Major Depressive Disorder and Oxidative Stress: In Silico Investigation of Fluoxetine Activity against ROS

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Due to the seriousness of depressive disorders and their social implications, any strategy to improve clinical symptoms are of considerable importance. It is recognized that oxidative stress negatively impacts on this and other psychiatric diseases. Fluoxetine, a well-known and largely prescribed antidepressant drug, has antioxidant capacity, but, based on our analysis, this is due to its efficiency in increasing the concentration of free serotonin, rather than its direct ROS scavenging activity.

Abstract

Major depressive disorder is a psychiatric disease having approximately a 20% lifetime prevalence in adults in the United States (U.S.), as reported by Hasin et al. in JAMA Psichiatry 2018 75, 336–346. Symptoms include low mood, anhedonia, decreased energy, alteration in appetite and weight, irritability, sleep disturbances, and cognitive deficits. Comorbidity is frequent, and patients show decreased social functioning and a high mortality rate. Environmental and genetic factors favor the development of depression, but the mechanisms by which stress negatively impacts on the brain are still not fully understood. Several recent works, mainly published during the last five years, aim at investigating the correlation between treatment with fluoxetine, a non-tricyclic antidepressant drug, and the amelioration of oxidative stress. In this work, the antioxidant activity of fluoxetine was investigated using a computational protocol based on the density functional theory approach. Particularly, the scavenging of five radicals (HO^•, HOO^•, CH₃OO^•, CH₂=CHOO^•, and CH₃O^•) was considered, focusing on hydrogen atom transfer (HAT) and radical adduct formation (RAF) mechanisms. Thermodynamic as well as kinetic aspects are discussed, and, for completeness, two metabolites of fluoxetine and serotonin, whose extracellular concentration is enhanced by fluoxetine, are included in our analysis. Indeed, fluoxetine may act as a radical scavenger, and exhibits selectivity for HO^• and CH₃O^•, but is inefficient toward peroxyl radicals. In contrast, the radical scavenging efficiency of serotonin, which has been demonstrated in vitro, is significant, and this supports the idea of an indirect antioxidant efficiency of fluoxetine.

1. Introduction

1.1. Background

Fluoxetine hydrochloride (3-(p-trifluoromethylphenoxy)-N-methyl-3-phenylpropylamine HCl) (1, Figure 1) was presented to the community of physicians and medicinal chemists in the early 1970s, when it was described in a scientific journal as a selective serotonin-reuptake inhibitor [1]. Nevertheless, several years were required to fully develop this compound, which was later approved for the treatment of depression by the Food and Drug Administration (FDA, 1987) and marketed as Prozac (Eli Lilly) [2]. Fluoxetine is the prototype of selective serotonin-reuptake inhibitors (SSRIs), the first member of a new class of antidepressants initially introduced in the United States (U.S.) [2]. Moreover, it was also the first SSRI made available for clinical use in most countries besides the U.S. [3]. Despite early skepticism, Prozac became a true symbol of successful “blockbuster” drugs through the years. In fact, a fluoxetine capsule was depicted in the cover of Newsweek, celebrated as “a breakthrough drug for depression” by the same magazine (1990), as one of the “Pharmaceutical Products of the Century” by Fortune (1999) and, more in general, as the “happiness pill” in the pop culture [2].

By blocking the reuptake of serotonin (2, Figure 1) binding the neuronal presynaptic serotonin transporter SLC6A4 (Solute Carrier Family 6 Member 4), fluoxetine promotes an increase of the concentration of the neurotransmitter in the synaptic cleft. This leads to enhanced postsynaptic neuronal activity of the serotoninergic neurotransmission with limited effects on catecholaminergic neurons, differently from tricyclic antidepressants (TCAs) [4,5,6]. The observed therapeutic results are mainly due to the effect on the 5-HT_2C receptors [7].

