalina Makieieva
1,*,
Teobald Kupka
1 and
Oimahmad Rahmonov
2,*
1
Faculty of Chemistry and Pharmacy, University of Opole, 48, Oleska Street, 45-052 Opole, Poland
2
Institute of Earth Sciences, Faculty of Natural Sciences, University of Silesia in Katowice, 41-200 Sosnowiec, Poland
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2025, 15(16), 8892; https://doi.org/10.3390/app15168892
Submission received: 26 June 2025 / Revised: 30 July 2025 / Accepted: 1 August 2025 / Published: 12 August 2025
(This article belongs to the Special Issue Research on Organic and Medicinal Chemistry)

Abstract

Featured Application

This work could provide preliminary data for experimental studies of the stability of cathinone–COOH/OH functionalized carbon nanotube complexes in environments with different pH. These data may have potential use in the development of new targeted anticancer therapies.

Abstract

Today, cathinone and its synthetic derivatives are among the most popular narcotics in the world. Their different cytotoxic activities on humans are increasingly and rapidly being published in forensic reports and the scientific literature. New studies demonstrate that these compounds target the apoptosis of some human cancer cell lines. These results could potentially open a new perspective for cathinones’ use as potential therapeutic agents. Even so, the psychostimulant effects of these compounds require testing their activity in the form of drug delivery systems. In our work, we report on the first theoretical studies concerning the potential use of functionalised carbon nanotubes (CNTs) as carriers in the targeted transport of cathinones. Using density functional theory (DFT), we predicted cathinone–CNT interaction energies in environments with different polarity, as well as the stability of complexes in simplified models of healthy and cancer tissue. The results of the current work provide first-step insights into cathinone–CNT non-covalent complex formation in neutral and acidified environments. This study may serve as the theoretical basis for further experimental works on the possibility of using cathinone–CNT complexes in targeted anticancer therapy.

1. Introduction

Changing urban environment conditions lead to the physiological and psycho-emotional modification of the human organism. Consequently, its carcinogenic factor resistance is reduced. Morbidity and mortality caused by various forms of cancer are increasing every year [1]. According to official world statistics, in 2022, about 20 million new cases of the disease and more than 9 million deaths caused by various neoplasms were registered [2]. Therefore, today, new anticancer therapies are one of the leading topics in medicinal chemistry [3]. An efficient treatment without side cytotoxic effects has not been developed yet [3].
Many studies present the use of known cytostatics against new forms of neoplasms, as well as in synergistic therapies to increase their anticancer activity [4,5,6,7]. Scientific works increasingly describe the anticancer potential of new and known natural [8,9,10,11,12] and synthetic compounds [11,13,14]. Particular attention is also being paid to drugs targeting various forms of cancer cell death—reactive oxygen species (ROS) formation [15], immunogenic cell death [16], ferroptosis [17,18], cuproptosis [19], and others [20,21,22]. The diverse localization and degree of neoplasm development, the emergence of new drug-resistant tumours, and the different interactions of cytostatics with patients’ healthy organs still do not allow the preparation of universal anticancer agents. This leaves a question regarding the anticancer properties open for different classes of substances. Attention is being drawn to new derivatives of known anticancer drugs (for example, transition metal complexes [13] or coumarin-based derivatives [11]), as well as to new organic and inorganic compounds.
One of the once “new” groups with unexpected therapeutic potential is cannabinoids. Naturally occurring in Cannabis sativa L. and Cannabis indica plants, these substances have long been known as psychostimulants [23]. The discovery of their anticancer properties in the past century [24] led to active works on the development of new synthetic derivatives with an improved therapeutic profile. The effectiveness of cannabinoids in the treatment of multiple myeloma [25], osteosarcoma [26], glioblastoma multiforme [27], and triple-negative breast cancer [28] was described. In addition, their anti-inflammatory properties [29,30,31], potential for treating Alzheimer’s [32] and Parkinson’s [33] disease, possible uses in treating neurocognitive deficiencies associated with HIV-1 infection [34], and potential for promoting bone [35] and skin [36] regeneration have been presented.
Another well-known group of psychostimulants is cathinone and its synthetic derivatives. Cathinone is a metabolite of the Catha edulis plant, which grows in North Africa and Western Asia. This compound is an amphetamine β-keto derivative and is popular as a cheap stimulant in countries where C. edulis naturally grows [37]. In most countries, the use of this narcotic substance is restricted.
Due to the ease and low cost of structure modification, many synthetic derivatives of cathinone have been produced over the years [38,39,40]. These substances are used as cheap and less psychoactive amphetamine and cocaine substitutes [39,41,42]. The production of cathinone and its derivatives is so massive that it is difficult to describe the current size of this drug group [43]. Their psychostimulant activities and addiction properties significantly limit research on their pharmacological properties. Despite this, the potential of some cathinones for the treatment of depression has been described. Currently, bupropion is a registered antidepressant and smoking cessation medicine [44,45]. Pyrovalerone has shown effectiveness in treating chronic fatigue [46], and amphepramone has demonstrated strong appetite-suppression effects without psychostimulation [47]. It is worth noting that some synthetic cathinone derivatives have demonstrated the targeting of apoptosis in some human cancer cell lines [48,49,50,51,52,53,54,55,56,57,58,59].
Legal restrictions significantly limit research on cathinones in the pharmaceutical field and do not allow extensive studies to determine the structural–psychostimulation correlation. Even so, some reports on decreasing the psychotropic properties of cathinones while increasing their cytotoxicity can be found in the literature [60,61,62,63]. A tendency towards a selective cytotoxic effect on cancer tissues has also been noted. Moreover, the increase in mephedrone cytostatic properties with the development of carcinogenesis in cancer tissue is also described [64,65,66,67]. For this reason, similar to cannabinoids, research into the anticancer potential of cathinone and its derivatives should not be ignored. On the other hand, possible psychostimulant and addictive properties require introduction of cathinones into the body in a form that avoids these side effects.
Anticancer agents are commonly administered via classical chemotherapy. This method has a number of limitations. The main disadvantages of conventional chemotherapy are toxic side effects on patients’ healthy organs, the limited solubility of cytostatics in physiological fluids, and the repeated administration of large doses of drugs, which carries the risk of overdose. A potential solution to all the above-mentioned limitations is targeted transport of cytostatics in drug delivery systems (DDSs). This form of anticancer therapy involves a preparation of reversible drug complexes with a biocompatible carrier and subsequent controlled drug transport to the cancerous tissue [3]. The increase in cytostatic activity of DDS administrated medicines compared to classical injection is described [68,69]. The targeted delivery also helps overcome the multidrug resistance of neoplasms [69,70,71] and increases general drugs’ permeability into tumours [72,73,74]. Growing anticancer activity has also been observed for alternative therapies in DDS forms—nanocytostatics [75,76], immunotherapy [77], ferroptosis targeting [78], and potential natural-origin drugs [79,80]. Nevertheless, the effectiveness of the DDS is often limited by the difficulties in choice of a good carrier. The key criteria are controlled drug transport and release near the molecular target, as well as the carrier removal from the body without excessively harming the patient’s health [3]. For this reason, intensive research on new carriers’ preparation and the improvement of materials with good effectivity in DDS therapies is being conducted. Attention is paid to synthetic and natural polymers [73,74,77], vesicular systems [70,72,79], antibodies [20], and others. In addition, the development of nanotechnology in recent years introduces new possibilities for the use of nanostructures as effective DDS carriers [69,74,76]. The high efficiency of metal nanoparticles [80,81], as well as ordered carbon nanostructures in the targeted transport of anticancer agents [82,83,84,85,86], is described. The introduction of the nanocomplexes enhances the absorption of the drug by the cancer cell [87], increases the therapy selectivity [88], and improves the transport of the drug into drug-resistant neoplasms [82]. Some studies demonstrate that carbon nanocarriers with certain particle sizes do not provide toxic effects on the human and animal body in certain concentrations [89,90]. It has also been noted that the additional functionalization of these structures allows for preventing possible negative effects on the human body [88,91]. For this reason, this work is intended to present introductory molecular modelling of the stability of the complexes, with cathinones as potential drugs in cancer treatment and carbon nanotubes as potential carriers.
The stability of DDS complexes and their controlled release is often based on the environment pH gradient. It is reported that the extracellular pH value of healthy tissues is close to neutral (about 7), and in the case of neoplasms it acquires an acidic character [92,93]. Therefore, in this work, the geometry and stability of the potential DDS complexes at different pH values are modelled. The influence of the cathinone and its derivatives structure on the number and strength of the interactions formed with different structural fragments of the nanotube—functional groups and an aromatic carbon skeleton—is considered. The influence of the environment polarity on the complexes’ geometrical parameters and energy prediction is also considered. The main goal is the analysis of the complexes’ stability in the simplified model of healthy tissue environment, their degradability in an acidic simplified model of neoplasm surface, and the preliminary determination of the efficiency of the carbon nanotubes’ classical functional groups (hydroxyl and carboxyl) in the targeted transport of cathinones. These results could provide a theoretical foundation for future experimental studies on the stability and anticancer efficacy of cathinone–nanotube complexes under varying physiological pH conditions.

2. Methods

All calculations were performed using Gaussian 16 C.01 program package [94]. Density functional theory was used to predict the structural, spectroscopic, and energy parameters for cathinone and its derivatives, carboxylated and hydroxylated carbon nanotubes, and the drug-nanotube complexes. All structures of CNTs and studied cathinones were created in GaussView [95]. The B3LYP hybrid density functional with Grimme’s D3BJ empirical correction for dispersion were used [96,97,98,99]. This method demonstrated good prediction of studied parameters for models of carbon nanostructures, as well as other small- and middle-size organic molecules [100,101,102,103,104,105,106,107]. Due to the relatively large size of interacting complexes, Pople’s type triple-zeta quality 6-311++G** basis set was used for all calculations [108]. All studied compounds and their complexes were optimised without any geometrical constrains and with tight convergence criteria. The lack of imaginary harmonic frequencies was used as a criterion for the obtained equilibrium structures. The environment polarity effect on CNT–cathinone complexes and model dimers (protonated/deprotonated formic acid—protonated methylamine), geometrical parameters, and interaction energies was studied in the gas phase and using a polarisable-continuum model (PCM) of chloroform (only for model dimers) and water [109]. To improve the intermolecular non-covalent interactions prediction, the first hydration sphere was further enhanced by adding one or two discrete water molecules near the sides of polar intermolecular non-covalent interactions. The interaction energy E C N T C a t h of complexes (kcal/mol) was determined using the following Formula (1):
E C N T C a t h = ( E C N T C a t h E C N T E C a t h ) 627.509
where E are the electronic energies of the studied complex or its fragments. The obtained values were corrected for the basis set superposition error (BSSE) using the counterpoise method [110].

3. Results and Discussion

The systematic theoretical studies revealed several cathinone complexes with single-walled carbon nanotubes (SWCNTs) end-functionalised by a single carboxyl or hydroxyl group. The non-substituted ends of all SWCNT models were capped with hydrogen atoms. To avoid overcrowding the work with figures and tables, the obtained complexes’ structures are shown in Figures S1–S3 in the Supporting Information. To simplify the analysis of the obtained results, each structure is named by the kind of “Nanotube substituent _ cathinone or its derivative code _ specific intermolecular interactions”. In order to reduce the computational power and to avoid the influence of intramolecular interactions between CNT substituents occurring in real multi-walled nanotubes (MWCNTs), a simplified model of a single-walled zigzag nanotube (5,0) SWCNT with one substituent was used in this work. The nanotube with a carboxyl substituent is represented by the abbreviation “COO” for the deprotonated and “COOH” for the protonated functional group. Similarly, a hydroxylated model is labelled using the abbreviation “OH”. The structures of cathinone and its derivatives with their chemical names and the attached letter code A–D are shown in Figure 1.
Cathinone was chosen as the primary structure of the studied drug groups. The other three cathinones were chosen to compare the influence of their structural modifications on the type and energy of intermolecular interactions with the carbon nanotube. Since the pKa of the cathinones’ amine end is in the range of 8–10 [111], the cationic form of these substances will dominate in both neutral and acidic environments. It is reported that only S-cathinone is synthesised by C. edulis and exhibits psychotropic and cytotoxic properties [37,48]. For this reason, its R-configuration was not considered in this work. In the case of synthetic cathinones, there are few data on the R/S-configuration influence on their activity [51,53,112,113]. Despite this, the main goal of the work was to determine the stability of potential DDS carbon nanotube–cathinone complexes in an environment resembling healthy and cancer cells and the contribution of CNT substituents and different cathinone modifications to the interaction energy. In this case, R-configurations of cathinone derivatives were considered. Further experimental determination of the cytostatic properties of cathinones in a free form and in the DDS complex will help to determine the most efficient derivative and its configuration. For a more accurate analysis of intermolecular interactions in nanotube–cathinone complexes, the total interaction energies with correction for the basis set superposition error (BSSE) were considered. EBSSE values are shown in red in the figure of each structure (see Figures S1–S3).

3.1. The Impact of Environment Polarity and SWCNT-Model Length on the Structure and Intermolecular Interactions Energies in the Complex

The first factor analysed in this work is the effect of the environment polarity on the structure and the total interaction energy values in nanotube–cathinone complexes. For this purpose, two media with significantly different dielectric constants ε were selected—a non-polar gas phase (ε = 1) and water (ε = 78.4) using a PCM. Hydrogen bonds in the gas phase and solution have different dynamics depending on the structural features of the proton donor and acceptor molecules. Therefore, it was difficult to determine which position of hydrogen in the CNT–cathinone complexes will correspond to the equilibrium structure. To solve this problem, scan calculations were performed for model complexes—protonated/deprotonated formic acid and methylamine cation. The reaction path of the bridged hydrogen was studied in the gas phase, chloroform, and water using PCMs to track the effect of a gradual increase in the medium polarity on the proton movement. The proton transfer energy profile analysis has demonstrated reliability in predicting hydrogen bond geometric parameters and energies in other molecular systems, supported by experimental data [114,115,116,117]. The proton transfer from the -NH3+ in three possible directions is considered as follows: to the carbonyl oxygen of the protonated carboxyl group, to the hydroxyl oxygen of the protonated carboxyl group, and to the oxygen of the deprotonated carboxyl group. Since the hydroxyl groups of CNTs are significantly more resistant to deprotonation than the carboxyl groups [118,119], the proton transfer in this case was not analysed. Figure 2 shows the dependence of the dimer energy on the N-H interatomic distance in all analysed models in vacuum and solution. For better analyses, each energy profile is presented separately in Figures S4–S6 in SI. As can be seen, the proton transfer from nitrogen to oxygen in both the carbonyl and hydroxyl fragments of the protonated carboxyl group is not energetically favoured (the energy barrier is about 25 kcal/mol in all environments for N-H··O=C-OH models and about 30–40 kcal/mol for N-H··O(H)-C=O models). In complexes with a deprotonated carboxyl group (Figure 2G–I), the proton transfer barrier decreases with an increase in the polarity of the medium from about 10 to about 1 kcal/mol. Because the energy barrier is very small, it is expected that in a real polar physiological environment, a rapid proton transfer occurs between the two minimum energy positions (Figure 2I). Consequently, it is expected that in the equilibrium structure the N-H distance will be the average of the two energy minima.
In the case of cathinone-nanotube complexes, unconstrained geometry optimisation was performed. In Figure 3, the structures of COO_A_NH nanotube–cathinone complexes optimised in vacuum (Figure 3A) and water using a PCM (Figure 3B) are shown. As can be seen from Figure 3A, in the gas phase, a transfer of a hydrogen atom from cationic to anionic form is observed, rather than the expected hydrogen bond formation (according to the previous energy profiles in Figure 2G–I). It can be concluded that the lack of solvent significantly worsens the prediction of the structure of complexes with ionised components (models in simplified neutral environment of healthy tissue). Similar shortcomings of the hydrogen bond DFT predictions in vacuum have also been noted for small clusters of ionic liquids [120,121,122]. A similar artefact is also observed for the cathinone–CNT complex in water using PCM (Figure 3B). It is worth noting that the medium polarisation only slightly improves the prediction of hydrogen bonds (the O··H interatomic distance in vacuum was 1.0004 Å, and in water—1.0018 Å, see Figure 3).
In the case of interactions between the cationic form of cathinones and the neutral form of SWCNT-COOH, as a model in a simplified acidic environment of neoplasms, the situation was similar. As can be seen from Figure 4A, the transfer of a hydrogen atom from S-cathinone to O=C of the CNT carboxyl group occurred in the gas phase. In the case of this complex in water using a PCM (Figure 4B), the formation of two hydrogen bonds with partial delocalization of the hydrogen atom between the amine group of the cathinone and the carbonyl group of SWCNT-COOH was observed. The detachment of the proton to CNT hydroxyl oxygen was not observed in the complexes with SWCNT-OH, both in vacuum and in water (Figure 5).
The above-mentioned problems in a prediction of the complexes structure are caused by a significant simplification of the solvent effect using the PCM, which is unable to predict specific interactions. On the other hand, using the discrete solvent molecules in the first hydration sphere is very computationally demanding. To improve the prediction with minimal calculation efforts, we used only one or two water molecules placed close to the sites of unwanted proton transfer. This simplified approach to providing the first hydration sphere was presented as effective in the modelling of specific interactions—the breaking of the C-P bond in an acidic environment [123]. As can be seen from Figure 6, predicting complexes of SWCNT-COO or SWCNT-COOH with the discrete water molecule addition in the PCM leads to the formation of the non-covalent complexes of realistic geometry (according to energy profiles in Figure 2). It is worth noting that the addition of a water molecule to complexes with SWCNT-OH does not introduce significant changes in these complexes’ geometric parameters (see Figure 7).
As can be seen, the partial inclusion of the first hydration sphere plays a key role in the prediction of intermolecular H-bonds in the SWCNT-COO–cathinone and SWCNT-COOH–cathinone complexes. In the SWCNT-OH–cathinone complexes, such a tendency was not observed. Such differences in the discrete water molecules effects on interactions with -OH and -COO/COOH could be explained by the presence of the cathinones amine group in the cationic form. Its higher reactivity compared to the neutral one could lead to a tendency to form hydrogen bonds with the additional donation of a hydrogen atom to a more electronegative oxygen. The oxygen atom in -C=O of the -COOH group and the oxygen atoms of the -COO group are more electronegative compared to the hydroxyl group. Therefore, in the SWCNT-OH models, a significantly lower ability of the oxygen atom to form H-bonds is observed, and the transfer of the hydrogen atom did not occur during modelling. Additionally, when the -OH substituent is an H-bond donor, proton abstraction does not occur due to the greater chemical stability of this group compared to the carboxyl substituent. Addition of the discrete water molecules near a -COOH/COO oxygen atom with the formation of the additional H-bond leads to the partial shift in electron density toward the water. As a consequence, the water molecules block the hydrogen transfer in CNT–cathinone interactions. It can also be assumed that in real systems, solvent molecules significantly affect the type and energy of the formed intermolecular interactions and, as a consequence, the stability of the considered complexes in a medium with different polarity and pH values.
Since this work is the first step in determining the stability of potential DDS complexes under different conditions, the simplified effect of the environment polarity was considered. In the future, both the effect of discrete solvent molecules on the type and strength of the bonds formed, and the dynamics of complex formation and degradation in a medium with different polarity and pH should be studied in more detail.
The inclusion of one (or two) discrete water molecules significantly influenced hydrogen bonds, while non-polar interactions remained largely unaffected. In the case of H-π and π-π interactions, the introduction of both the PCM and its addition by discrete solvent molecules did not significantly affect their interatomic distances (see Figure 5, Figure 6 and Figure 7). This can be explained by the non-polar nature of these interactions, and, as consequence, the small impact of environment polarity. It is worth noting that these non-covalent bonds additionally stabilise the complex structure.
Another important aspect in the first step determining cathinone–CNT complexes’ stability is the choice of relatively small CNT model. To determine the optimal size of SWCNTs, the interactions of S-cathinone with (5, 0) zigzag SWCNT-OH built with 1, 2, or 3 “bamboo” units [100,101,102,103,104,105] were analysed. Full optimisation of the complexes was performed in water using the PCM. The effect of one discrete water molecule addition to the first hydration sphere on the complexes geometries and interaction energies prediction was analysed. As can be seen from Figure 8 and Figure 9, reducing the model to 1 “bamboo” unit will not allow us to predict all possible interactions of cathinone with the SWCNT wall. Increasing the model to 3 “bamboo” units only slightly changes the complex structure. In addition, it can be seen from Figure 8 and Figure 9 that the structural parameters of the complexes varied insignificantly upon an addition of the discrete water molecule. It can be seen from Table 1 that the interaction energies in the complexes of S-cathinone with 1–3 “bamboo” units SWCNT-OH, with and without one water molecule, varied insignificantly. This difference could be explained by the accidental compensation of the calculation errors and some small deviations between the non-covalent interaction distances. Therefore, using the model with 2 “bamboo” unit allows us to obtain results with acceptable accuracy and calculation time.

3.2. Effect of the CNT Substituent Type and Cathinone Structural Modifications on the Intermolecular Interaction Energy Values