Fluoxetine is structurally related to diphenhydramine, which is an antihistaminic that had been developed 30 years before [5]. It is a racemic mixture of two enantiomers, R(−)-fluoxetine and S(+)-fluoxetine, the latter being 1.5 times more potent in inhibiting serotonin reuptake [3,8]. The molecular basis and the binding mode justifying this difference were studied from a structural point of view [9]. After the patent on racemic fluoxetine expired, attempts to develop S(+)-fluoxetine formulations were pursued [10]. Fluoxetine has been marketed in capsules (the typical dose is 20 mg for the treatment of depression), but formulations for prolonged drug release were also studied [5,11]. It has been approved worldwide for the treatment of major depression, but it is also effective against several other syndromes [1,5], with a clinical efficacy similar to that of TCAs and fewer cardiovascular and anticholinergic side effects [5]. Fluoxetine effectively acts on a wide spectrum of mood disorders and protects against the adverse effects of different types of stressors by decreasing some effects of stress on the immune system and by protecting against oxidative damage. Different molecular mechanisms have been proposed to explain its neuroprotective effects, including BDNF (Brain-derived Neurotrophic Factor) release, antagonism on NMDA (N-methyl-D-aspartate) receptors, the inhibition of NF-kB (Nuclear Factor Kappa B Subunit 1) activity, and inhibition of the release of pro-inflammatory factors (TNF-α, Tumor Necrosis Factor-Alpha, IL-1β, Interleukin 1 Beta) from microglial cells [12]. However, the underlying mechanisms of its therapeutic efficacy remain unclear, particularly those related to its antioxidant activity. The brain is very susceptible to oxidative stress, since it has a high energy requirement, and oxidative stress has been implicated in the pathogenesis of many psychiatric and degenerative disorders. Moreover, aversive stimuli promote peripheral oxidative stress, which leads to an increase in the generation of reactive oxygen species (ROS) in peripheral blood lymphocytes, granulocytes, and monocytes, and a meta-analysis showed an increase in oxidative stress markers such as 8-oxo-2′deoxyguanosine and F2-isoprostanes in depressed patients [13]. High level of proteins and lipid peroxidation and an imbalance between superoxide dismutase and catalase were found in the brain and in the submitochondrial particles into the brain, and the antidepressant treatment improves these oxidative stress parameters in patients with depression [14]. Higher serum total oxidant status and a lower serum total antioxidant capacity in depressed patients were reversed after treatment with antidepressants in animal models of depression as well as in patients [15,16,17].

It has been postulated that the capacity of fluoxetine to ameliorate the oxidative stress damage may be either due to a direct role of the molecule or achieved through the stimulation of some antioxidant enzymes. Oxidative stress can damage the cell through lipid peroxidation, DNA or protein oxidation, and mitochondrial damage [18]. In this connection, it must be pointed out that the central nervous system is composed of a high percentage of phospholipids, which can undergo peroxidation and generate ROS, and may eventually lead to potentially harmful conditions for cellular structures [19]. It has been demonstrated, mainly in preclinical but also in clinical studies, that fluoxetine provides a beneficial antioxidant effect through a combination of mechanisms: the inhibition of lipid peroxidation, an increase of glutaminergic transmission, the restoration of the normal metabolism of monoamines, the influence on ion balance, and a reduction of inflammation, which is connected to ROS production [18,20,21]. Kolla et al. showed that amitriptyline and fluoxetine protect against oxidative stress-induced damage in rat pheochromocytoma (PC12) cells, contrasting the effects of H₂O₂ [22]. Caiaffo et al. recently reviewed the evidences of the anti-inflammatory, antiapoptotic, and antioxidant activity of fluoxetine [19]. Particularly, several contributions highlighted that fluoxetine may positively influence, to different degrees, the expression and functioning of “endogenous components of the antioxidant defense system” (superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx) as well as “non-enzymatic antioxidant components”. Moreover, the same authors suggested that, based on the reported findings, fluoxetine provides its antioxidant effect only under conditions of oxidative damage, which can be connected to other diseases (diabetes, depression, ischemia) and/or polypharmacological treatments [19,23]. It must be also pointed out that very recently, Dalmizrak et al. studied the inhibitory potential of fluoxetine on glutathione reductase activity [24].