Carbon nanotubes are massive and chemically stable hydrophobic ordered structures. However, under the influence of concentrated and oxidising acids, they are functionalized with oxygen-containing substituents, mainly with hydroxyl and carboxyl groups. Functionalization occurs mainly at the ends, and partially on the outer surface of the nanotube. CNTs’ potential applications are promising [82,118,119,124]. Since this work is intended to be a first-step study of pH and CNT functionalization effects on the type of intermolecular interactions and the complexes’ stability, two models with single -COOH or -OH group were considered. A nanotube with a narrow diameter was chosen to avoid the synergistic effect of the substituent and the penetration of cathinone into the CNT. In future works, the effect of the substituent should be supplemented by the influence of several functional groups of the same and different type, as well as the possibility of drug penetration into the CNT.
In Table 2, the BSSE-corrected interaction energies and selected intermolecular distances of SWCNT-OH–cathinones, SWCNT-COO–cathinones, and SWCNT-COOH–cathinones are gathered.
It is worth noting that for both protonated and deprotonated carboxyl groups, the energy of CNT–cathinone complexes was higher than for hydroxylated SWCNTs for the majority of complexes. As can be seen from Table 2, the SWCNT-OH complexes’ EBSSE values were about 3–11 kcal/mol. The most stable were the “CO”-type complexes. In each of them, one hydrogen bond was formed, where the donor was the hydroxyl substituent of the CNT, and the acceptor was the carbonyl group of cathinones. In “CO”-type complexes, a number of interactions of the π-type were also observed. It is known from the literature that these interactions with low-polarity groups and benzene rings are characterised by lower energy than typical H-bonds [107,125]. However, as can be seen from the OH_C_π complex, where only three interactions of the H-π and π-π types were observed, the complex total interaction energy is about 9 kcal/mol (see Table 2 and Figure S1(C_6)). Therefore, the H-bonds and π-type interactions play an equal role in stabilising the SWCNT-OH–cathinone complexes. A significant contribution of low-polarity π interactions has also been observed in a number of biological macromolecular systems [126,127,128]. It is worth noting that the hydrogen bonds with the hydroxyl substituent as a donor were stronger than H-bonds with the -OH oxygen as an acceptor. The interaction energies of the OH_A_NH and OH_C_NH complexes (EBSSE approx. 6 kcal/mol for both) with one hydrogen bond of the CNT-O··H-N type and a number of the π-type interactions were significantly lower than for the complexes with the CNT-O-H··O=C type hydrogen bond (EBSSE approx. 11 kcal/mol, see Table 2). This can be explained by the lower electronegativity of the oxygen atom in the hydroxyl group in contrast to the carbonyl group. As a consequence, the lower ability of -OH to accept a proton is observed, which is shown in the elongation of the hydrogen bond and its weakening (see Table 2 and Figure S1(A_2,C_3)). In addition to hydrogen bonds with the -OH substituent, H-bonds between cathinones carbonyl oxygen and hydrogen atoms at the ends of the nanotube were also observed. It is worth noting that, partly due to the steric blockade by the side methyl group in cathinones, the corresponding H-bonds’ lengths were 3.1801 Å in OH_A_NH_π and 2.4568 Å in OH_C_NH_π. In both complexes with the energetically less favourable CNT-O··H-N hydrogen bond, these interactions played an additional stabilising role (see Table 2 and Figure S1(A_3,C_4)). Analysing the effect of cathinones benzene ring halogenation on the ability to form non-covalent interactions with SWCNT-OH, its small contribution to the complex stabilisation should be noticed. As can be seen for the p-Cl cathinone B, the chlorine atom did not form non-covalent interactions with either the -OH substituent or the terminal nanotube hydrogens. In the case of fluorine, the ability to form hydrogen bonds with the -OH substituent was noted. As can be seen from the OH_C_F complex (see Figure S1), the CNT-O-H··F bond was characterised by a longer length (1.8392 Å) and lower energy (approx. 3 kcal/mol) compared to the H-bonds of the CNT-O-H··O=C type. An explanation for such a low energy may be due to low ability of the fluoride substituent in a specific chemical environment to form intermolecular hydrogen bonds. This effect was reported in theoretical studies of 5-fluorouracil hydration [107,129].
Analysing the interactions of cathinones with SWCNT-COO (a model of a nanotube in neutral pH of healthy tissue), it is worth paying attention to Table 2 and Figure S2. It seems that the key role in stabilising these complexes is played by charge-assisted hydrogen bonds -COO with hydrogen at the N+-end of cathinones. As can be seen for the COO_B_NH_W and COO_C_NH_W complexes (Figure S2(B_2,C_1)), where one H-bond of the -C=O··H-N+ type was observed, the stabilisation energies were about 19 and 20 kcal/mol, respectively. The second most significant were the π-type interactions. In the case of COO_A_NH_π_W and COO_A_NH_W complexes (Figure S2(A_2,A_3)), the appearance of one additional bond of the -CNT-C(π)··H-N or -CNT-C-H··π type increased the complexes stabilisation energy by about 3 kcal/mol, compared to COO_B_NH_W and COO_C_NH_W. In addition to the canonical H-bonds with the -COO substituent, bifurcated hydrogen bonds were also observed. As can be seen from Figure S2(D_2), bifurcated H-bonds were formed in the COO_D_NH_W2 complex. Their appearance could be explained by the structural modification of cathinone D, where a propyl side group is present opposite the pyrrolidine ring. As a result, two hydrogen atoms of these substituents were close to each other and formed bifurcated H-bonds with one oxygen of -COO. At the same time, one canonical H-bond of considerable length (2.4678 Å) was formed by a hydrogen atom from the pyrrolidine ring with the second oxygen of -COO. As a result, the complex was stabilised by three hydrogen bonds, but the canonical H-bond was long due to the steric effect of pyrrolidine, and the remaining two were bifurcated. This led to a decrease in the complex total interaction energy to about 17 kcal/mol. It is also worth noting that hydrogen atoms of the cathinones’ low-polarity benzene ring, as well as aliphatic substituents, also formed H-bonds with -COO. In addition, similar H-bonds were formed between the cathinones carbonyl oxygen and the nanotubes’ aromatic hydrogen atoms. As can be seen from Figure S2(A_1,C_2,C_3), these interactions weakly stabilised the SWCNT-COO–cathinone complexes. In the COO_A_CO-CH complex, two H-bonds were formed between two hydrogen atoms of the cathinone A benzene ring and two -COO oxygens, one -CNT-C-H··O=C- bond, and two -CNT-C-H··π bonds. All non-covalent bonds were fairly long, and their total interaction energy was low (approx. 7 kcal/mol). Similar interaction energy and non-covalent bond lengths could be seen in case of the COO_C_π complex. In the COO_C_π2_W2 complex, -COO interactions with hydrogens of cathinone C aliphatic substituents were also formed. As can be seen from Table 2 and Figure S2(C_3), the complex total interaction energy was about 4 kcal/mol higher compared to COO_A_CO_CH and COO_C_π complexes. This could be due to the overall contribution of five non-covalent interactions in COO_C_π2_W2 compared to three interactions in COO_C_π, as well as by the higher polarity of some functional groups contributing to non-covalent interactions in COO_C_π2_W2, compared to COO_A_CO_CH. The synergistic effect of interaction energy weakening by bifurcated H-bonds with low-polar functional groups could be seen in the COO_B_CO-CH complex. As can be seen from Figure S2(B_1), four bifurcated H-bonds were formed in the complex, which led to a low value of interaction energy—about 6 kcal/mol. Another type of hydrogen bonds with low-polarity groups was observed for the complex COO_D_COC_W. It was formed between a nanotube terminal hydrogen atom with the cathinone D dioxolane oxygen. As can be seen from Figure S2(D_1), a polarised but longer (2.3822 Å) H-bond between the -COO and the dioxolane hydrogen and an interaction of the -CNT-C-H··O=C type were also formed in the system. Consequently, the complex also had a fairly low interaction energy (about 9 kcal/mol, see Table 2). Analysing the effect of cathinone halogenation on the type and energy of interactions in the SWCNT-COO–cathinone complexes, it is worth noting that the fluorine did not form hydrogen bonds with the nanotube terminal hydrogen atoms. On the other hand, the chlorine atom in the COO_B_π complex was an acceptor of two bifurcated hydrogen bonds with the nanotube terminal hydrogen atoms (see Figure S2(B_3) and Table 2). Even so, these H-bonds were long and appeared together with two canonical hydrogen bonds with -COO and one interaction of the -CNT-C-H··π type, and they weakly stabilised the complex (EBSSE about 9 kcal/mol).
Finally, SWCNT-COOH complexes with cathinones were studied as models in neoplasms acidic pH conditions. It is apparent form Table 2 and Figure S3 that the highest contribution to the stabilisation of the complexes was made by canonical strong hydrogen bonds of the -CNT-C=O··H-N and -CNT-O-H··O=C types. In the complexes COOH_A_Dimer_W, COOH_B_Dimer_W, and COOH_C_Dimer_W (Figure S3(A_1,B_2,C_1)), one interaction of both types is visible, so these complexes are characterised by the highest interaction energy values among the complexes with SWCNT-COOH—15–17 kcal/mol. The next most important non-covalent interactions were the π-type ones. As can be seen from Figure S3(D_2), in the COOH_D_Dimer_W complex, two canonical H-bonds with -COOH were formed. However, due to the larger and more complex structure of cathinone D, its N-end was sterically less accessible to interactions with -COOH than cathinones A–C. Therefore, an elongation and weakening of H-bonds was observed. On the other hand, the cathinone propyl side chain formed two H-π interactions with the CNT sidewall. As a result, the weakened H-bridges were compensated by π-type interactions, and the complex had a high interaction energy of about 16 kcal/mol. A similar effect of stabilisation by the π-type interactions was also observed for the complexes with a single canonical hydrogen bond. As can be seen from Figure S3(A_2,B_3,C_3), in COOH_A_NH_W, COOH_B_NH_W and COOH_C_NH_W complexes, a single canonical H-bond of the -CNT-C=O··H-N type was formed. The complexes were additionally stabilised by one or two H-π-type interactions. Consequently, the complexes energies were close to the EBSSE of the complexes with two conventional H-bonds—about 13–16 kcal/mol. It can also be noted that the -COOH substituent, in addition to classical polar H-bonds, participated in a number of the H-bridges with low-polar functional groups. Thus, in the COOH_A_π_W complex (Figure S3(A_3), Table 2), the carbonyl oxygen was an acceptor of hydrogen atom from the cathinone A benzene ring. In the COOH_C_π2 complex (Figure S3(C_4), Table 2), the same carbonyl oxygen atom was an acceptor of a hydrogen atom from the cathinone C aliphatic side chain. The hydroxyl fragment of -COOH also participated in the H-bonds with low-polar groups. In the COOH_D_COC_W complex (Figure S3(D_1), Table 2), the hydroxyl group was an H-bond donor to the dioxolane oxygen atom of the cathinone D. On the other hand, the hydroxyl oxygen atom was an acceptor of the H-bond with the cathinone D benzene hydrogen in the COOH_D_π complex (Figure S3(D_3)). All the mentioned complexes with H-bridges formed by the low-polar functional groups were additionally stabilised by the π-type interactions. Due to the lower energy of all non-covalent interactions, compared to canonical polar H-bonds, the complexes’ total interaction energy was not very high (about 7–12 kcal/mol, see Table 2). Analysing the effect of cathinone halogenation on the intermolecular interaction types and energies in the SWCNT-COOH–cathinone complexes, it can be noted that the fluorine and chlorine atoms were acceptors of H-bonds with the -COOH substituent. As can be seen for the COOH_B_CI and COOH_C_F_CO complexes (Figure S3(B_1,C_2)), the interaction lengths were longer than 2 Å, and their contribution to the complexes’ stabilisation was small. As can be seen in the COOH_C_F_CO complex, a single H-bond of the -CNT-C-H··O=C type was additionally formed. The same type of H-bond and several π-type interactions were formed in the COOH_B_CI complex. The total EBSSE of both complexes was quite low (about 6 kcal/mol for the COOH_C_F_CO and about 8 kcal/mol for the COOH_B_CI).
It can be summarised that both SWCNT functionalization and cathinone structure modification significantly contribute to the complexes’ stability. It can be noted that the SWCNT-OH complexes were characterised by a lower EBSSE values compared to most of the SWCNT-COO and SWCNT-COOH complexes. In addition, in the SWCNT-OH complexes, the hydroxyl substituent was capable of forming a smaller number of H-interactions compared to -COO/-COOH. In the case of cathinones, the key role was played by the modifications of the N-end. The spatial accessibility of H-N played a key role in the formation of the both H-bonds and π-type interactions. In addition, the modification of the cathinones side aliphatic chain played a significant role in its location relative to the side wall of the CNT and, as a consequence, in the number and strength of the π-type interactions in the complex. The halogenation of the cathinones played a role in stabilising the complexes with SWCNTs, although the formed H-bonds involving fluorine and chlorine atoms were weak and occurred only in the case of some favourable positions of cathinone over the CNT surface.

3.3. The Influence of pH on the Complex Stability

The process of protonation–deprotonation in the environment of different pH is dynamic and occurs chaotically and quickly. Therefore, in each environment, one should expect the presence of the protonated and deprotonated forms of each pH-sensitive functional group. One should also expect the dominance of the negative ion of the acidic group at a pH higher than the pKa value. According to experimental data, the pKa of carboxyl groups in CNT is about 7, and that of hydroxyl groups is about 10 [130]. Therefore, in the neutral environment of healthy tissue, one should expect the dominance of deprotonated -COO and protonated -OH. In the acidic pH of cancer cells, one should expect the protonation of both functional groups.
Since the deprotonation of -OH occurs to a small extent both at neutral and acidic pH, the interaction energy of this functional group of CNT with cathinones will remain virtually the same under the analysed conditions. As mentioned earlier, the interaction energies in the CNT-OH–cathinone complexes were lower than those of both CNT-COOH–cathinone and CNT-COO–cathinone. Deprotonated hydroxyl groups are expected to contribute minimally to the overall complex stability. As a result, the decisive contribution to the complex stability will be made by interactions with the carboxyl group, as it is more sensitive to changes in the physiological pH in cancer cells. Analysing the total EBSSE of -COO/COOH complexes, it should be noted that it significantly differs, depending on the pH value. It is worth paying attention to Table 3. It presents the EBSSE values for “NH_W”-type complexes. Each of them is stabilised by one strong H-bond, which in the case of -COO is additionally strengthened by the negative charge of the carboxylate substituent. In the case of -COOH and COO_A_NH_W complexes, a stabilising effect of π-type interactions occurs too. The structures of “A_NH_W”, “B_NH_W”, and “C_NH_W” with SWCNT-COO and SWCNT-COOH are also presented in Figure 10. The energies of all obtained complexes at different pH are presented in Table S1 in SI.
As can be seen from Table 3, all complexes with -COO (model in the healthy tissues) show higher interaction energy and are therefore more stable in comparison to complexes with -COOH. Therefore, in a real system, one should expect the intermolecular hydrogen bond to break as result of the protonation of the oxygen atom participating in the H-bond and the complex dissociation. It corresponds to the pH value decrease in the neoplasms’ medium. If protonation occurs on the oxygen atom not participating in the H-bond, one should also expect a significant weakening of the complex’s stability (see Table 3) and its gradual degradation. Analysing other complexes with the -COO/COOH motif, it is worth noting that a high dependence of the interaction energy on the medium pH value was obtained only for classical H-bonds (see Table 2). The EBSSE of complexes with H-bridges with low-polar groups, H-bonds with halogens, and the π-type interaction dominance varied only slightly in different pHs. Therefore, in the case of the experimental design of CNT–cathinone DDS complexes, nanotubes functionalized with both -OH and -COOH or only -COOH substituents could be recommended. Due to the high pKa value and, therefore, significant resistance to deprotonation in healthy and cancerous tissues, hydroxyl substituents will additionally stabilise the complex during transport to the molecular target and slow down the rate of the complex degradation to an optimal value near the neoplasm. Carboxyl substituents will significantly stabilise the complex during transport to the molecular target, and they will serve as a trigger for drug release near the neoplasm surface. It could be supposed that standard functionalization with polar -COOH/OH substituents will be sufficient to ensure the stability and controlled release of the drug from the carrier. This assumption is based on the relatively high EBSSE values in complexes with conventional H-bonds and moderate EBSSE values in complexes with the bifurcated and low-polarity H-bonds for CNT with one substituent. Even so, this explanation requires further in-depth theoretical and experimental confirmation.

4. Conclusions

As a result of systematic theoretical studies, the first data on the interaction of cathinone and its three derivatives with simplified models of hydroxylated and carboxylated nanotubes in the context of new potential anticancer DDS preparation were obtained. The effect of the CNT substituent, as well as the structural modification of cathinones on the type and energies of intermolecular interactions in the complex was analysed. It was noted that both structural features of CNT and cathinones are equally important in the complexes’ formation and stabilisation. It was observed that in the SWCNT-OH complexes, a smaller number of non-covalent intermolecular interactions are formed compared to the SWCNT-COO/COOH complexes. The stabilisation energies of the SWCNT-OH complexes were lower compared to most of the SWCNT-COO/COOH complexes. Therefore, the hydroxyl substituents in real systems will stabilise the complex less strongly during transport to molecular targets. On the other hand, due to the high -OH pKa value, its very low ability to deprotonate should be expected both at neutral pH healthy tissue and at acidic pH neoplasms. Therefore, the functionalization of CNT with -OH substituents is recommended due to the possibility of the additional stabilisation of the complex during transport and the slowing down of the drug release near the molecular target. Carboxyl substituents will stabilise the complex significantly more during transport. Their ability to protonate during a pH decrease in the neoplasms will serve as the start of the complex’s degradation and controlled drug release. Therefore, it is recommended to consider the possibility of using CNT functionalized with either carboxyl or carboxyl and hydroxyl substituents, in the future, for more detailed theoretical and experimental studies. The obtained theoretical data show that the H-bonds with functional groups of different polarity and π-type interactions will dominate in the cathinone–CNT complexes. In the case of cathinone halogenation, H-bonds with halogen atoms can also be expected, but they will be significantly weaker than classical H-bridges. Based on the obtained data, it could be assumed that the classically functionalized CNT will provide more effective transport of cathinones compared to traditional drug injection. It is suspected that the release of the drug near the molecular target will allow for the more effective use of its cytostatic potential. It is also worth mentioning that the introduction of cathinones in complexes with the CNT will potentially decrease side cytotoxic effects on healthy tissues, as well as the drugs’ psychotropic activity.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/app15168892/s1, Figure S1. Structures of SWCNT-OH model with cathinones A–D (labelling from Figure 1 in manuscript) complexes. Dash lines indicate intermolecular interactions, and their lengths (in Å) are shown in purple. The BSSE-corrected total interaction energies (in kcal/mol) are shown in red. Figure S2. Structures of SWCNT-COO- model with cathinones A-D (labelling from Figure 1 in manuscript) complexes. Dash lines indicate intermolecular interactions, and their lengths (in Å) are shown in purple. The BSSE-corrected total interaction energies (in kcal/mol) are shown in red. Figure S3. Structures of SWCNT-COOH model with cathinones A–D (labelling from Figure 1 in manuscript) complexes. Dash lines indicate intermolecular interactions, and their lengths (in Å) are shown in purple. The BSSE-corrected total interaction energies (in kcal/mol) are shown in red. Figure S4. Potential energy curves of model dimers with varying N-H interatomic distance with (A and B) protonated and (C) deprotonated formic acid in the gas phase. Figure S5. Potential energy curves of model dimers with varying N-H interatomic distance with (A and B) protonated and (C) deprotonated formic acid in chloroform using a PCM. Figure S6. Potential energy curves of model dimers with varying N-H interatomic distance with (A and B) protonated and (C) deprotonated formic acid in water using a PCM. Table S1. BSSE-corrected interaction energies (kcal/mol) in complexes of S-cathinone and its derivatives (A–D) with and without discrete water molecule(s) and (5.0) zigzag SWCNT with two “bamboo” units. Label “W” stands for discrete water molecule(s) in the system.

Author Contributions

N.M.: conceptualization, methodology, investigation, data analyses, visualisation, and writing—original draft. T.K.: conceptualization, methodology, writing—review and editing, and supervision. O.R.: writing—review and editing, and supervision. All authors have read and agreed to the published version of the manuscript.

Funding

N.M. and T.K. were partly supported by the University of Opole.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are contained within the article and Supplementary Materials.

Acknowledgments

Created using resources provided by the Wroclaw Centre for Networking and Supercomputing (http://wcss.pl). Grant no. hpc-titanium-1721124296. The authors thank Piotr Lodowski for participating in the results’ discussion and the useful recommendations. The authors are grateful for the three reviewers’ constructive criticism and useful suggestions, which helped to prepare this work in its best possible form.

Conflicts of Interest

The authors declare no competing interests.