Kalogiannis et al. investigated the role of fluoxetine in ameliorating the condition of a mice model of cerebral inflammation. According to the working hypothesis of the authors, this SSRI may enhance the cerebral antioxidant capacity of serotonin by increasing its extracellular concentration in the brain [25]. In fact, serotonin is known to possess antioxidant capacity, and has been previously studied in silico as well as in vitro for its potentially protective role for the cell [26,27]. At the same time, the connection between the levels of this neurotransmitter and the antioxidant defense has been clearly established [28], and evidences of the in vitro antioxidant and radical scavenging properties of serotonin have been demonstrated using a combination of experimental techniques [29].

1.2. Aim of This Work

Computational methodologies are nowadays largely employed to rationalize chemical and biochemical phenomena. Particularly, accurate mechanistic studies on the control of oxidative stress by endogenous defenses, including enzymes such as glutathione peroxidase [30,31,32], and molecular drugs that act as mimics of these enzymes [33,34,35,36,37] or as radical scavengers [38] have been reported by some of us. In this work, we investigate in silico the antioxidant activity of fluoxetine via HAT (hydrogen atom transfer) and RAF (radical adduct formation) mechanisms. The purpose is to assess its radical scavenging efficiency; for completeness, two metabolites of fluoxetine (M1 and M2, Figure 1) are included. Finally, the analysis is performed also on serotonin, the extracellular concentration of which is enhanced in patients treated with fluoxetine.

2. Materials and Methods

2.1. Calculation of ΔG°_HAT/RAF

A conformational analysis of 1 was carried out using the semi-empirical quantum mechanical method GFN2-xTB [39,40,41]. Conversely, the most stable conformer of 2 was taken from [27]. For all the studied reactions of HAT and RAF, geometry optimizations of the reactants and products were performed in the gas phase without any constraint, using the M06-2X functional [42] combined with the 6-31G(d) basis set, as implemented in Gaussian 16 [43]. Spin contamination was checked for the doublet ground state species to assess the reliability of the wavefunction. Frequency calculations were carried out at the same level of theory (M06-2X/6-31G(d)) in order to confirm the stationary points (all positive frequencies) and to obtain the thermodynamic corrections at 1 atm and 298 K. Afterwards, single-point energy calculations were performed at M06-2X/6-311+G(d,p) in the gas phase in order to obtain more accurate energy values, and subsequently, at the same level of theory, in benzene and water using the continuum Solvation Model based on Density (SMD) [44,45]. This level of theory is denoted in the text (SMD)-M06-2X/6-311+G(d,p)//M06-2X/6-31G(d,p). Benzene and water mimic an apolar and a polar environment, respectively [46]. The calculation of the HAT/RAF Gibbs free energies for all the available sites was streamlined using an in-house Python script.

Natural spin densities and atomic charges were calculated with the natural population analysis (NPA) for C4 sites in 1 and its metabolites (Scheme 3) [47]. The electron spin density surfaces related to the localized natural bond orbitals (NBO) were also drawn for selected structures with Multiwfn [48] with a high-quality grid and the isodensity value of 0.003.

2.2. Calculation of ΔG^‡_HAT

On the basis of ΔG°_HAT, the most reactive sites were identified, and the energy barriers were computed (level of theory: (SMD)-M06-2X/6-311+G(d,p)//M06-2X/6-31G(d,p)). The single imaginary frequency of all the transition states was analyzed to ensure that it corresponded to the correct vibrational mode. In gas phase, a reactant complex (RC) and a product complex (PC) exist on the potential energy surface, before and after the transition state (TS), respectively. In all cases, these species are located at higher energy than the free reactants and products; thus, energy barriers were calculated, referring to the free reactants in the gas phase as well as in the solvent [49].

3. Results

Radical scavenging occurs via different mechanisms, among which hydrogen atom transfer (HAT) and radical adduct formation (RAF) have been identified as mostly efficient in several organic molecules displaying antioxidant properties, including Trolox [50], melatonin [51], and capsaicin [52], but also psychotropic drugs such as zolpidem [38]. These mechanisms are summarized in Figure 2.

HAT implies the transfer of H^• from one site of the scavenger to the ROS. Conversely, RAF consists in the addition of the ROS to a double bond site. The calculations of ΔG°_HAT/RAF have been streamlined using an in-house Python script, in order to automatically screen all the available sites of fluoxetine (1), its metabolites, and serotonin (2). Activation energies ΔG^‡_HAT/RAF were computed only for the most exergonic reactions. HAT results are presented in the following subsections, while the RAF mechanism and the related energetics are included in the Discussion.

3.1. Fluoxetine

HAT Gibbs free energy (ΔG°_HAT) was computed for all the possible sites of fluoxetine (Figure 1) considering five ROSs, i.e., HO^•, HOO^•, CH₃OO^•, CH₂=CHOO^•, and CH₃O^• (Figure 2). The results are shown in Figure 3 and reported in Table S1. HO^• is the most reactive and electrophilic oxygen-centered radical; the peroxyl radicals HOO^• and CH₃OO^• are much less reactive, and thus can reach remote cellular locations; CH₂=CHOO^• was chosen to mimic larger unsaturated peroxyl radicals; finally, CH₃O^• has an intermediate reactivity between HO^• and the peroxyl radicals.

The thermodynamic results, i.e., reaction energies are discussed first. Referring to the gas-phase values, it emerges that fluoxetine is selective for HO^• and alkoxyl radicals, excluding—in this latter case—the sites on the phenyl rings; it is not selective for peroxyl radicals. Focusing on the scavenging of HO^•, HAT is thermodynamically strongly favored from N site 16 and from C sites 7, 14–15 and 17, among which 7 and 15 are associated to the largest (negative) values, i.e., −26.06 and −26.88 kcal mol⁻¹. A similar ΔG°_HAT is computed for HAT from N site 16 (−24.24 kcal mol⁻¹) and from C site 17 (−24.87 kcal mol⁻¹). In solvent, the same trends are maintained, the ΔG°_HAT becoming more negative with increasing polarity, and the largest negative value is found for HAT from N 16 in water (−31.41 kcal mol⁻¹). When considering CH₃O^•, in the gas phase, HAT is thermodynamically favored only from sites 7 and 14–17. Meanwhile, ΔG°_HAT values are approximately half (in absolute value) those computed for HO^•, except for those associated to C 14 and N 16, which are drastically reduced, changing from −18.31 and −24.24 kcal mol⁻¹ to −3.81 and −9.73 kcal mol⁻¹, respectively. Also, for CH₃O^•, increasing the solvent polarity results in thermodynamically more favored reactions. The reactivity of C sites 14 and 15 of fluoxetine recalls the reactivity of the topologically similar C site 4 in melatonin [46] and zolpidem [38]. By comparing the transfer of the methylene hydrogens to HO^• in these compounds, which were computed at the same level of theory, [38] the order is zolpidem (−33.3 kcal mol⁻¹) > melatonin (−28.9 kcal mol⁻¹) > fluoxetine (−26.88 kcal mol⁻¹). The value of ΔG°_HAT involving HO^• of Trolox is −38.7 kcal mol⁻¹ [38]. As mentioned above, fluoxetine is not selective for peroxyl radicals: a negative value of ΔG°_HAT, i.e., −1.23 kcal mol⁻¹, is computed only for CH₂=CHOO^• in water.

The transition states and thus the activation energies were computed only for the exergonic reactions; they are reported in

Table 1. ΔG^‡_HAT (kcal mol⁻¹) in the gas phase, benzene, and water, for the scavenging of HO^• and CH₃O^• through HAT in 1. Level of theory: (SMD)-M06-2X/6-311+G(d,p)//M06-2X/6-31G(d).