References

  1. Casolino, R.; Sullivan, R.; Jobanputra, K.; Abdel-Wahab, M.; Grbic, M.; Hammad, N.; Kutluk, T.; Melnitchouk, N.; Mueller, A.; Ortiz, R.; et al. Integrating Cancer into Crisis: A Global Vision for Action from WHO and Partners. Lancet Oncol. 2025, 26, e55–e66. [Google Scholar] [CrossRef]
  2. Bray, F.; Laversanne, M.; Sung, H.; Ferlay, J.; Siegel, R.L.; Soerjomataram, I.; Jemal, A. Global Cancer Statistics 2022: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J. Clin. 2024, 74, 229–263. [Google Scholar] [CrossRef]
  3. Yan, M.; Wu, S.; Wang, Y.; Liang, M.; Wang, M.; Hu, W.; Yu, G.; Mao, Z.; Huang, F.; Zhou, J. Recent Progress of Supramolecular Chemotherapy Based on Host–Guest Interactions. Adv. Mater. 2024, 36, 2304249. [Google Scholar] [CrossRef] [PubMed]
  4. Li, J.; Du, Q.; Wan, J.; Yu, D.-G.; Tan, F.; Yang, X. Improved Synergistic Anticancer Action of Quercetin and Tamoxifen Citrate Supported by an Electrospun Complex Nanostructure. Mater. Des. 2024, 238, 112657. [Google Scholar] [CrossRef]
  5. Sikov, W.M.; Berry, D.A.; Perou, C.M.; Singh, B.; Cirrincione, C.T.; Tolaney, S.M.; Kuzma, C.S.; Pluard, T.J.; Somlo, G.; Port, E.R.; et al. Impact of the Addition of Carboplatin and/or Bevacizumab to Neoadjuvant Once-per-Week Paclitaxel Followed by Dose-Dense Doxorubicin and Cyclophosphamide on Pathologic Complete Response Rates in Stage II to III Triple-Negative Breast Cancer: CALGB 40603 (Alliance). J. Clin. Oncol. 2015, 33, 13–21. [Google Scholar] [CrossRef]
  6. Loibl, S.; O’Shaughnessy, J.; Untch, M.; Sikov, W.M.; Rugo, H.S.; McKee, M.D.; Huober, J.; Golshan, M.; von Minckwitz, G.; Maag, D.; et al. Addition of the PARP Inhibitor Veliparib plus Carboplatin or Carboplatin Alone to Standard Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer (BrighTNess): A Randomised, Phase 3 Trial. Lancet Oncol. 2018, 19, 497–509. [Google Scholar] [CrossRef]
  7. Lencioni, R.; Llovet, J.M.; Han, G.; Tak, W.Y.; Yang, J.; Guglielmi, A.; Paik, S.W.; Reig, M.; Kim, D.Y.; Chau, G.-Y.; et al. Sorafenib or Placebo plus TACE with Doxorubicin-Eluting Beads for Intermediate Stage HCC: The SPACE Trial. J. Hepatol. 2016, 64, 1090–1098. [Google Scholar] [CrossRef]
  8. Eryilmaz, I.E.; Colakoglu Bergel, C.; Arioz, B.; Huriyet, N.; Cecener, G.; Egeli, U. Luteolin Induces Oxidative Stress and Apoptosis via Dysregulating the Cytoprotective Nrf2-Keap1-Cul3 Redox Signaling in Metastatic Castration-Resistant Prostate Cancer Cells. Mol. Biol. Rep. 2024, 52, 65. [Google Scholar] [CrossRef]
  9. Jędrzejewski, T.; Sobocińska, J.; Maciejewski, B.; Spisz, P.; Walczak-Skierska, J.; Pomastowski, P.; Wrotek, S. In Vitro Treatment of Triple-Negative Breast Cancer Cells with an Extract from the Coriolus Versicolor Mushroom Changes Macrophage Properties Related to Tumourigenesis. Immunol. Res. 2024, 73, 14. [Google Scholar] [CrossRef]
  10. Chunarkar-Patil, P.; Kaleem, M.; Mishra, R.; Ray, S.; Ahmad, A.; Verma, D.; Bhayye, S.; Dubey, R.; Singh, H.N.; Kumar, S. Anticancer Drug Discovery Based on Natural Products: From Computational Approaches to Clinical Studies. Biomedicines 2024, 12, 201. [Google Scholar] [CrossRef]
  11. Yadav, A.K.; Maharjan Shrestha, R.; Yadav, P.N. Anticancer Mechanism of Coumarin-Based Derivatives. Eur. J. Med. Chem. 2024, 267, 116179. [Google Scholar] [CrossRef]
  12. Wang, R.; Wang, C.; Lu, L.; Yuan, F.; He, F. Baicalin and Baicalein in Modulating Tumor Microenvironment for Cancer Treatment: A Comprehensive Review with Future Perspectives. Pharmacol. Res. 2024, 199, 107032. [Google Scholar] [CrossRef] [PubMed]
  13. Casini, A.; Pöthig, A. Metals in Cancer Research: Beyond Platinum Metallodrugs. ACS Cent. Sci. 2024, 10, 242–250. [Google Scholar] [CrossRef] [PubMed]
  14. Zahirović, A.; Fetahović, S.; Feizi-Dehnayebi, M.; Višnjevac, A.; Bešta-Gajević, R.; Kozarić, A.; Martić, L.; Topčagić, A.; Roca, S. Dual Antimicrobial-Anticancer Potential, Hydrolysis, and DNA/BSA Binding Affinity of a Novel Water-Soluble Ruthenium-Arene Ethylenediamine Schiff Base (RAES) Organometallic. Spectrochim. Acta Part A Mol. Biomol. Spectrosc. 2024, 318, 124528. [Google Scholar] [CrossRef] [PubMed]
  15. Glorieux, C.; Liu, S.; Trachootham, D.; Huang, P. Targeting ROS in Cancer: Rationale and Strategies. Nat. Rev. Drug Discov. 2024, 23, 583–606. [Google Scholar] [CrossRef]
  16. Galluzzi, L.; Guilbaud, E.; Schmidt, D.; Kroemer, G.; Marincola, F.M. Targeting Immunogenic Cell Stress and Death for Cancer Therapy. Nat. Rev. Drug Discov. 2024, 23, 445–460. [Google Scholar] [CrossRef]
  17. Zhou, Q.; Meng, Y.; Li, D.; Yao, L.; Le, J.; Liu, Y.; Sun, Y.; Zeng, F.; Chen, X.; Deng, G. Ferroptosis in Cancer: From Molecular Mechanisms to Therapeutic Strategies. Sig. Transduct. Target. Ther. 2024, 9, 55. [Google Scholar] [CrossRef]
  18. Kim, S.E.; Zhang, L.; Ma, K.; Riegman, M.; Chen, F.; Ingold, I.; Conrad, M.; Turker, M.Z.; Gao, M.; Jiang, X.; et al. Ultrasmall Nanoparticles Induce Ferroptosis in Nutrient-Deprived Cancer Cells and Suppress Tumour Growth. Nat. Nanotechnol. 2016, 11, 977–985. [Google Scholar] [CrossRef]
  19. Wang, Y.; Chen, Y.; Zhang, J.; Yang, Y.; Fleishman, J.S.; Wang, Y.; Wang, J.; Chen, J.; Li, Y.; Wang, H. Cuproptosis: A Novel Therapeutic Target for Overcoming Cancer Drug Resistance. Drug Resist. Updates 2024, 72, 101018. [Google Scholar] [CrossRef]
  20. Klein, C.; Brinkmann, U.; Reichert, J.M.; Kontermann, R.E. The Present and Future of Bispecific Antibodies for Cancer Therapy. Nat. Rev. Drug Discov. 2024, 23, 301–319. [Google Scholar] [CrossRef]
  21. Lasser, S.A.; Ozbay Kurt, F.G.; Arkhypov, I.; Utikal, J.; Umansky, V. Myeloid-Derived Suppressor Cells in Cancer and Cancer Therapy. Nat. Rev. Clin. Oncol. 2024, 21, 147–164. [Google Scholar] [CrossRef] [PubMed]
  22. Fenis, A.; Demaria, O.; Gauthier, L.; Vivier, E.; Narni-Mancinelli, E. New Immune Cell Engagers for Cancer Immunotherapy. Nat. Rev. Immunol. 2024, 24, 471–486. [Google Scholar] [CrossRef] [PubMed]
  23. Radhakrishnan, R.; Wilkinson, S.T.; D’Souza, D.C. Gone to Pot—A Review of the Association between Cannabis and Psychosis. Front. Psychiatry 2014, 5, 72718. [Google Scholar] [CrossRef] [PubMed]
  24. Munson, A.E.; Harris, L.S.; Friedman, M.A.; Dewey, W.L.; Carchman, R.A. Antineoplastic Activity of Cannabinoids2. JNCI: J. Natl. Cancer Inst. 1975, 55, 597–602. [Google Scholar] [CrossRef]
  25. Barbado, M.V.; Medrano, M.; Caballero-Velázquez, T.; Álvarez-Laderas, I.; Sánchez-Abarca, L.I.; García-Guerrero, E.; Martín-Sánchez, J.; Rosado, I.V.; Piruat, J.I.; Gonzalez-Naranjo, P.; et al. Cannabinoid Derivatives Exert a Potent Anti-Myeloma Activity Both in Vitro and in Vivo. Int. J. Cancer 2017, 140, 674–685. [Google Scholar] [CrossRef]
  26. Notaro, A.; Emanuele, S.; Geraci, F.; D’Anneo, A.; Lauricella, M.; Calvaruso, G.; Giuliano, M. WIN55,212-2-Induced Expression of Mir-29b1 Favours the Suppression of Osteosarcoma Cell Migration in a SPARC-Independent Manner. Int. J. Mol. Sci. 2019, 20, 5235. [Google Scholar] [CrossRef]
  27. Gurley, S.N.; Abidi, A.H.; Allison, P.; Guan, P.; Duntsch, C.; Robertson, J.H.; Kosanke, S.D.; Keir, S.T.; Bigner, D.D.; Elberger, A.J.; et al. Mechanism of Anti-Glioma Activity and in Vivo Efficacy of the Cannabinoid Ligand KM-233. J. Neurooncol. 2012, 110, 163–177. [Google Scholar] [CrossRef]
  28. Greish, K.; Mathur, A.; Al Zahrani, R.; Elkaissi, S.; Al Jishi, M.; Nazzal, O.; Taha, S.; Pittalà, V.; Taurin, S. Synthetic Cannabinoids Nano-Micelles for the Management of Triple Negative Breast Cancer. J. Control Release 2018, 291, 184–195. [Google Scholar] [CrossRef]
  29. Selvi, E.; Lorenzini, S.; Garcia-Gonzalez, E.; Maggio, R.; Lazzerini, P.E.; Capecchi, P.L.; Balistreri, E.; Spreafico, A.; Niccolini, S.; Pompella, G.; et al. Inhibitory Effect of Synthetic Cannabinoids on Cytokine Production in Rheumatoid Fibroblast-like Synoviocytes. Clin. Exp. Rheumatol. 2008, 26, 574. [Google Scholar]
  30. Fichna, J.; Bawa, M.; Thakur, G.A.; Tichkule, R.; Makriyannis, A.; McCafferty, D.-M.; Sharkey, K.A.; Storr, M. Cannabinoids Alleviate Experimentally Induced Intestinal Inflammation by Acting at Central and Peripheral Receptors. PLoS ONE 2014, 9, e109115. [Google Scholar] [CrossRef]
  31. Gui, H.; Liu, X.; Liu, L.-R.; Su, D.-F.; Dai, S.-M. Activation of Cannabinoid Receptor 2 Attenuates Synovitis and Joint Distruction in Collagen-Induced Arthritis. Immunobiology 2015, 220, 817–822. [Google Scholar] [CrossRef]
  32. Tolón, R.M.; Núñez, E.; Pazos, M.R.; Benito, C.; Castillo, A.I.; Martínez-Orgado, J.A.; Romero, J. The Activation of Cannabinoid CB2 Receptors Stimulates in Situ and in Vitro Beta-Amyloid Removal by Human Macrophages. Brain Res. 2009, 1283, 148–154. [Google Scholar] [CrossRef]
  33. Jimenez Del Rio, M.; Velez-Pardo, C. Paraquat Induces Apoptosis in Human Lymphocytes: Protective and Rescue Effects of Glucose, Cannabinoids and Insulin-like Growth Factor-1. Growth Factors 2008, 26, 49–60. [Google Scholar] [CrossRef]
  34. Hu, S.; Sheng, W.S.; Rock, R.B. CB2 Receptor Agonists Protect Human Dopaminergic Neurons against Damage from HIV-1 Gp120. PLoS ONE 2013, 8, e77577. [Google Scholar] [CrossRef] [PubMed]
  35. Idris, A.I.; van ’t Hof, R.J.; Greig, I.R.; Ridge, S.A.; Baker, D.; Ross, R.A.; Ralston, S.H. Regulation of Bone Mass, Bone Loss and Osteoclast Activity by Cannabinoid Receptors. Nat. Med. 2005, 11, 774–779. [Google Scholar] [CrossRef] [PubMed]
  36. Bort, A.; Alvarado-Vazquez, P.A.; Moracho-Vilrriales, C.; Virga, K.G.; Gumina, G.; Romero-Sandoval, A.; Asbill, S. Effects of JWH015 in Cytokine Secretion in Primary Human Keratinocytes and Fibroblasts and Its Suitability for Topical/Transdermal Delivery. Mol. Pain. 2017, 13, 1744806916688220. [Google Scholar] [CrossRef]
  37. Gebissa, E. Khat in the Horn of Africa: Historical Perspectives and Current Trends. J. Ethnopharmacol. 2010, 132, 607–614. [Google Scholar] [CrossRef] [PubMed]
  38. Van Hout, M.C. Kitchen Chemistry: A Scoping Review of the Diversionary Use of Pharmaceuticals for Non-Medicinal Use and Home Production of Drug Solutions. Drug Test. Anal. 2014, 6, 778–787. [Google Scholar] [CrossRef]
  39. Archer, R.P. Fluoromethcathinone, a New Substance of Abuse. Forensic Sci. Int. 2009, 185, 10–20. [Google Scholar] [CrossRef]
  40. Liu, C.; Jia, W.; Li, T.; Hua, Z.; Qian, Z. Identification and Analytical Characterization of Nine Synthetic Cathinone Derivatives N-Ethylhexedrone, 4-Cl-Pentedrone, 4-Cl-α-EAPP, Propylone, N-Ethylnorpentylone, 6-MeO-Bk-MDMA, α-PiHP, 4-Cl-α-PHP, and 4-F-α-PHP. Drug Test. Anal. 2017, 9, 1162–1171. [Google Scholar] [CrossRef]
  41. Kehr, J.; Ichinose, F.; Yoshitake, S.; Goiny, M.; Sievertsson, T.; Nyberg, F.; Yoshitake, T. Mephedrone, Compared with MDMA (Ecstasy) and Amphetamine, Rapidly Increases Both Dopamine and 5-HT Levels in Nucleus Accumbens of Awake Rats. Br. J. Pharmacol. 2011, 164, 1949–1958. [Google Scholar] [CrossRef]