Site	Gas Phase	Benzene	Water	Gas Phase	Benzene	Water
		HO•			CH3O•
7	6.57	8.58	10.03	13.69	16.07	16.45
14	7.48	8.91	9.54	14.95	16.72	16.26
15	5.39	5.95	4.24	11.67	12.35	9.74
16	3.68	4.01	0.85	8.34	9.01	6.18
17	7.84	8.35	5.50	14.43	15.28	12.19

.

Considering the HAT from C sites 7 and 14, the energy barriers increase almost in all cases when going from the gas phase to benzene and water. Conversely, for the HAT from C sites 15 and 17 and N site 16, the lowest activation energies are computed in water. Kinetically, the easiest scavenging involves HO^• in water from N 16, which is also the most thermodynamically favored reaction.

3.2. Fluoxetine Metabolites

The pharmacokinetic and metabolic aspects of fluoxetine in the human body have been described in detail by Hiemke and Hartter and by Mandrioli et al. [3,5]. Fluoxetine is a lipophilic molecule that is almost completely absorbed after oral administration. Oral bioavailability is lower than 90% of the dose, due to hepatic first-pass extraction [53]. Fluoxetine highly accumulates in lungs, mainly due to lysosomal trapping, and it is characterized by a large volume of distribution (Vd), similar to that of TCAs [3]. Accumulation in the brain is lower than that of other SSRIs, with a brain to plasma ratio of 2.6:1 compared with 24:1 for fluvoxamine [54]. Fluoxetine is also characterized by a long half-life (t_1/2), ranging from 24 h to 4 days, which implies that between 1–22 months may be required to reach steady-state conditions during therapy [3,8]. Moreover, it has been observed that fluoxetine follows non-linear kinetics, since there is a disproportion between increase in blood concentration after dose escalation [3]. With a 20–60 mg/die dose, plasma levels range from 50 to 480 ng/mL [5].

R(−)-fluoxetine and S(+)-fluoxetine have different metabolic rates, since a four times greater clearance has been reported for the first, which means that the t_1/2 of the more active S(+) enantiomer is shorter [4]. Hepatic cytocrome P450 enzymes are responsible for the biotransformation in humans. Particularly, fluoxetine undergoes metabolic transformation mediated by CYP isoenzymes, and less than 10% is excreted unchanged or as fluoxetine N-glucuronide [55]. CYP2D6, and other isoforms such as CYP2C9 and CYP3A4, mediate N-demethylation to the active metabolite norfluoxetine (M1). Concerning this metabolite, the pharmacological difference between enantiomers is even stronger: S(+)-norfluoxetine is 20 times more potent in inhibiting serotonin uptake than the R(−) isomer [3]. Norfluoxetine has a longer t_1/2 (4–16 days), and it can also be converted to its glucuronide form [3,5]. CYP2D6 also mediates the further degradation of R(−)-fluoxetine, S(+)-fluoxetine, and S(+)-norfluoxetine, without influencing R(−)-norfluoxetine concentration. Other studies report that CYP2C9 is more selective for the R(−) enantiomer, while the remaining isoforms catalyze N-demethylation on both isomers with similar rates [56]. The oxidative O-dealkylation reaction of fluoxetine can also lead to the formation of another metabolite, p-trifluoromethylphenol (M2). This reaction is mediated by CYP2C19 and CYP3A4 [5].

Several analytical methods have been developed through the years for the identification and quantification of fluoxetine and its metabolites in biological samples. HPLC-UV, mass spectrometry, and gas chromatography are some of the tools included in the methods currently available in the literature [5,57,58,59]. The choice of applying one or more of such analytical techniques should also take into consideration the stereochemical aspects [6]. For the sake of completeness, we have investigated the scavenging activity of M1 and M2.

ΔG°_HAT are shown in Figure 4 and reported in Table S2.

The results of norfluoxetine are very similar to those of 1. Scavenging via HAT is thermodynamically most favored from C sites 7, 14–16. Particularly, in the gas phase, the largest (negative) ΔG°_HAT values are found for C 7 (−30.94 and −16.43 kcal mol⁻¹ for HO^• and CH₃O^•), which become even more negative with increasing solvent polarity, i.e., −31.48 and −16.41 kcal mol⁻¹ in benzene and −32.61 and −17.53 kcal mol⁻¹ in water, respectively. In general, the reactivity of M1 from these sites toward the hydroxyl and methoxyl radicals via HAT is enhanced when compared to that of 1. Particularly, focusing on site C 7, negative values of ΔG°_HAT are computed also for CH₂=CHOO^•, ranging from −0.64 kcal mol⁻¹ in the gas phase to −0.90 and −2.44 kcal mol⁻¹ in benzene and water, respectively. The activation energies, which were computed for the exergonic reactions, are reported in

Table 2. ΔG^‡_HAT (kcal mol⁻¹) in the gas phase, benzene, and water, for the scavenging of HO^• and CH₃O^• through HAT in M1 and M2. Level of theory: (SMD)-M06-2X/6-311+G(d,p)//M06-2X/6-31G(d).

Site	Gas Phase	Benzene	Water	Gas Phase	Benzene	Water
		HO•			CH3O•
7	5.40	7.99	11.58	12.23	15.19	17.63
14	5.36	7.33	10.44	13.64	15.96	18.05
15	4.35	5.42	6.69	9.79	11.07	11.55
16	3.84	4.87	5.71	11.37	12.61	13.07
6a 1	6.21	8.26	12.40	1.83	3.11	5.38

¹ This is the only strongly reactive site (large negative ΔG°_HAT) of M2 toward both HO^• and CH₃O^•.

.

When considering M2, the only strongly reactive site via HAT is 6a, i.e., the alcohol functional group. The selectivity is limited to the HO^• and CH₃O^•. ΔG°_HAT values range from −11.24 kcal mol⁻¹ for the alkoxyl radical in the gas phase to −27.09 kcal mol⁻¹ for the hydroxyl radical in water. The activation energies increase with solvent polarity and are higher for this latter radical, with a value of 12.40 kcal mol⁻¹ in water to be compared with 5.38 kcal mol⁻¹ computed for the alkoxyl radical in the same conditions.

3.3. Serotonin

The radical scavenging activity of serotonin (2) was also systematically investigated, and the results are shown in Figure 5 and Table S3. The scavenging activity of 2 was expected for its well-known antioxidant capacity, which was likely related to its structural similarity to melatonin.

In the gas phase, the largest (negative) ΔG°_HAT values are computed for HAT to HO^• from sites 9, 10–12, and 5a, with values ranging from −18.02 kcal mol⁻¹ (N of the primary amine) to −33.19 kcal mol⁻¹ (O). The trend is maintained in the condensed phase, where the reaction energies become more negative with increasing solvent polarity, reaching the values of −23.50 kcal mol⁻¹ (N of the primary amine) and −39.23 kcal mol⁻¹ (O). Differently from 1 and its metabolites, serotonin also displays some modest activity toward peroxyl radicals, in particular CH2=CHOO^•, when HAT occurs from the O site, with ΔG°_HAT going from −1.60 kcal mol⁻¹ in the gas phase to −4.75 and −9.05 kcal mol⁻¹ in benzene and water, respectively.

The transition states and thus the activation energies were computed only for the exergonic reactions involving the hydroxyl and the methoxyl radical; they are reported in

Table 3. ΔG^‡_HAT (kcal mol⁻¹) in the gas phase, benzene, and water, for the scavenging of HO^• and CH₃O^• through HAT in 2. Level of theory: (SMD)-M06-2X/6-311+G(d,p)//M06-2X/6-31G(d).

Site	Gas Phase	Benzene	Water	Gas Phase	Benzene	Water
		HO•			CH3O•
9	5.61	6.87	0.08	11.97	14.14	11.12
10	6.86	8.02	7.40	14.43	15.73	14.08
11	6.35	6.91	6.46	12.12	12.92	11.44
12	5.40	6.06	5.14	13.13	14.10	13.10
5a	5.02	6.14	11.23	7.29	8.50	5.36

. In fact, the activation energies for HAT from the most thermodynamically favored site are much higher when considering the other radicals, even when HAT occurs from site 5a (Table S4). By inspecting the values shown in Table 3, in the gas phase and benzene, the activation energies for the amines (sites 9 and 12) are almost identical; conversely, in water, ΔG^‡_HAT from the N of the secondary amine becomes almost negligible when the hydroxyl radical is considered, i.e., 0.08 kcal mol⁻¹, a value which, combined with a large negative ΔG°_HAT, i.e., −31.84 kcal mol⁻¹, reveals that the HAT from this site is very efficient. Conversely, the thermodynamically most favored process, which is HAT from 5a, has the highest activation energy in water, i.e., 11.23 kcal mol⁻¹.

4. Discussion

The data on HAT thermodynamics and kinetics for fluoxetine and its two metabolites show a selectivity for hydroxyl and alkoxyl radicals, in analogy to what has been reported for melatonin [46]. The most reactive sites are the hydroxyl group and the amine groups. Rather large negative ΔG°_HAT values are also computed from the C atoms of the hydrocarbon chain, which is in agreement with the reactivity described for melatonin and zolpidem [38]. In order to verify whether there are more efficient scavenging channels for fluoxetine, we have also investigated the RAF mechanism involving the aromatic C sites. ΔG°_RAF values for HO^• were computed for 1 as well as for 2, and are reported in Tables S5 and S6. Focusing on HO^•, it is worth noticing that the scavenging reactions of 1 that are less exergonic via HAT are significantly more exergonic via RAF, as it emerges for when comparing sites 1, 5, and 13, for which the ΔG°_HAT values are −6.14, −3.40, and −5.68 kcal mol⁻¹, and the ΔG°_RAF values are −7.98, −9.20, and −8.29 kcal mol⁻¹, respectively. Small negative Gibbs free reaction energies imply a larger stabilization of the reactants than the products. When comparing HAT and RAF, since the reactants are the same, it is useful to inspect the radical product. In Figure 6, the example of the spin densities computed for the radical products obtained from HAT and RAF involving site 1 and HO^• is shown. RAF leads to the formation of a radical product in which the spin density is significantly more delocalized on the benzene ring and the adjacent oxygen atom.

There is no clear trend for RAF exergonicity when going from the gas phase to benzene and water. In general, the reactants should be more stabilized with increasing solvent polarity, and so the reaction Gibbs free energies should become more negative from benzene to water. However, this is not observed for sites 5, 6, and 8, which are located in a sterically crowded region of fluoxetine between the two orthogonal phenyl rings. In 2, both hydroxyl and methoxyl radicals were tested, and we found that in gas-phase serotonin is selective via RAF for HO^• except from site 3. The process is weakly exergonic from site 8, too; these sites correspond to the junction carbon atoms. When CH₃O^• is considered, the HAT from these sites becomes strongly endergonic. Conversely, exergonic RAF occurs only on sites 1 and 4. The trend in solvent shows that the exergonicity increases with increasing solvent polarity, with the exceptions of sites 2–4 (HO^•) and 4 (CH₃O^•).

5. Conclusions

The major outcomes of our analysis can be summarized in the following. (i) Fluoxetine has antioxidant capacity acting as ROS scavenging via the HAT mechanism, and is selective for hydroxyl and methoxyl radicals. (ii) Scavenging may occur also via the RAF mechanism involving the C sites of the benzene rings. (iii) Serotonin is overall a better scavenger of hydroxyl and peroxyl radicals and, thanks to the presence of the alcoholic group, as in M2, which is one identified metabolite of fluoxetine, displays antioxidant activity also toward peroxyl radicals. These observations support the hypothesis that the clinical evidence of improvement of oxidative damage associated to fluoxetine therapy is likely due to the enhanced concentration of free serotonin, i.e., is an indirect effect.

Due to the seriousness of depressive disorders and their social implication, strategies to improve clinical symptoms are of considerable importance; particularly, the antioxidant capacity combined with the main therapeutic action of existing drugs is an idea that should be further investigated, and likely screened in silico as well as tested in vitro/vivo.