  42. Smith, D.A.; Negus, S.S.; Poklis, J.L.; Blough, B.E.; Banks, M.L. Cocaine-like Discriminative Stimulus Effects of Alpha-Pyrrolidinovalerophenone, Methcathinone and Their 3,4-Methylenedioxy or 4-Methyl Analogs in Rhesus Monkeys. Addict. Biol. 2017, 22, 1169–1178. [Google Scholar] [CrossRef] [PubMed]
  43. Vendrell-Dones, M.O.; Hernandez, E.; Dogruer Erkok, S.; McCord, B. Detection of Synthetic Cathinones in Seized Drugs Using Surface-Enhanced Raman Spectroscopy (SERS). Forensic Chem. 2024, 41, 100613. [Google Scholar] [CrossRef]
  44. Wilkes, S. The Use of Bupropion SR in Cigarette Smoking Cessation. COPD 2008, 3, 45–53. [Google Scholar] [CrossRef] [PubMed]
  45. Fava, M.; Rush, A.J.; Thase, M.E.; Clayton, A.; Stahl, S.M.; Pradko, J.F.; Johnston, J.A. 15 Years of Clinical Experience With Bupropion HCl: From Bupropion to Bupropion SR to Bupropion XL. Prim. Care Companion J. Clin. Psychiatry 2005, 7, 106–113. [Google Scholar] [CrossRef] [PubMed]
  46. Goldberg, J.; Gardos, G.; Cole, J.O. A Controlled Evaluation of Pyrovalerone in Chronically Fatigued Volunteers. Int. Pharmacopsychiatry 2017, 8, 60–69. [Google Scholar] [CrossRef]
  47. Seaton, D.A.; Duncan, L.J.P.; Rose, K.; Scott, A.M. Diethylpropion in the Treatment of “Refractory” Obesity. Br. Med. J. 1961, 1, 1009–1011. [Google Scholar] [CrossRef]
  48. Lu, Y.; Li, Y.; Xiang, M.; Zhou, J.; Chen, J. Khat Promotes Human Breast Cancer MDA-MB-231 Cell Apoptosis via Mitochondria and MAPK-Associated Pathways. Oncol. Lett. 2017, 14, 3947–3952. [Google Scholar] [CrossRef]
  49. Soares, J.; Costa, V.M.; Gaspar, H.; Santos, S.; de Lourdes Bastos, M.; Carvalho, F.; Capela, J.P. Structure-Cytotoxicity Relationship Profile of 13 Synthetic Cathinones in Differentiated Human SH-SY5Y Neuronal Cells. NeuroToxicology 2019, 75, 158–173. [Google Scholar] [CrossRef]
  50. Soares, J.; Costa, V.M.; Gaspar, H.; Santos, S.; Bastos, M.d.L.; Carvalho, F.; Capela, J.P. Adverse Outcome Pathways Induced by 3,4-Dimethylmethcathinone and 4-Methylmethcathinone in Differentiated Human SH-SY5Y Neuronal Cells. Arch. Toxicol. 2020, 94, 2481–2503. [Google Scholar] [CrossRef]
  51. Paškan, M.; Rimpelová, S.; Svobodová Pavlíčková, V.; Spálovská, D.; Setnička, V.; Kuchař, M.; Kohout, M. 4-Isobutylmethcathinone—A Novel Synthetic Cathinone with High In Vitro Cytotoxicity and Strong Receptor Binding Preference of Enantiomers. Pharmaceuticals 2022, 15, 1495. [Google Scholar] [CrossRef]
  52. Matsunaga, T.; Morikawa, Y.; Kamata, K.; Shibata, A.; Miyazono, H.; Sasajima, Y.; Suenami, K.; Sato, K.; Takekoshi, Y.; Endo, S.; et al. α-Pyrrolidinononanophenone Provokes Apoptosis of Neuronal Cells through Alterations in Antioxidant Properties. Toxicology 2017, 386, 93–102. [Google Scholar] [CrossRef]
  53. Silva, B.; Palmeira, A.; Silva, R.; Fernandes, C.; Guedes de Pinho, P.; Remião, F. S-(+)-Pentedrone and R-(+)-Methylone as the Most Oxidative and Cytotoxic Enantiomers to Dopaminergic SH-SY5Y Cells: Role of MRP1 and P-Gp in Cathinones Enantioselectivity. Toxicol. Appl. Pharmacol. 2021, 416, 115442. [Google Scholar] [CrossRef] [PubMed]
  54. Valente, M.J.; Bastos, M.d.L.; Fernandes, E.; Carvalho, F.; Guedes de Pinho, P.; Carvalho, M. Neurotoxicity of β-Keto Amphetamines: Deathly Mechanisms Elicited by Methylone and MDPV in Human Dopaminergic SH-SY5Y Cells. ACS Chem. Neurosci. 2017, 8, 850–859. [Google Scholar] [CrossRef] [PubMed]
  55. Leong, H.S.; Philp, M.; Simone, M.; Witting, P.K.; Fu, S. Synthetic Cathinones Induce Cell Death in Dopaminergic SH-SY5Y Cells via Stimulating Mitochondrial Dysfunction. Int. J. Mol. Sci. 2020, 21, 1370. [Google Scholar] [CrossRef]
  56. Valente, M.J.; Amaral, C.; Correia-da-Silva, G.; Duarte, J.A.; Bastos, M.d.L.; Carvalho, F.; Guedes de Pinho, P.; Carvalho, M. Methylone and MDPV Activate Autophagy in Human Dopaminergic SH-SY5Y Cells: A New Insight into the Context of β-Keto Amphetamines-Related Neurotoxicity. Arch. Toxicol. 2017, 91, 3663–3676. [Google Scholar] [CrossRef] [PubMed]
  57. Morikawa, Y.; Miyazono, H.; Kamase, K.; Suenami, K.; Sasajima, Y.; Sato, K.; Endo, S.; Monguchi, Y.; Takekoshi, Y.; Ikari, A.; et al. Protective Effect of Aldo–Keto Reductase 1B1 Against Neuronal Cell Damage Elicited by 4′-Fluoro-α-Pyrrolidinononanophenone. Neurotox. Res. 2021, 39, 1360–1371. [Google Scholar] [CrossRef]
  58. Morikawa, Y.; Miyazono, H.; Sakai, Y.; Suenami, K.; Sasajima, Y.; Sato, K.; Takekoshi, Y.; Monguchi, Y.; Ikari, A.; Matsunaga, T. 4′-Fluoropyrrolidinononanophenone Elicits Neuronal Cell Apoptosis through Elevating Production of Reactive Oxygen and Nitrogen Species. Forensic Toxicol. 2021, 39, 123–133. [Google Scholar] [CrossRef]
  59. Sakai, Y.; Morikawa, Y.; Nagao, Y.; Hattori, J.; Suenami, K.; Yanase, E.; Takayama, T.; Ikari, A.; Matsunaga, T. 4′-Iodo-α-Pyrrolidinononanophenone Provokes Differentiated SH-SY5Y Cell Apoptosis Through Downregulating Nitric Oxide Production and Bcl-2 Expression. Neurotox. Res. 2022, 40, 1322–1336. [Google Scholar] [CrossRef]
  60. Zawilska, J.B.; Wojcieszak, J. α-Pyrrolidinophenones: A New Wave of Designer Cathinones. Forensic Toxicol. 2017, 35, 201–216. [Google Scholar] [CrossRef]
  61. Wojcieszak, J.; Andrzejczak, D.; Kedzierska, M.; Milowska, K.; Zawilska, J.B. Cytotoxicity of α-Pyrrolidinophenones: An Impact of α-Aliphatic Side-Chain Length and Changes in the Plasma Membrane Fluidity. Neurotox. Res. 2018, 34, 613–626. [Google Scholar] [CrossRef]
  62. Zhou, X.; Bouitbir, J.; Liechti, M.E.; Krähenbühl, S.; Mancuso, R.V. Para-Halogenation of Amphetamine and Methcathinone Increases the Mitochondrial Toxicity in Undifferentiated and Differentiated SH-SY5Y Cells. Int. J. Mol. Sci. 2020, 21, 2841. [Google Scholar] [CrossRef] [PubMed]
  63. Nadal-Gratacós, N.; Ríos-Rodríguez, E.; Pubill, D.; Batllori, X.; Camarasa, J.; Escubedo, E.; Berzosa, X.; López-Arnau, R. Structure–Activity Relationship of N-Ethyl-Hexedrone Analogues: Role of the α-Carbon Side-Chain Length in the Mechanism of Action, Cytotoxicity, and Behavioral Effects in Mice. ACS Chem. Neurosci. 2023, 14, 787–799. [Google Scholar] [CrossRef] [PubMed]
  64. Marszalek-Grabska, M.; Lemieszek, M.K.; Chojnacki, M.; Winiarczyk, S.; Jakubowicz-Gil, J.; Zarzyka, B.; Pawelec, J.; Kotlinska, J.H.; Rzeski, W.; Turski, W.A. Cell-Specific Vulnerability of Human Glioblastoma and Astrocytoma Cells to Mephedrone—An In Vitro Study. Molecules 2025, 30, 2277. [Google Scholar] [CrossRef] [PubMed]
  65. Marszalek-Grabska, M.; Zakrocka, I.; Budzynska, B.; Marciniak, S.; Kaszubska, K.; Lemieszek, M.K.; Winiarczyk, S.; Kotlinska, J.H.; Rzeski, W.; Turski, W.A. Binge-like Mephedrone Treatment Induces Memory Impairment Concomitant with Brain Kynurenic Acid Reduction in Mice. Toxicol. Appl. Pharmacol. 2022, 454, 116216. [Google Scholar] [CrossRef]
  66. den Hollander, B.; Sundström, M.; Pelander, A.; Ojanperä, I.; Mervaala, E.; Korpi, E.R.; Kankuri, E. Keto Amphetamine Toxicity—Focus on the Redox Reactivity of the Cathinone Designer Drug Mephedrone. Toxicol. Sci. 2014, 141, 120–131. [Google Scholar] [CrossRef]
  67. Alanazi, I.M.; Alzahrani, A.R.; Alsaad, M.A.; Moqeem, A.L.; Hamdi, A.M.; Taher, M.M.; Watson, D.G.; Helen Grant, M. The Effect of Mephedrone on Human Neuroblastoma and Astrocytoma Cells. Saudi Pharm. J. 2024, 32, 102011. [Google Scholar] [CrossRef]
  68. Zheng, H.; Zhang, Y.; Liu, L.; Wan, W.; Guo, P.; Nyström, A.M.; Zou, X. One-Pot Synthesis of Metal–Organic Frameworks with Encapsulated Target Molecules and Their Applications for Controlled Drug Delivery. J. Am. Chem. Soc. 2016, 138, 962–968. [Google Scholar] [CrossRef]
  69. Xu, X.; Saw, P.E.; Tao, W.; Li, Y.; Ji, X.; Bhasin, S.; Liu, Y.; Ayyash, D.; Rasmussen, J.; Huo, M.; et al. ROS-Responsive Polyprodrug Nanoparticles for Triggered Drug Delivery and Effective Cancer Therapy. Adv. Mater. 2017, 29, 1700141. [Google Scholar] [CrossRef]
  70. Kim, M.S.; Haney, M.J.; Zhao, Y.; Mahajan, V.; Deygen, I.; Klyachko, N.L.; Inskoe, E.; Piroyan, A.; Sokolsky, M.; Okolie, O.; et al. Development of Exosome-Encapsulated Paclitaxel to Overcome MDR in Cancer Cells. Nanomed. Nanotechnol. Biol. Med. 2016, 12, 655–664. [Google Scholar] [CrossRef]
  71. Song, M.; Liu, T.; Shi, C.; Zhang, X.; Chen, X. Bioconjugated Manganese Dioxide Nanoparticles Enhance Chemotherapy Response by Priming Tumor-Associated Macrophages toward M1-like Phenotype and Attenuating Tumor Hypoxia. ACS Nano 2016, 10, 633–647. [Google Scholar] [CrossRef]
  72. Yang, T.; Martin, P.; Fogarty, B.; Brown, A.; Schurman, K.; Phipps, R.; Yin, V.P.; Lockman, P.; Bai, S. Exosome Delivered Anticancer Drugs Across the Blood-Brain Barrier for Brain Cancer Therapy in Danio Rerio. Pharm. Res. 2015, 32, 2003–2014. [Google Scholar] [CrossRef]
  73. Zhou, Q.; Shao, S.; Wang, J.; Xu, C.; Xiang, J.; Piao, Y.; Zhou, Z.; Yu, Q.; Tang, J.; Liu, X.; et al. Enzyme-Activatable Polymer–Drug Conjugate Augments Tumour Penetration and Treatment Efficacy. Nat. Nanotechnol. 2019, 14, 799–809. [Google Scholar] [CrossRef]
  74. Lin, T.; Zhao, P.; Jiang, Y.; Tang, Y.; Jin, H.; Pan, Z.; He, H.; Yang, V.C.; Huang, Y. Blood–Brain-Barrier-Penetrating Albumin Nanoparticles for Biomimetic Drug Delivery via Albumin-Binding Protein Pathways for Antiglioma Therapy. ACS Nano 2016, 10, 9999–10012. [Google Scholar] [CrossRef]
  75. Huo, M.; Wang, L.; Chen, Y.; Shi, J. Tumor-Selective Catalytic Nanomedicine by Nanocatalyst Delivery. Nat. Commun. 2017, 8, 357. [Google Scholar] [CrossRef] [PubMed]
  76. Qiu, M.; Wang, D.; Liang, W.; Liu, L.; Zhang, Y.; Chen, X.; Sang, D.K.; Xing, C.; Li, Z.; Dong, B.; et al. Novel Concept of the Smart NIR-Light–Controlled Drug Release of Black Phosphorus Nanostructure for Cancer Therapy. Proc. Natl. Acad. Sci. USA 2018, 115, 501–506. [Google Scholar] [CrossRef]
  77. Rodell, C.B.; Arlauckas, S.P.; Cuccarese, M.F.; Garris, C.S.; Li, R.; Ahmed, M.S.; Kohler, R.H.; Pittet, M.J.; Weissleder, R. TLR7/8-Agonist-Loaded Nanoparticles Promote the Polarization of Tumour-Associated Macrophages to Enhance Cancer Immunotherapy. Nat. Biomed. Eng. 2018, 2, 578–588. [Google Scholar] [CrossRef] [PubMed]
  78. Zhang, Y.; Tan, H.; Daniels, J.D.; Zandkarimi, F.; Liu, H.; Brown, L.M.; Uchida, K.; O’Connor, O.A.; Stockwell, B.R. Imidazole Ketone Erastin Induces Ferroptosis and Slows Tumor Growth in a Mouse Lymphoma Model. Cell Chem. Biol. 2019, 26, 623–633.e9. [Google Scholar] [CrossRef] [PubMed]
  79. Liu, M.; Zhang, Z.; Wang, J.; Guo, R.; Zhang, L.; Kong, L.; Yu, Y.; Zang, J.; Liu, Y.; Li, X. Immunomodulatory and Anti-Ovarian Cancer Effects of Novel Astragalus Polysaccharide Micelles Loaded with Podophyllotoxin. Int. J. Biol. Macromol. 2025, 290, 138960. [Google Scholar] [CrossRef]
  80. Rocha, G.N.d.S.A.O.; Silva, J.Y.R.; Santos, D.K.D. do N.; Pereira, A.C.M.V.; Rocha, J.V.R.; Alves, C. dos S.C.; Almeida, J.R.G. da S.; Gomes, A.S.L.; Bakuzis, A.F.; Junior, S.A. Design of a Magnetic Nanocarrier Containing Phyllacanthone as Delivery of Anticancer Phytochemical: Characterization and Theranostic in Vitro Applications. J. Alloys Compd. 2025, 1010, 177860. [Google Scholar] [CrossRef]
  81. Xia, L.; Zhou, C.; Liu, X.; Yu, Y.; Xie, Q.; Lin, H.; Xiong, X.; Zhang, S.; Liang, W.; Shao, H. Transforming Bone Cancer Treatment: A Comprehensive Review of Green-Synthesized Metal Nanoparticles. Cancer Cell Int. 2025, 25, 193. [Google Scholar] [CrossRef]
  82. AbouAitah, K.; Abdelaziz, A.M.; Higazy, I.M.; Swiderska-Sroda, A.; Hassan, A.M.E.; Shaker, O.G.; Szałaj, U.; Stobinski, L.; Malolepszy, A.; Lojkowski, W. Functionalized Carbon Nanotubes for Delivery of Ferulic Acid and Diosgenin Anticancer Natural Agents. ACS Appl. Bio Mater. 2024, 7, 791–811. [Google Scholar] [CrossRef]
  83. Singh, G.; Nenavathu, B.P.; Imtiyaz, K.; Moshahid A Rizvi, M. Fabrication of Chlorambucil Loaded Graphene- Oxide Nanocarrier and Its Application for Improved Antitumor Activity. Biomed. Pharmacother. 2020, 129, 110443. [Google Scholar] [CrossRef]
  84. Madeo, L.F.; Schirmer, C.; Cirillo, G.; Asha, A.N.; Ghunaim, R.; Froeschke, S.; Wolf, D.; Curcio, M.; Tucci, P.; Iemma, F.; et al. ZnO–Graphene Oxide Nanocomposite for Paclitaxel Delivery and Enhanced Toxicity in Breast Cancer Cells. Molecules 2024, 29, 3770. [Google Scholar] [CrossRef] [PubMed]
  85. de Andrade, L.R.M.; Andrade, L.N.; Bahú, J.O.; Cárdenas Concha, V.O.; Machado, A.T.; Pires, D.S.; Santos, R.; Cardoso, T.F.M.; Cardoso, J.C.; Albuquerque-Junior, R.L.C.; et al. Biomedical Applications of Carbon Nanotubes: A Systematic Review of Data and Clinical Trials. J. Drug Deliv. Sci. Technol. 2024, 99, 105932. [Google Scholar] [CrossRef]
  86. Feazell, R.P.; Nakayama-Ratchford, N.; Dai, H.; Lippard, S.J. Soluble Single-Walled Carbon Nanotubes as Longboat Delivery Systems for Platinum(IV) Anticancer Drug Design. J. Am. Chem. Soc. 2007, 129, 8438–8439. [Google Scholar] [CrossRef] [PubMed]
  87. Zhuang, W.; He, L.; Wang, K.; Ma, B.; Ge, L.; Wang, Z.; Huang, J.; Wu, J.; Zhang, Q.; Ying, H. Combined Adsorption and Covalent Linking of Paclitaxel on Functionalized Nano-Graphene Oxide for Inhibiting Cancer Cells. ACS Omega 2018, 3, 2396–2405. [Google Scholar] [CrossRef]
  88. Hussien, N.A.; Işıklan, N.; and Türk, M. Pectin-Conjugated Magnetic Graphene Oxide Nanohybrid as a Novel Drug Carrier for Paclitaxel Delivery. Artif. Cells Nanomed. Biotechnol. 2018, 46, 264–273. [Google Scholar] [CrossRef]
  89. Liao, K.-H.; Lin, Y.-S.; Macosko, C.W.; Haynes, C.L. Cytotoxicity of Graphene Oxide and Graphene in Human Erythrocytes and Skin Fibroblasts. ACS Appl. Mater. Interfaces 2011, 3, 2607–2615. [Google Scholar] [CrossRef]
  90. Zhang, X.; Yin, J.; Peng, C.; Hu, W.; Zhu, Z.; Li, W.; Fan, C.; Huang, Q. Distribution and Biocompatibility Studies of Graphene Oxide in Mice after Intravenous Administration. Carbon 2011, 49, 986–995. [Google Scholar] [CrossRef]
  91. Ageev, S.V.; Semenov, K.N.; Shemchuk, O.S.; Iurev, G.O.; Andoskin, P.A.; Rumiantsev, A.M.; Sambuk, E.V.; Kozhukhov, P.K.; Maistrenko, D.N.; Molchanov, O.E.; et al. Synthesis, Biocompatibility and Biological Activity of a Graphene Oxide-Folic Acid Conjugate for Cytarabine Delivery. Colloids Surf. A Physicochem. Eng. Asp. 2024, 697, 134360. [Google Scholar] [CrossRef]
  92. Koltai, T. The Ph Paradigm in Cancer. Eur. J. Clin. Nutr. 2020, 74, 14–19. [Google Scholar] [CrossRef]
  93. Gillies, R.J.; Raghunand, N.; Karczmar, G.S.; Bhujwalla, Z.M. MRI of the Tumor Microenvironment. J. Magn. Reson. Imaging 2002, 16, 430–450. [Google Scholar] [CrossRef] [PubMed]
  94. Frisch, M.J.; Trucks, G.W.; Schlegel, G.E.; Scuseria, M.A.; Robb, J.R.; Cheeseman, G.; Scalmani, V.; Barone, G.A.; Petersson, H.; Nakatsuji, X.; et al. Gaussian 16 Revision C.01 2019; Gaussian, Inc.: Wallingford, CT, USA, 2019. [Google Scholar]
  95. Dennington, R.; Keith, T.A.; Millam, J.M. GaussView 6.0 2016; Gaussian, Inc.: Wallingford, CT, USA, 2016. [Google Scholar]
  96. Becke, A.D. Density-Functional Exchange-Energy Approximation with Correct Asymptotic Behavior. Phys. Rev. A 1988, 38, 3098–3100. [Google Scholar] [CrossRef] [PubMed]
  97. Lee, C.; Yang, W.; Parr, R.G. Development of the Colle-Salvetti Correlation-Energy Formula into a Functional of the Electron Density. Phys. Rev. B 1988, 37, 785–789. [Google Scholar] [CrossRef]
  98. Miehlich, B.; Savin, A.; Stoll, H.; Preuss, H. Results Obtained with the Correlation Energy Density Functionals of Becke and Lee, Yang and Parr. Chem. Phys. Lett. 1989, 157, 200–206. [Google Scholar] [CrossRef]
  99. Grimme, S.; Ehrlich, S.; Goerigk, L. Effect of the Damping Function in Dispersion Corrected Density Functional Theory. J. Comput. Chem. 2011, 32, 1456–1465. [Google Scholar] [CrossRef]
  100. Kupka, T.; Stachów, M.; Stobiński, L.; Kaminský, J. DFT Study of Zigzag (n, 0) Single-Walled Carbon Nanotubes: 13C NMR Chemical Shifts. J. Mol. Graph. Model. 2016, 67, 14–19. [Google Scholar] [CrossRef]
  101. Kupka, T.; Stachów, M.; Stobiński, L.; Kaminský, J. Calculation of Raman Parameters of Real-Size Zigzag (n, 0) Single-Walled Carbon Nanotubes Using Finite-Size Models. Phys. Chem. Chem. Phys. 2016, 18, 25058–25069. [Google Scholar] [CrossRef]
  102. Kupka, T.; Stachów, M.; Chełmecka, E.; Pasterny, K.; Stobińska, M.; Stobiński, L.; Kaminský, J. Efficient Modeling of NMR Parameters in Carbon Nanosystems. J. Chem. Theory Comput. 2013, 9, 4275–4286. [Google Scholar] [CrossRef]
  103. Chełmecka, E.; Pasterny, K.; Kupka, T.; Stobiński, L. DFT Studies of COOH Tip-Functionalized Zigzag and Armchair Single Wall Carbon Nanotubes. J. Mol. Model. 2012, 18, 2241–2246. [Google Scholar] [CrossRef] [PubMed]
  104. Chełmecka, E.; Pasterny, K.; Kupka, T.; Stobiński, L. Density Functional Theory Studies of OH-Modified Open-Ended Single-Wall Zigzag Carbon Nanotubes (SWCNTs). J. Mol. Struct. THEOCHEM 2010, 948, 93–98. [Google Scholar] [CrossRef]
  105. Kupka, T.; Stachów, M.; Nieradka, M.; Stobiński, L. DFT Calculation of Structures and NMR Chemical Shifts of Simple Models of Small Diameter Zigzag Single Wall Carbon Nanotubes (SWCNTs). Magn. Reson. Chem. 2011, 49, 549–557. [Google Scholar] [CrossRef] [PubMed]
  106. Makieieva, N.; Kupka, T.; Stobiński, L.; Małolepszy, A. Modeling Hydration of Graphene Oxide (GO)—Does Size Matter? J. Mol. Struct. 2024, 1318, 139317. [Google Scholar] [CrossRef]
  107. Buczek, A.; Staś, M.; Hebenstreit, C.; Maller, C.; Broda, M.A.; Kupka, T.; Kelterer, A.-M. Interaction of 5-Fluorouracil with β-Cyclodextrin: A Density Functional Theory Study with Dispersion Correction. Int. J. Quantum Chem. 2021, 121, e26487. [Google Scholar] [CrossRef]
  108. Francl, M.M.; Pietro, W.J.; Hehre, W.J.; Binkley, J.S.; Gordon, M.S.; DeFrees, D.J.; Pople, J.A. Self-consistent Molecular Orbital Methods. XXIII. A Polarization-type Basis Set for Second-row Elements. J. Chem. Phys. 1982, 77, 3654–3665. [Google Scholar] [CrossRef]
  109. Barone, V.; Cossi, M.; Tomasi, J. Geometry Optimization of Molecular Structures in Solution by the Polarizable Continuum Model. J. Comput. Chem. 1998, 19, 404–417. [Google Scholar] [CrossRef]
  110. Boys, S.F.; Bernardi, F. The Calculation of Small Molecular Interactions by the Differences of Separate Total Energies. Some Procedures with Reduced Errors. Mol. Phys. 1970, 19, 553–566. [Google Scholar] [CrossRef]
  111. Nowak, P.M.; Olesek, K.; Woźniakiewicz, M.; Mitoraj, M.; Sagan, F.; Kościelniak, P. Cyclodextrin-Induced Acidity Modification of Substituted Cathinones Studied by Capillary Electrophoresis Supported by Density Functional Theory Calculations. J. Chromatogr. A 2018, 1580, 142–151. [Google Scholar] [CrossRef]
  112. Smith, S.W. Chiral Toxicology: It’s the Same Thing…Only Different. Toxicol. Sci. 2009, 110, 4–30. [Google Scholar] [CrossRef]
  113. Silva, B.; Rodrigues, J.S.; Almeida, A.S.; Lima, A.R.; Fernandes, C.; Guedes de Pinho, P.; Miranda, J.P.; Remião, F. Enantioselectivity of Pentedrone and Methylone on Metabolic Profiling in 2D and 3D Human Hepatocyte-like Cells. Pharmaceuticals 2022, 15, 368. [Google Scholar] [CrossRef] [PubMed]
  114. Jóźwiak, K.; Jezierska, A.; Panek, J.J.; Łydżba-Kopczyńska, B.; Filarowski, A. Renewed Spectroscopic and Theoretical Research of Hydrogen Bonding in Ascorbic Acid. Spectrochim. Acta Part A Mol. Biomol. Spectrosc. 2024, 320, 124585. [Google Scholar] [CrossRef] [PubMed]
  115. Jóźwiak, K.; Jezierska, A.; Panek, J.J.; Kochel, A.; Łydżba-Kopczyńska, B.; Filarowski, A. Very Strong Hydrogen Bond in Nitrophthalic Cocrystals. Molecules 2024, 29, 3565. [Google Scholar] [CrossRef]
  116. Jóźwiak, K.; Jezierska, A.; Panek, J.J.; Kochel, A.; Filarowski, A. Inter- vs. Intra-Molecular Hydrogen Bond in Complexes of Nitrophthalic Acids with Pyridine. Int. J. Mol. Sci. 2023, 24, 5248. [Google Scholar] [CrossRef] [PubMed]
  117. Jóźwiak, K.; Jezierska, A.; Panek, J.J.; Goremychkin, E.A.; Tolstoy, P.M.; Shenderovich, I.G.; Filarowski, A. Inter- vs. Intramolecular Hydrogen Bond Patterns and Proton Dynamics in Nitrophthalic Acid Associates. Molecules 2020, 25, 4720. [Google Scholar] [CrossRef]
  118. Stobinski, L.; Lesiak, B.; Kövér, L.; Tóth, J.; Biniak, S.; Trykowski, G.; Judek, J. Multiwall Carbon Nanotubes Purification and Oxidation by Nitric Acid Studied by the FTIR and Electron Spectroscopy Methods. J. Alloys Compd. 2010, 501, 77–84. [Google Scholar] [CrossRef]
  119. Stobinski, L.; Lesiak, B.; Zemek, J.; Jiricek, P. Time Dependent Thermal Treatment of Oxidized MWCNTs Studied by the Electron and Mass Spectroscopy Methods. Appl. Surf. Sci. 2012, 258, 7912–7917. [Google Scholar] [CrossRef]
  120. Addicoat, M.A.; Stefanovic, R.; Webber, G.B.; Atkin, R.; Page, A.J. Assessment of the Density Functional Tight Binding Method for Protic Ionic Liquids. J. Chem. Theory Comput. 2014, 10, 4633–4643. [Google Scholar] [CrossRef]
  121. Bodo, E.; Mangialardo, S.; Ramondo, F.; Ceccacci, F.; Postorino, P. Unravelling the Structure of Protic Ionic Liquids with Theoretical and Experimental Methods: Ethyl-, Propyl- and Butylammonium Nitrate Explored by Raman Spectroscopy and DFT Calculations. J. Phys. Chem. B 2012, 116, 13878–13888. [Google Scholar] [CrossRef]
  122. Gong, L.; Guo, W.; Xiong, J.; Li, R.; Wu, X.; Li, W. Structures and Stability of Ionic Liquid Model with Imidazole and Hydrogen Fluorides Chains: Density Functional Theory Study. Chem. Phys. Lett. 2006, 425, 167–178. [Google Scholar] [CrossRef]
  123. Doskocz, M.; Roszak, S.; Majumdar, D.; Doskocz, J.; Gancarz, R.; Leszczynski, J. Theoretical Studies on the Mechanism of C−P Bond Cleavage of a Model α-Aminophosphonate in Acidic Condition. J. Phys. Chem. A 2008, 112, 2077–2081. [Google Scholar] [CrossRef] [PubMed]
  124. Hernández-Acosta, M.A.; Martínez-Gutiérrez, H.; Martínez-González, C.L.; Torres-SanMiguel, C.R.; Trejo-Valdez, M.; Torres-Torres, C. Fractional and Chaotic Electrical Signatures Exhibited by Random Carbon Nanotube Networks. Phys. Scr. 2018, 93, 125801. [Google Scholar] [CrossRef]
  125. Graton, J.; Le Questel, J.-Y.; Legouin, B.; Uriac, P.; van de Weghe, P.; Jacquemin, D. A DFT-D Evaluation of the Complexation of a Molecular Tweezer with Small Aromatic Molecules. Chem. Phys. Lett. 2012, 522, 11–16. [Google Scholar] [CrossRef]
  126. Allott, C.; Adams, H.; Hunter, C.A.; Thomas, J.A.; Bernad , P.L., Jr.; Rotger, C. Hydrogen-Bond Recognition of Cyclic Dipeptides in Water. Chem. Commun. 1998, 22, 2449–2450. [Google Scholar] [CrossRef]
  127. Steiner, T.; Koellner, G. Hydrogen Bonds with π-Acceptors in Proteins: Frequencies and Role in Stabilizing Local 3D Structures1. J. Mol. Biol. 2001, 305, 535–557. [Google Scholar] [CrossRef]
  128. Fernández-Recio, J.; Romero, A.; Sancho, J. Energetics of a Hydrogen Bond (Charged and Neutral) and of a Cation-π Interaction in Apoflavodoxin1. J. Mol. Biol. 1999, 290, 319–330. [Google Scholar] [CrossRef]
  129. Alagona, G.; Ghio, C.; Monti, S. 5-Fluorouracil Dimers in Aqueous Solution: Molecular Dynamics in Water and Continuum Solvation. Int. J. Quantum Chem. 2002, 88, 133–146. [Google Scholar] [CrossRef]
  130. Gorgulho, H.F.; Mesquita, J.P.; Gonçalves, F.; Pereira, M.F.R.; Figueiredo, J.L. Characterization of the Surface Chemistry of Carbon Materials by Potentiometric Titrations and Temperature-Programmed Desorption. Carbon 2008, 46, 1544–1555. [Google Scholar] [CrossRef]
Figure 1. Cathinone and its selected synthetic derivatives with their chemical names and letter codes (AD).
Figure 1. Cathinone and its selected synthetic derivatives with their chemical names and letter codes (AD).
Applsci 15 08892 g001
Figure 2. Potential energy curves of model dimers with varying N-H interatomic distance in the gas phase (A,D,G), chloroform (B,E,H), and water (C,F,I) using a PCM.
Figure 2. Potential energy curves of model dimers with varying N-H interatomic distance in the gas phase (A,D,G), chloroform (B,E,H), and water (C,F,I) using a PCM.
Applsci 15 08892 g002
Figure 3. Effect of the environment polarity on COO_A_NH nanotube–cathinone complexes’ structures and intermolecular interactions (dash lines) in (A) the gas phase and (B) water using a PCM. Short intermolecular distances are also shown.
Figure 3. Effect of the environment polarity on COO_A_NH nanotube–cathinone complexes’ structures and intermolecular interactions (dash lines) in (A) the gas phase and (B) water using a PCM. Short intermolecular distances are also shown.
Applsci 15 08892 g003
Figure 4. Effect of the environment polarity on COOH_A_Dimer nanotube–cathinone complexes’ structures and intermolecular interactions (dash lines) in (A) the gas phase and (B) water using a PCM. Short intermolecular distances are also shown.
Figure 4. Effect of the environment polarity on COOH_A_Dimer nanotube–cathinone complexes’ structures and intermolecular interactions (dash lines) in (A) the gas phase and (B) water using a PCM. Short intermolecular distances are also shown.
Applsci 15 08892 g004
Figure 5. Effect of the environment polarity on OH_A_NH_π nanotube–cathinone complexes’ structures and intermolecular interactions (dash lines) in (A) the gas phase and (B) water using a PCM. Short intermolecular distances are also shown.
Figure 5. Effect of the environment polarity on OH_A_NH_π nanotube–cathinone complexes’ structures and intermolecular interactions (dash lines) in (A) the gas phase and (B) water using a PCM. Short intermolecular distances are also shown.
Applsci 15 08892 g005
Figure 6. Effect of a discrete water molecule addition on the structure of (A) COO_A_NH and (B) COOH_A_NH nanotube–cathinone complexes in water using a PCM.
Figure 6. Effect of a discrete water molecule addition on the structure of (A) COO_A_NH and (B) COOH_A_NH nanotube–cathinone complexes in water using a PCM.
Applsci 15 08892 g006
Figure 7. OH_A_NH structure in water using a PCM (A) without and (B) with a discrete water molecule addition. Short intermolecular (dash lines) distances are also shown.
Figure 7. OH_A_NH structure in water using a PCM (A) without and (B) with a discrete water molecule addition. Short intermolecular (dash lines) distances are also shown.
Applsci 15 08892 g007
Figure 8. Complexes of S-cathinone with zigzag (5,0) SWCNT-OH with (A) one, (B) two, and (C) three “bamboo” units. Short intermolecular distances (dash lines) are also shown.
Figure 8. Complexes of S-cathinone with zigzag (5,0) SWCNT-OH with (A) one, (B) two, and (C) three “bamboo” units. Short intermolecular distances (dash lines) are also shown.
Applsci 15 08892 g008
Figure 9. Complexes of the S-cathinone (5,0) with one water molecule and zigzag (5,0) SWCNT-OH with (A) one, (B) two, and (C) three “bamboo” units. Short intermolecular distances (dash lines) are also shown.
Figure 9. Complexes of the S-cathinone (5,0) with one water molecule and zigzag (5,0) SWCNT-OH with (A) one, (B) two, and (C) three “bamboo” units. Short intermolecular distances (dash lines) are also shown.
Applsci 15 08892 g009
Figure 10. Structures of “NH_W”-type complexes of cathinones A–C with (A) SWCNT-COO (model in the neutral pH) and (B) SWCNT-COOH (model in the acidic pH).
Figure 10. Structures of “NH_W”-type complexes of cathinones A–C with (A) SWCNT-COO (model in the neutral pH) and (B) SWCNT-COOH (model in the acidic pH).
Applsci 15 08892 g010
Table 1. BSSE-corrected interaction energies (kcal/mol) in complexes of the S-cathinone with/without a discrete water molecule addition with zigzag (5,0) SWCNT-OH with one, two, and three “bamboo” units.
Table 1. BSSE-corrected interaction energies (kcal/mol) in complexes of the S-cathinone with/without a discrete water molecule addition with zigzag (5,0) SWCNT-OH with one, two, and three “bamboo” units.
Without WaterWith Water
ComplexEBSSEComplexEBSSE
1 unit−10.94641 unit−10.8627
2 units−11.05562 units−11.3299
3 units−11.41933 units−11.4700
Table 2. BSSE-corrected interaction energies (kcal/mol) and non-covalent intermolecular interaction lengths (Å) in complexes of S-cathinone and its derivatives (A–D) with and without discrete water molecule(s) and (5,0) zigzag SWCNT with two “bamboo” units. Label “W” stands for discrete water molecule(s) in the system.
Table 2. BSSE-corrected interaction energies (kcal/mol) and non-covalent intermolecular interaction lengths (Å) in complexes of S-cathinone and its derivatives (A–D) with and without discrete water molecule(s) and (5,0) zigzag SWCNT with two “bamboo” units. Label “W” stands for discrete water molecule(s) in the system.
ComplexEBSSEKind of InteractionH··A or π··π Length
SWCNT-OH
OH_A_CO−11.0556CNT-O-H··O=C1.7279
CNT-C(π)··H-N2.2097
CNT-C(π)··H-C2.8326
OH_A_NH−5.6333CNT-O··H-N2.4271
CNT-C(π)··H-N2.1972
CNT-C(π)··H-C2.6250
CNT-C(π)··H-C2.9627
OH_A_NH_π−9.9913CNT-O··H-N1.9932
CNT-C-H··O=C3.1801
CNT-C(π)··C(π)3.2626
OH_B_CO−11.0684CNT-O-H··O=C1.7519
CNT-O··H-C2.8541
CNT-C(π)··H-C3.3073
CNT-C(π)··C(π)3.2787
OH_C_CO−10.5607CNT-O-H··O=C1.7193
CNT-C(π)··H-N2.1034
CNT-C(π)··H-C3.4077
OH_C_F−3.2792CNT-O-H··F1.8392
OH_C_NH−5.6249CNT-O··H-N1.9322
CNT-C(π)··H-C2.8021
OH_C_NH_π−6.0032CNT-O··H-N2.0279
CNT-C-H··O=C2.4568
CNT-C-H··C(π)2.6999
OH_C_NH_π2−10.0124CNT-O··H-C3.2526
CNT-C(π)··H-N2.1870
CNT-C(π)··H-C2.9081
CNT-C(π)··H-C2.5219
CNT-C(π)··H-C2.8047
OH_C_π−9.0711CNT-C(π)··H-C2.6274
CNT-C(π)··H-C2.7309
CNT-C(π)··C(π)3.2898
SWCNT-COO
COO_A_CO-CH−7.4879CNT-C-H··O=C2.6517
CNT-C-H··C(π)2.6270
CNT-C-H··C(π)2.7392
CNT-C=O··H-C2.3810
CNT-C=O··H-C2.5079
COO_A_NH_π_W−22.8341CNT-C=O··H-N1.3952
CNT-C-H··C(π)2.4972
COO_A_NH_W−23.2044CNT-C=O··H-N1.5029
CNT-C(π)··H-N2.9131
COO_B_CO-CH−6.2739CNT-C=O··H-C2.7538
CNT-C=O··H-C2.1771
CNT-C-H··O=C2.3519
CNT-C-H··O=C2.4012
COO_B_NH_W−18.6932CNT-C=O··H-N1.4511
COO_B_π−8.8260CNT-C-H··CI3.1526
CNT-C-H··CI2.8095
CNT-C=O··H-C2.3634
CNT-C=O··H-C2.5071
CNT-C-H··C(π)2.8230
COO_C_NH_W−20.2424CNT-C=O··H-N1.4768
COO_C_π−7.4756CNT-C=O··H-C2.4253
CNT-C=O··H-C2.4082
CNT-C-H··C(π)2.7564
COO_C_π2_W2−11.8132CNT-C=O··H-C2.2884
CNT-C=O··H-C2.0081
CNT-C=O··H-C2.4404
CNT-C-H··O=C2.5782
CNT-C-H··C(π)2.6376
COO_D_COC_W−8.8299CNT-C=O··H-C2.3822
CNT-C-H··O-C2.6209
CNT-C-H··O=C2.3299
COO_D_NH_W2−16.5568CNT-C=O··H-N1.6187
CNT-C=O··H-C2.4678
CNT-C=O··H-C2.3770
SWCNT-COOH
COOH_A_Dimer_W−15.3782CNT-O-H··O=C1.8247
CNT-C=O··H-N1.5116
COOH_A_NH_W−16.4735CNT-C=O··H-N1.6398
CNT-C(π)··H-C3.0042
COOH_A_π_W−7.1474CNT-C=O··H-C2.4025
CNT-C-H··C(π)2.7412
COOH_B_CI−7.6597CNT-O-H··CI3.4914
CNT-C(π)··H-C2.3745
CNT-C(π)··H-C2.7376
CNT-C(π)··H-N2.6783
COOH_B_Dimer_W−14.5553CNT-O-H··O=C1.8315
CNT-C=O··H-N1.5659
COOH_B_NH_W−16.2372CNT-C=O··H-N1.5541
CNT-C(π)··H-N2.4967
CNT-C(π)··H-C3.0067
COOH_C_Dimer_W−16.9588CNT-O-H··O=C1.8993
CNT-C=O··H-N1.6445
COOH_C_F_CO−5.5671CNT-O-H··F2.0677
CNT-C-H··O=C2.3553
COOH_C_NH_W−13.1462CNT-C=O··H-N1.5767
CNT-C(π)··H-C3.0016
CNT-C(π)··H-C3.0241
COOH_C_π2−9.4891CNT-C(π)··H-C2.8867
CNT-C(π)··H-C2.8332
CNT-C(π)··H-C2.8735
CNT-C(π)··H-C2.7112
CNT-C-H··C(π)3.3450
COOH_D_COC_W−11.5632CNT-O-H··O-C2.1689
CNT-C(π)··H-C2.8143
CNT-C(π)··H-C2.8537
CNT-C(π)··H-C2.5988
CNT-C(π)··H-C3.4458
CNT-C-H··C(π)2.6291
COOH-D_Dimer_W−16.2812CNT-O-H··O=C1.8966
CNT-C=O··H-N1.6131
CNT-C(π)··H-C2.9518
CNT-C(π)··H-C2.9298
COOH_D_π−10.2033CNT-O··H-C2.2241
CNT-O··H-C2.5506
CNT-C(π)··H-C2.5417
CNT-C(π)··H-C2.7299
CNT-C-H··C(π)2.5632
Table 3. The BSSE-corrected interaction energies (kcal/mol) in complexes of the S-cathinone and its derivatives B-C with SWCNT-COOH and SWCNT-COO and discrete water molecules.
Table 3. The BSSE-corrected interaction energies (kcal/mol) in complexes of the S-cathinone and its derivatives B-C with SWCNT-COOH and SWCNT-COO and discrete water molecules.
ComplexEBSSE (SWCNT-COO)EBSSE (SWCNT-COOH)
A_NH_W−23.2044−16.4735
B_NH_W−18.6932−16.2372
C_NH_W−20.2424−13.1462
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Makieieva, N.; Kupka, T.; Rahmonov, O. Modelling of Cathinone–Carbon Nanotube Complexes’ Stability: Theory with a Cancer Treatment Perspective. Appl. Sci. 2025, 15, 8892. https://doi.org/10.3390/app15168892

AMA Style

Makieieva N, Kupka T, Rahmonov O. Modelling of Cathinone–Carbon Nanotube Complexes’ Stability: Theory with a Cancer Treatment Perspective. Applied Sciences. 2025; 15(16):8892. https://doi.org/10.3390/app15168892

Chicago/Turabian Style

Makieieva, Natalina, Teobald Kupka, and Oimahmad Rahmonov. 2025. "Modelling of Cathinone–Carbon Nanotube Complexes’ Stability: Theory with a Cancer Treatment Perspective" Applied Sciences 15, no. 16: 8892. https://doi.org/10.3390/app15168892

APA Style

Makieieva, N., Kupka, T., & Rahmonov, O. (2025). Modelling of Cathinone–Carbon Nanotube Complexes’ Stability: Theory with a Cancer Treatment Perspective. Applied Sciences, 15(16), 8892. https://doi.org/10.3390/app15168892

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop