Design, synthesis, and multitarget evaluation of thiosemicarbazone–sulfonamide hybrids as potent cholinesterase and MAO-A inhibitors with neuroblastoma-associated cytotoxicity

Abstract

Neurodegenerative disorders and neuroblastoma represent major therapeutic challenges, and multitarget approaches have gained increasing attention. In this study, a series of thiosemicarbazone derivatives (5a–t) was evaluated for their inhibitory activity against acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and monoamine oxidase A (MAO-A), together with their cytotoxic effects and molecular interaction profiles. In vitro enzyme assays revealed nanomolar inhibition for several compounds. Notably, compound 5n exhibited potent and balanced multitarget activity with IC₅₀ values of 104.28 nM (AChE), 23.04 nM (BChE), and 215.50 nM (MAO-A), surpassing galantamine (IC₅₀ = 296.32 and 105.20 nM for AChE and BChE, respectively) and approaching the activity of clorgyline (IC₅₀ = 401.68 nM). Kinetic studies confirmed strong enzyme binding, with K_i values of 92.42 nM (AChE) and 25.35 nM (BChE). Cytotoxicity assays against SH-SY5Y neuroblastoma cells showed selective antiproliferative effects, with compound 5n displaying an IC₅₀ of 5.23 µM and a selectivity index of 8.6 relative to HUVEC cells. Molecular docking and MM-GBSA analyses revealed strong binding affinities (docking scores − 10.4 to − 15.4 kcal/mol; ΔG_bind − 55.9 to − 88.4 kcal/mol), which were further supported by molecular dynamics simulations. DFT calculations indicated favorable electronic properties (HOMO–LUMO gap: 0.098–0.116 eV), while ADME predictions suggested acceptable drug-like behavior and good oral absorption. These results identify thiosemicarbazone derivative 5n as a promising multitarget lead for the development of agents targeting cholinergic dysfunction, MAO-A inhibition, and neuroblastoma proliferation.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-026-52909-6.

Introduction

Alzheimer’s disease (AD) is the most common form of dementia, a chronic and neurodegenerative disease characterized by progressive deterioration in memory, learning, decision-making, and executive functions. As the disease progresses, individuals’ ability to independently perform daily living activities decreases, and in advanced stages, the need for complete care arises^1,2. In this respect, Alzheimer’s disease is considered a serious public health problem that profoundly affects not only patients but also caregivers and healthcare systems. Globally, with the aging population, the incidence of Alzheimer’s disease is increasing; consequently, the economic and social burden of the disease is also reaching significant levels³. Current treatment options largely provide symptomatic relief, and there is no effective treatment yet that can stop or reverse the progression of the disease⁴. This clearly highlights the need for new and innovative treatment approaches that can more effectively target the underlying biological mechanisms of Alzheimer’s disease.

The pathophysiology of Alzheimer’s disease is complex, involving the simultaneous disruption of numerous biological mechanisms. Among these mechanisms, cholinergic dysfunction and neurotransmitter imbalance play a key role in the emergence of the disease’s cognitive symptoms^5,6. In particular, a decrease in acetylcholine levels leads to significant impairments in memory and learning processes, making the cholinergic system one of the primary therapeutic targets in Alzheimer’s treatment⁷. AChE and BChE are the key enzymes responsible for the hydrolysis of acetylcholine in the synaptic cleft⁸. While AChE activity is dominant in the early stages of Alzheimer’s disease, BChE activity is known to increase as the disease progresses and become more decisive in cholinergic degradation. Therefore, the development of inhibitors targeting not only AChE but also BChE stands out as a rational approach that could provide more sustainable cholinergic efficacy at different stages of the disease^9,10. On the other hand, the monoamine oxidase-A (MAO-A) enzyme is involved in the metabolism of monoamine neurotransmitters, and increased activity in Alzheimer’s disease is associated with increased oxidative stress, mitochondrial dysfunction, and neuronal damage. MAO-A-mediated oxidative processes can accelerate neurodegeneration, further deepening cognitive decline^11,12. In this context, MAO-A inhibition offers a complementary strategy in Alzheimer’s treatment by contributing not only to the maintenance of neurotransmitter balance but also to the reduction of oxidative stress¹³.

Although AD is primarily a neurodegenerative disorder, increasing evidence suggests that several molecular pathways involved in neurodegeneration, including cholinergic signaling, monoamine metabolism, oxidative stress, and mitochondrial dysfunction, are also closely associated with cancer cell survival and proliferation^14,15. In this context, the investigation of cytotoxic effects in cancer-derived neuronal models can provide complementary insight into the broader biological activity of candidate compounds. Therefore, in the present study, SH-SY5Y neuroblastoma cells were employed not only as a neuronal-like model relevant to AD-associated pathways but also as a cancer cell line to evaluate the potential antiproliferative properties of the synthesized compounds^16–18. This dual approach enables a more comprehensive assessment of the biological profile of the compounds, linking their enzyme inhibitory activities with cellular responses related to both neurodegeneration and tumor cell viability¹⁹.

The combined targeting of these enzymes and neuroblastoma cells enables intervention in the multifaceted pathology of AD through multiple mechanisms. The development of small molecules capable of simultaneously modulating AChE, BChE, and MAO-A enzymes is a promising approach for the emergence of multi-targeted and more effective therapeutic candidates for AD²⁰. However, it is crucial to evaluate the therapeutic potential of such candidates not only through their inhibitory activity at the enzyme level but also through their effects on neuronal cells. In this context, human neuroblastoma cell lines associated with neurodegenerative diseases offer a complementary and important in vitro model for elucidating the cellular safety and efficacy profiles of multi-targeted compounds^21,22.

In line with the targeted multiple enzyme inhibition in this study, novel hybrid compounds containing indole-sulfonamide-thiosemicarbazone motifs were developed using a rational design approach (Scheme 1). The indole core was chosen as a privileged scaffold, frequently found in neuroactive compounds, and capable of exhibiting strong interactions with enzyme active sites due to its potential to form hydrogen bonds via aromatic-π interactions. Furthermore, the potential of indole derivatives to cross the blood-brain barrier makes this core attractive in drug design for Alzheimer’s disease^23,24. The thiosemicarbazone group, due to its flexible structure and hydrogen-binding/donating properties, can offer effective binding profiles in the active sites of enzymes such as cholinesterases and monoamine oxidases. The reporting in the literature of thiosemicarbazone derivatives exhibiting neuroprotective²², MAO inhibitor¹³, and multitarget biological activities²⁵ constitutes the main justification for including this functional group in the study. The conversion of the indole NH group to a sulfonamide derivative via 3,5-dichlorobenzenesulfonyl chloride was carried out to regulate the lipophilicity of the molecule, increase its metabolic stability, and enhance its potential for interaction with hydrophobic pockets in enzyme active sites. Furthermore, it was predicted that the sulfonamide function could increase binding affinity through hydrogen bonds and halogen interactions. Through these structural arrangements and using a series of compounds obtained with different N-substituted thiosemicarbazone side chains, the aim was to systematically evaluate the structure-activity relationships (SAR).

Scheme 1.

The design strategy of compounds 5a-t.

This study aimed to synthesize a new series of compounds consisting of indole-based sulfonamide-thiosemicarbazone hybrids and to comprehensively evaluate their biological potential. The inhibitory activities of the synthesized compounds against AChE, BChE, and MAO-A enzymes were investigated in vitro; their cytotoxic effects were evaluated on SH-SY5Y neuroblastoma and HUVEC normal endothelial cell lines to determine their potential therapeutic safety profiles. To interpret the experimental biological findings at the molecular level, molecular docking, molecular dynamics simulations, and ADME estimations were performed; furthermore, the electronic properties and reactivity tendencies of the compounds were supported by DFT analyses. All these data aim to reveal the potential of the synthesized compounds as multi-target therapeutic candidates for AD through a holistic approach.

Results and discussion

Chemistry

In this study, a series of twenty novel indole-based thiosemicarbazone derivatives were rationally designed and synthesized. The synthetic strategy commenced with the sulfonylation of indole-3-carboxaldehyde (1) using 3,5-dichlorobenzenesulfonyl chloride (2) under basic conditions, affording the corresponding sulfonamide intermediate (3). This key intermediate was subsequently condensed with a range of N-substituted thiosemicarbazides (4a–t) to yield the target thiosemicarbazone derivatives (5a–t) in good yields, as outlined in Scheme 2. The chemical structures of all synthesized compounds were unequivocally established using standard spectroscopic techniques, including ¹H and ¹³C NMR spectroscopy, together with HRMS analyses.

Scheme 2.

The design strategy of compounds 5a-t.

Analysis of the ¹H NMR spectra revealed characteristic resonance patterns fully consistent with the proposed thiosemicarbazone scaffold. The hydrazinic NH protons were observed as well-resolved singlets in the δ 12.19–11.54 ppm range. The thioamide NH protons appeared as singlets at δ 10.12–9.45 ppm for the aromatic-substituted derivatives, whereas a triplet pattern was detected at δ 8.65–8.57 ppm for the benzylic analogues^22,26. In addition, the azomethine protons resonated as sharp singlets in the δ 8.43–8.38 ppm region, providing clear evidence for the successful formation of the imine linkage across the entire compound series^27,28. The ¹³C NMR spectra further corroborated the proposed structures, displaying characteristic signals attributable to the thioamide C = S carbons in the δ 178.0–176.0 ppm range. The imine carbons were observed at δ 139.9–139.6 ppm, in good agreement with the expected electronic environment^29,30. Moreover, in the fluorine-containing derivatives, aromatic carbon resonances appeared as well-defined doublets arising from ¹³C to ¹⁹F coupling, providing additional confirmation for the successful incorporation of fluorinated substituents within the aromatic framework^31,32.

In vitro enzyme inhibition studies

AChE inhibition and SAR analysis

The synthesized thiosemicarbazone derivatives were evaluated for their in vitro AChE inhibitory activity in order to assess their potential relevance to AD therapy. Galantamine was employed as the reference inhibitor, and the inhibitory performances of the synthesized compounds were directly compared with this standard. The results revealed that all tested derivatives exhibited potent AChE inhibitory activity, with several compounds displaying comparable or even superior inhibition relative to galantamine. The detailed inhibition data for the entire compound series are summarized in Table 1.

Table 1.

Enzyme inhibition and kinetic results of compounds 5a-t against target enzymes.

Comp.	IC50 (nM)						Ki (nM)
	AChE	R 2	BChE	R 2	MAO-A	R 2	AChE	BChE
5a	197.21	0.972	62.11	0.938	348.52	0.960	208.12 ± 9.86	67.01 ± 5.09
5b	189.53	0.925	31.25	0.957	241.34	0.922	161.51 ± 7.42	27.55 ± 3.08
5c	186.55	0.953	45.78	0.926	342.71	0.971	147.17 ± 3.46	38.61 ± 4.18
5d	199.81	0.978	86.20	0.927	301.48	0.954	210.48 ± 8.66	68.31 ± 7.52
5e	151.60	0.928	93.58	0.947	361.41	0.989	141.46 ± 8.70	79.31 ± 6.94
5f	145.15	0.953	56.76	0.920	370.98	0.922	152.61 ± 6.06	46.38 ± 7.16
5g	106.08	0.981	35.40	0.938	292.46	0.922	108.10 ± 5.91	27.26 ± 2.62
5h	101.67	0.991	20.73	0.913	232.77	0.937	94.59 ± 8.17	24.85 ± 3.84
5i	133.25	0.925	52.37	0.915	331.62	0.963	104.38 ± 5.23	46.47 ± 3.20
5j	136.30	0.952	35.65	0.903	265.27	0.973	139.81 ± 6.13	49.47 ± 5.35
5k	153.54	0.968	25.13	0.972	263.24	0.908	187.66 ± 11.58	28.40 ± 6.28
5l	101.22	0.949	29.31	0.972	283.50	0.990	90.13 ± 5.23	22.65 ± 3.58
5m	124.93	0.969	34.42	0.937	323.83	0.977	145.12 ± 7.40	25.80 ± 4.34
5n	104.28	0.968	23.04	0.956	215.50	0.911	92.42 ± 5.75	25.35 ± 3.21
5o	109.11	0.974	18.43	0.915	221.32	0.926	97.58 ± 6.21	14.83 ± 3.46
5p	136.71	0.982	27.51	0.944	236.73	0.953	129.43 ± 5.77	31.02 ± 5.41
5q	129.61	0.978	82.31	0.974	361.87	0.978	132.54 ± 3.54	65.24 ± 5.31
5r	131.17	0.966	78.73	0.980	311.42	0.905	106.42 ± 6.45	61.34 ± 5.55
5s	106.37	0.910	21.71	0.936	252.86	0.983	113.58 ± 3.36	18.11 ± 2.23
5t	109.60	0.923	24.88	0.951	381.21	0.931	99.53 ± 6.32	20.78 ± 3.43
Galantamine	296.32	0.985	105.20	0.981	-	-	247.06 ± 11.46	92.57 ± 5.10
Clorgyline	-	-	-	-	401.68	0.979	-	-

The inhibitory potential of the synthesized thiosemicarbazone derivatives towards AChE was evaluated in detail based on their K_i values ​​(Table 1). The results showed that all compounds were strong inhibitors of AChE at the nanomolar level. Remarkably, all synthesized compounds exhibited lower IC₅₀ and K_i values ​​compared to the reference inhibitor galantamine (IC₅₀ = 296.32 nM and K_i = 247.06 ± 11.46 nM), demonstrating higher binding affinity. Among the compounds, the derivatives coded 5h (IC₅₀ = 101.67 nM and K_i = 94.59 ± 8.17 nM), 5 L (IC₅₀ = 101.22 nM and K_i = 90.13 ± 5.23 nM), and 5n (IC₅₀ = 104.28 nM and K_i = 92.42 ± 5.75 nM) stood out as the strongest inhibitors against AChE. In addition, the inhibition type was determined as non-competitive for compounds 5a, 5c, 5 g, 5i, 5q, 5r, 5s, 5t, and galantamine, while the remaining compounds were calculated to exhibit competitive inhibition (Fig. 1). These findings suggest that the relevant substituents can optimize their interactions with the enzyme active site and increase binding stability. The concentration of K_i values ​​within a narrow range and at low nanomolar levels reveals that the designed indole-sulfonamide-thiosemicarbazone scaffold offers a successful molecular framework for AChE inhibition.

Fig. 1.

Lineweaver-Burk plots for compound 5n (as representative competitive inhibitors) against AChE and BChE.

When the relationship between AChE inhibitory activity and N-substituted thiosemicarbazone side chains was examined, distinct structure-activity trends were observed. Compounds bearing aliphatic substituents (5a-5e) generally exhibited higher K_i values compared to analogs with aromatic substituents; this suggests that aromatic groups are more advantageous in terms of interaction with aromatic and hydrophobic pockets in the AChE active site. Among benzyl and phenyl derivatives, compounds containing para-substituted aromatic rings were found to provide a significant improvement in AChE inhibition. In particular, 4-methylbenzyl (5h) and 4-chlorophenyl (5 L) derivatives stood out with their low K_i values, demonstrating that hydrophobic or light electron-donating groups in the para-position positively influence enzyme binding. Similarly, halogen-containing aromatic substituents (5 g, 5j, 5k, 5 L, 5n, 5o) generally exhibited a strong profile in terms of AChE inhibition; this suggests that halogens may contribute to binding affinity through hydrophobic interactions and possible halogen bonds. In compound 5n steric effects appear to optimize the binding geometry and allow for more favorable localization at the AChE active site. In contrast, in compounds containing bulky and sterically more restrictive aliphatic groups (e.g., the cyclohexyl derivative 5e), AChE inhibition was observed to be relatively weaker.

The experimentally determined inhibition types were further interpreted in light of the molecular docking results to establish a structure-mechanism relationship. Compounds exhibiting competitive inhibition are likely to interact predominantly with the catalytic active site, where they can directly interfere with substrate binding and hydrolysis. In contrast, derivatives displaying non-competitive inhibition may preferentially associate with the peripheral anionic site or other allosteric regions of the enzyme. This is consistent with the docking results, where several compounds were observed to extend toward peripheral binding regions rather than being confined solely within the catalytic gorge. Such dual-site or peripheral interactions may explain the non-competitive inhibition behavior by modulating substrate access or inducing conformational effects rather than directly competing with the substrate.

BChE inhibition and SAR analysis

The BChE inhibitory activities of the synthesized thiosemicarbazone derivatives were evaluated based on K_i values (Table 1). The data obtained show that all compounds exhibit high affinity for BChE and are effective inhibitors at the nanomolar level. Remarkably, all synthesized derivatives showed stronger inhibitory profiles, exhibiting lower K_i values compared to the reported K_i value for BChE of the reference inhibitor galantamine (IC₅₀ = 105.20 nM and 92.57 ± 5.10 nM). Among the compounds, the derivatives coded 5o (IC₅₀ = 18.43 nM and K_i = 14.83 ± 3.46 nM), 5s (IC₅₀ = 21.71 nM and K_i = 18.11 ± 2.23 nM), 5l (IC₅₀ = 29.31 nM and K_i = 22.65 ± 3.58 nM), 5n (IC₅₀ = 23.04 nM and K_i = 25.35 ± 3.21 nM), and 5h (IC₅₀ = 20.73 nM and K_i = 24.85 ± 3.84 nM) stood out as the most potent inhibitors of BChE. The low K_i values exhibited by these compounds suggest that the designed scaffold is highly compatible with the broader and hydrophobic structure of the BChE active site. In addition, the inhibition type was determined as non-competitive for compounds 5c, 5d, 5j, 5l, 5s, and galantamine, while the remaining compounds were calculated to exhibit competitive inhibition (Fig. 1).

When the relationship between BChE inhibitory activity and N-substituted thiosemicarbazone side chains was examined, more pronounced substituent effects were observed compared to AChE. Compounds containing aliphatic groups (5a–5e) generally exhibited higher K_i values compared to analogs with aromatic substituents; this indicates that aromatic rings are more advantageous in terms of binding due to the size and hydrophobic character of the BChE active site. In particular, compounds carrying halogen-substituted aromatic rings constituted the most successful group in terms of BChE inhibition. The extremely low K_i value exhibited by the 4-bromophenyl (5o) derivative suggests that halogen atoms, which can form bulky and strongly hydrophobic interactions, can significantly stabilize binding in the BChE active site. Similarly, chlorine-containing phenyl derivatives (5k-n) exhibited strong inhibitory profiles, and it was understood that the binding geometry of the 2,3-dichlorophenyl derivative (5n) in particular could be positively affected. Among the methoxy-substituted derivatives, the remarkably low K_i value of 3-methoxy phenyl (5s) suggests that both hydrophobic and potential hydrogen bonding interactions may play a role. In contrast, in derivatives containing bulky aliphatic groups (e.g., cyclohexyl, 5e), BChE inhibition was observed to be relatively weak; this indicates that steric constraints may negatively affect binding efficiency.

A correlation was also observed between kinetic data and docking results for BChE inhibition. Compounds showing competitive inhibition are likely to occupy the catalytic active site, consistent with the relatively larger and more flexible binding pocket of BChE that accommodates various substituents. On the other hand, non-competitive inhibitors may interact with peripheral or alternative binding regions, influencing enzyme activity without directly competing with the substrate. Docking analyses support this interpretation, suggesting that certain derivatives can adopt binding poses extending beyond the catalytic site, which may account for their non-competitive inhibition profiles.

MAO-A inhibition and SAR analysis

The MAO-A inhibitor activities of the synthesized thiosemicarbazone derivatives were evaluated based on IC₅₀ values, and the results were compared with the reference MAO-A inhibitor clorgyline (IC₅₀ = 401.68 nM) (Table 1). The data clearly showed that most of the tested compounds exhibited stronger MAO-A inhibition compared to clorgyline.

The 4-bromophenyl-substituted compound 5o, which stood out as the strongest MAO-A inhibitor in the series, showed approximately 1.8 times higher inhibitory activity than clorgyline with an IC₅₀ value of 221.32 nM. Similarly, the 2,3-dichlorophenyl derivative 5n (IC₅₀ = 215.50 nM) and the 4-methylbenzyl derivative 5h (IC₅₀ = 232.77 nM) were among the compounds exhibiting significantly superior MAO-A inhibition compared to the reference inhibitor. Among halogenated aromatic derivatives, the analogs 4-chlorophenyl (5l, IC₅₀ = 283.50 nM) and 4-fluorobenzyl (5g, IC₅₀ = 292.46 nM) also stood out as potent MAO-A inhibitors, offering lower IC₅₀ values ​​than clorgyline. Furthermore, the ortho-methoxy phenyl derivative 5s (IC₅₀ = 252.86 nM) showed a significant inhibitory effect against MAO-A, suggesting that methoxy substitution provides a favorable electronic environment for this enzyme. In contrast, derivatives containing aliphatic or bulky cyclic substituents (e.g., 5e, IC₅₀ = 361.41 nM; 5q, IC₅₀ = 361.87 nM) were observed to have MAO-A inhibitory activities close to or weaker than the reference inhibitor. This supports the idea that the MAO-A active site prefers aromatic and electronically oriented groups.

Cytotoxicity studies

To evaluate the safety and selectivity profiles of the synthesized thiosemicarbazone derivatives, their in vitro cytotoxic effects on the human neuroblastoma cell line SH-SY5Y and the normal human umbilical vein endothelial cell line (HUVEC) were investigated. Sorafenib was used as the reference drug in the study, and the results obtained were compared with this standard. Cytotoxicity data are summarized in Table 2.

Table 2.

IC₅₀ values of compounds 5a-t against SH-SY5Y and HUVEC cell lines and selectivity indices (SI).

Compounds	IC50 (µM)*		Selectivity Index (SI)**
	SH-SY5Y	HUVEC
5a	14.02 ± 1.05	38.06 ± 2.65	2.7
5b	8.69 ± 0.92	22.20 ± 2.11	2.6
5c	20.00 ± 1.95	31.90 ± 2.37	1.6
5d	9.19 ± 1.35	40.62 ± 2.96	4.4
5e	18.08 ± 2.14	36.39 ± 3.42	2.0
5f	12.32 ± 1.53	50.43 ± 4.15	4.1
5g	15.74 ± 1.67	42.82 ± 4.57	2.7
5h	7.22 ± 0.88	42.23 ± 3.78	5.8
5i	18.43 ± 1.29	44.44 ± 3.65	2.4
5j	14.47 ± 1.22	30.08 ± 3.18	2.1
5k	19.77 ± 1.65	39.74 ± 3.49	2.0
5l	9.70 ± 0.92	50.37 ± 4.21	5.2
5m	8.39 ± 1.51	47.73 ± 3.15	5.7
5n	5.23 ± 0.78	44.89 ± 4.32	8.6
5o	10.04 ± 1.10	48.62 ± 3.58	4.8
5p	16.57 ± 1.32	43.72 ± 3.76	2.6
5q	7.35 ± 0.69	40.36 ± 3.61	5.5
5r	15.77 ± 1.32	45.73 ± 5.43	2.9
5s	11.03 ± 1.45	35.02 ± 3.54	3.2
5t	13.52 ± 1.77	37.97 ± 4.10	2.8
Sorafenib	3.93 ± 0.56	48.36 ± 4.09	12.3

*IC₅₀ values are presented as the mean ± standard deviation (SD) of three independent experiments (n = 3).

**The Selectivity Index (SI) was calculated as the ratio of the IC₅₀ value in HUVEC cells to that in SH-SY5Y cells (SI = IC₅₀ HUVEC / IC₅₀ SH-SY5Y); higher SI values indicate greater selectivity toward cancer cells over normal cells.

Sorafenib was the most potent cytotoxic agent in the series, with an IC₅₀ value of 3.93 ± 0.56 µM in SH-SY5Y cells, but showed limited selectivity in normal HUVEC cells, exhibiting an IC₅₀ value of 48.36 ± 4.09 µM (SI = 12.3). The synthesized compounds exhibited more moderate cytotoxic activity in SH-SY5Y cells compared to sorafenib, while showing a lower or comparable toxicity profile in HUVEC cells. Specifically, compounds 5n (IC₅₀ = 5.23 ± 0.78 µM), 5h (7.22 ± 0.88 µM), 5m (8.39 ± 1.51 µM), and 5l (9.70 ± 0.92 µM) showed cytotoxicity similar to sorafenib, while presenting a safer biological window with higher IC₅₀ values in normal cells. In the normal HUVEC cell line, most synthesized compounds exhibited IC₅₀ values in the 30–50 µM range, demonstrating similar or lower cytotoxicity than sorafenib. This indicates that the synthesized thiosemicarbazone derivatives can exhibit high enzyme inhibitory activity without causing significant toxicity in normal cells.

Molecular docking analysis

Molecular docking studies are a widely used computational approach to elucidate the binding modes, interaction types, and binding affinities of small molecules to the active sites of target proteins at the molecular level³³. This method allows for understanding the structural basis of experimental enzyme inhibition results and rationalizing observed biological activities at the molecular level. In this study, the Induced Fit Docking (IFD) protocol was used to more realistically model the interactions of synthesized thiosemicarbazone derivatives with the enzymes. The IFD approach, by considering conformational changes that may occur in the active site of the protein during ligand binding, provides more accurate and reliable binding positions compared to classical rigid docking methods^34,35. Following the docking analyses, the binding free energies of ligand-enzyme complexes were calculated using the MM-GBSA (Molecular Mechanics-Generalized Born Surface Area) method. MM-GBSA calculations go beyond docking scores, allowing for the assessment of the thermodynamic stability of ligand-protein interactions and enabling stronger correlations with experimental inhibition data³⁶.

In this study, molecular docking and MM-GBSA analyses were performed on compounds 5h, 5l, 5m, 5n, and 5o, which are the most promising candidates based on in vitro enzyme inhibition and cytotoxicity results, as well as on reference inhibitors. The binding modes and binding free energies of these compounds with the active sites of the target enzymes were investigated in detail, and the obtained computational results are presented in Table 3.

Table 3.

Molecular docking scores and MM-GBSA ΔG binding energies of in vitro most active compounds.

Compounds	IFD Docking Scores (kcal/mol)			MM-GBSA ΔG Bind. (kcal/mol)
	AChE (PDB: 4M0F)	BChE (PDB: 6EQP)	MAO-A (PDB: 2Z5X)	AChE	BChE	MAO-A
5h	-12.274	-10.379	-14.009	-79.05	-66.56	-84.13
5l	-12.647	-10.658	-13.747	-80.74	-63.87	-82.20
5m	-11.946	-10.780	-13.672	-77.38	-88.42	-83.77
5n	-12.164	-10.728	-15.440	-81.81	-71.62	-83.86
5o	-12.823	-10.467	-13.944	-74.38	-55.94	-85.54
Galantamine	-8.024	-5.183	-	-35.81	-41.84	-
Clorgyline	-	-	-7.612	-	-	-56.12

The molecular docking and MM-GBSA binding free energy results clearly demonstrate that the selected hit compounds form strong and stable interactions with AChE, BChE, and MAO-A enzymes. The obtained computational data show a high degree of agreement with the in vitro inhibition results.

The compounds evaluated for AChE exhibited significantly lower (better) IFD docking scores and more negative MM-GBSA ΔG binding energies compared to galantamine. While the docking score obtained for galantamine was − 8.024 kcal/mol and the MM-GBSA value was − 35.81 kcal/mol, the docking scores of the synthesized compounds ranged from − 11.946 to -12.823 kcal/mol, and the MM-GBSA values ​​ranged from − 74.38 to -81.81 kcal/mol. Specifically, compounds 5o (-12.823 kcal/mol) and 5L (-12.647 kcal/mol) exhibited a significantly superior binding profile compared to galantamine, displaying high binding affinity to the AChE active site.

BChE docking analyses showed a similar trend. Galantamine exhibited a relatively weak binding profile for BChE, presenting a docking score of -5.183 kcal/mol and an MM-GBSA value of -41.84 kcal/mol. In contrast, the docking scores of the selected hit compounds ranged from − 10.379 to -10.780 kcal/mol, and the MM-GBSA binding energies ranged from − 55.94 to -88.42 kcal/mol. In particular, 5m formed one of the most stable complexes against BChE with an MM-GBSA value of -88.42 kcal/mol, strongly supporting the experimental inhibition data.

In docking and MM-GBSA analyses performed for MAO-A, the compounds exhibited superior binding profiles compared to the reference inhibitor clorgyline. While the docking score calculated for clorgyline was − 7.612 kcal/mol and the MM-GBSA value was − 56.12 kcal/mol, the docking scores of the studied compounds ranged from − 13.672 to -15.440 kcal/mol, and the MM-GBSA values ​​ranged from − 82.20 to -85.54 kcal/mol. Specifically, 5n demonstrated a strong binding affinity, exhibiting the best docking score against MAO-A (-15.440 kcal/mol) while 5o stood out as one of the most stable ligand-enzyme complexes with a MM-GBSA value of -85.54 kcal/mol.

Based on the in vitro enzyme inhibition and cytotoxicity results, together with the insights obtained from IFD docking and MM-GBSA calculations, the most promising candidate, compound 5n, was selected for an in-depth molecular docking visualization analysis. To gain a clearer understanding of its binding behavior, both 2D and 3D interaction profiles were analyzed to elucidate the preferred binding orientations and the key molecular interactions stabilizing the ligand within the active sites of AChE, BChE, and MAO-A. The corresponding 2D and 3D ligand-protein interaction diagrams illustrating the binding mode of compound 5n within the AChE active site are presented in Fig. 2.

Fig. 2.

Molecular docking 2D (a) and 3D (b) ligand-protein interactions of 5n–AchE complex.

Molecular docking analysis demonstrated that compound 5n adopts a highly favorable and well-stabilized binding pose within the active site of AChE. The sulfonamide oxygen of the ligand forms a strong hydrogen bond with Tyr341 (2.24 Å), a key residue located within the peripheral anionic site that plays a crucial role in substrate guidance and initial ligand recognition. This interaction is critical, as engagement with Tyr341 is known to contribute to the effective blockage of substrate access to the catalytic gorge^36,37. Additionally, the thioamide NH group establishes a short hydrogen bond with Ser293 (1.86 Å), a residue positioned near the catalytic region and involved in stabilizing ligand orientation within the active-site gorge^38,39. This interaction provides an additional anchoring point, enhancing the overall stability of the ligand-enzyme complex.

Aromatic interactions further strengthen the binding of compound 5n within the enzyme. The indole ring participates in two π-π stacking interactions with Tyr341 (3.62 and 4.10 Å) and an additional π-π stacking interaction with Tyr124 (5.22 Å). Both residues are integral components of the aromatic network lining the active-site gorge, which is essential for π-π stacking and hydrophobic recognition of aromatic inhibitors. These interactions facilitate strong accommodation of the indole scaffold within the gorge^36,37. Moreover, the 3,5-dichlorophenyl moiety engages in π-π stacking interactions with Tyr337 (5.47 Å) and His447 (4.93 Å). Tyr337 is part of the catalytic anionic site and contributes to substrate stabilization, while His447 is a central component of the catalytic triad, directly involved in the hydrolytic mechanism of acetylcholine^40,41. The interaction with His447 is therefore particularly significant, as it suggests effective interference with the enzymatic catalytic process, providing a clear molecular rationale for the potent AChE inhibitory activity observed experimentally for compound 5n.

The 2D and 3D interaction profiles of the 5n–BChE complex are illustrated in Fig. 3, providing detailed insight into the molecular basis of the strong inhibitory activity observed experimentally. Docking analysis revealed that the thioamide moiety of compound 5n plays a central role in anchoring the ligand within the BChE active-site gorge. One of the thioamide NH groups forms a strong hydrogen bond with Ser287 at a distance of 1.69 Å, while the second NH establishes two additional hydrogen bonds with Ser287 (2.20 Å) and Asn289 (2.79 Å). These residues are positioned near the catalytic region and are known to contribute to ligand stabilization and proper orientation within the enzyme gorge, highlighting their importance in maintaining a stable ligand-enzyme complex^42,43.

Fig. 3.

Molecular docking 2D (a) and 3D (b) ligand-protein interactions of 5n–BchE complex.

Aromatic interactions further reinforce the binding of compound 5n within BChE. The indole ring engages in a π-π stacking interaction with Phe329 (5.16 Å), a residue that lines the hydrophobic cavity of the active site and facilitates aromatic recognition^44,45. In addition, the indole scaffold forms two π-π stacking interactions with Trp231 (4.62 and 4.94 Å), a key aromatic residue that plays a pivotal role in substrate guidance and stabilization within the BChE gorge^46,47. These interactions underscore the suitability of the indole core for effective engagement with the aromatic-rich environment of the enzyme.

Moreover, the 3,5-dichlorophenyl moiety establishes a π-π stacking interaction with His438 (4.95 Å), a residue located in proximity to the catalytic machinery and involved in substrate processing. Importantly, one of the chlorine atoms on this aromatic ring additionally forms a halogen bond with His438 (2.99 Å), further strengthening the ligand-enzyme interaction. Given the role of His438 as a component of the catalytic triad of BChE, these interactions are particularly significant, as they suggest effective interference with the catalytic function of the enzyme^48,49. The extensive hydrogen bonding, aromatic stacking, and halogen bonding interactions observed for compound 5n provide a compelling structural rationale for its potent BChE inhibitory activity.

The 2D and 3D interaction profiles of the 5n–MAO-A complex, presented in Fig. 4, provide detailed molecular insight into the strong inhibitory activity observed for this compound. Docking analysis revealed that the thioamide NH group of 5n forms a strong hydrogen bond with Asn181 (1.81 Å), a residue located within the substrate-binding cavity and known to contribute to ligand recognition and stabilization near the flavin adenine dinucleotide (FAD) cofactor⁵⁰. This interaction plays a key role in anchoring the ligand in a catalytically relevant orientation. In addition, sulfonamide oxygen atoms establish two hydrogen bonds with Ala68 (2.75 Å) and Tyr69 (2.71 Å). These residues are positioned at the entrance and lining of the MAO-A active site and are critically involved in shaping the binding pocket and guiding substrates toward the catalytic region. Hydrogen bonding with Ala68 and Tyr69 therefore facilitates optimal positioning of the ligand within the enzyme cavity and enhances binding stability^51,52.

Fig. 4.

Molecular docking 2D (a) and 3D (b) ligand-protein interactions of 5n–MAO-A complex.

Aromatic interactions further dominate the binding mode of 5n in MAO-A. The indole ring engages in two π-π stacking interactions with Tyr407 (3.70 and 3.99 Å) and an additional two π-π stacking interactions with Tyr444 (3.46 and 4.32 Å). Both Tyr407 and Tyr444 are key aromatic residues that line the hydrophobic substrate-binding pocket and are essential for π-π stacking interactions with aromatic inhibitors. These extensive aromatic contacts enable strong hydrophobic and electronic complementarity between the indole scaffold and the MAO-A active site, effectively stabilizing the ligand in close proximity to the FAD cofactor^53,54.

Molecular docking validation

Docking validation was carried out using self-docking (redocking) of the co-crystallized ligands into their corresponding active sites of MAO-A (PDB: 2Z5X)⁵², AChE (PDB: 4M0F)⁵⁵, and BChE (PDB: 6EQP)⁵⁶ structures obtained from the Protein Data Bank. The MAO-A crystal structure (2Z5X) was resolved at 2.20 Å with harmine bound, AChE (4M0F) at 2.30 Å with territrem B, and BChE (6EQP) at 2.35 Å with ethopropazine as the co-crystallized ligand. For each protein, the original co-crystallized ligand (green) and the redocked ligand pose (pink) were superimposed, and RMSD values were calculated to evaluate docking accuracy. Redocking of harmine in MAO-A (2Z5X) produced an RMSD of 0.4744 Å, while territrem B in AChE (4M0F) yielded an RMSD of 0.5382 Å. For BChE (6EQP), ethopropazine redocked with an RMSD of 0.9550 Å (Fig. 5). Since all RMSD values were below the acceptable threshold of 2.0 Å, the docking protocol was validated, confirming its reliability in accurately reproducing experimentally observed binding conformations.

Fig. 5.

Superposition of co-crystallized (green) and redocked (pink) ligands in (a) MAO-A (2Z5X), (b) AChE (4M0F), and (c) BChE (6EQP) active sites.

Molecular dynamics simulations

Molecular dynamics (MD) simulations are widely employed to investigate the time-dependent stability and dynamic behavior of ligand-protein complexes under conditions that closely mimic the physiological environment. Unlike static docking approaches, MD simulations provide detailed insight into conformational flexibility, interaction persistence, and structural stability of complexes over time^57,58. In this study, MD simulations were performed to validate the docking results, assess the stability of the selected ligand-enzyme complexes (5n–AchE, 5n–BchE, and 5n–MAO-A), and gain a deeper understanding of the dynamic interactions governing binding behavior. The obtained MD trajectories allowed for a comprehensive evaluation of key parameters such as structural deviations and interaction consistency throughout the simulation period.

The stability of the 5n–AChE complex was further evaluated by a 250 ns molecular dynamics simulation, and the time-dependent interaction profile is summarized in Fig. 6. During the simulation, the thioamide moiety of compound 5n exhibited consistent hydrogen-bonding behavior. The two thioamide NH groups formed water-mediated hydrogen bonds with Ser239, showing occupancies of 62% and 35%, while the thioamide sulfur participated in hydrogen-bond interactions with Tyr72 (22%), Thr75 (17%), and Tyr341 (25%), either directly or via water bridges. Aromatic interactions were highly persistent throughout the simulation. The indole ring displayed a dominant π-π stacking interaction with Tyr341, maintained for 99% of the simulation time. Additional π-π stacking interactions involving the indole moiety were observed with Tyr124 (89%) and Phe338 (35%). Furthermore, the 3,5-dichlorophenyl ring engaged in π-π stacking interactions with Trp86 (28%) and His447 (17%) (Fig. 6a).

Fig. 6.

The 250 ns MD simulation analysis of 5n–AChE complex. (a) 2D key ligand-protein interactions, (b) RMSD of ligand and protein atoms, (c) RMSF of protein atoms, (d) RMSF of ligand atoms, (e) fractional interaction histogram.

The average RMSD of the protein Cα atoms was 1.4 Å, indicating that the overall protein backbone remained structurally stable throughout the simulation. The ligand RMSD averaged 2.4 Å, with a deviation of 2.0 Å, suggesting moderate conformational flexibility of compound 5n within the binding pocket (Fig. 6b). The average RMSF value of the protein Cα atoms was 0.6 Å, indicating limited residue-level fluctuations and overall structural rigidity during the simulation (Fig. 6c). This low fluctuation profile consists of a stable protein-ligand complex. The average RMSF value of the ligand was 1.5 Å, indicating limited positional fluctuations and a stable binding mode within the AChE active site throughout the simulation (Fig. 6d). Additionally, as illustrated in Fig. 6c, the green vertical markers denote nearly twenty persistent protein-ligand contacts maintained throughout the simulation, further supporting the sustained and well-defined binding of compound 5n within the AChE active site.

Figure 6e depicts an interaction histogram summarizing the type and frequency of contacts established between the ligand and AChE residues throughout the 250 ns MD simulation. This analysis provides a concise overview of the dominant and persistent interaction patterns governing complex stability. Among the interacting residues, Tyr341, Phe338, Ser293, and Tyr124 exhibit the highest interaction frequencies, highlighting their central contributions to maintaining the ligand firmly anchored within the active site during the simulation.

Figure 7 illustrates the molecular dynamics analysis of the 5n–BChE complex. The interaction profile reveals highly persistent hydrogen bonding and aromatic interactions that collectively contribute to the stability of the complex. The thioamide NH groups form two strong hydrogen bonds with Ser287, exhibiting high occupancies of 96% and 80%, indicating their dominant role in maintaining ligand anchoring.

Fig. 7.

The 250 ns MD simulation analysis of 5n–BChE complex. (a) 2D key ligand-protein interactions, (b) RMSD of ligand and protein atoms, (c) RMSF of protein atoms, (d) RMSF of ligand atoms, (e) fractional interaction histogram.

In addition, the thioamide sulfur and imine nitrogen engage in water-mediated hydrogen bonds with Pro285, with occupancies of 49% and 43%, while the sulfonamide oxygen establishes a water-bridged hydrogen bond with Thr120 (52%). Aromatic interactions further stabilize the complex, as the indole ring participates in π-π stacking with Trp231 (61%) and Phe329 (45%). Notably, the 3,5-dichlorophenyl moiety shows strong π-π stacking interactions with Phe329 (78%) and His438 (70%), reflecting its significant contribution to binding persistence (Fig. 7a). Amino acids Ser287, Phe329, Pro285, Trp82, and His438 emerge as the most frequently interacting residues throughout the simulation (Fig. 7e).

From a dynamic stability perspective, the complex exhibits low structural fluctuations, with an average Cα RMSD of 1.0 Å for the protein and an average ligand RMSD of 2.0 Å. The ligand RMSD deviation remains limited to 1.0 Å, supporting a stable binding pose during the simulation (Fig. 7b). RMSF analysis further confirms this behavior, showing low average fluctuations for both the protein (0.6 Å) and the ligand (1.5 Å) (Fig. 7c and d). Consistently, nearly twenty persistent protein-ligand contacts were maintained over the simulation, underscoring the overall stability and robustness of the 5n–BChE complex.

Figure 8 presents the molecular dynamics analysis of the 5n–MAO-A complex over a 250 ns simulation period. The interaction profile is dominated by persistent hydrogen bonding and aromatic contacts that collectively stabilize the ligand within the MAO-A active site. One of the thioamide NH groups forms a highly stable hydrogen bond with Asn181, exhibiting a high occupancy of 94%, while the second NH participates in a water-mediated hydrogen bond with Gln215 (43%). In addition, the thioamide sulfur establishes a water-bridged hydrogen bond with Asn181, with an occupancy of 32%. The sulfonamide oxygen further contributes to binding stability through a direct hydrogen bond with Met445 (49%). Aromatic interactions play a complementary role in ligand stabilization. The indole moiety engages in π-π stacking interactions with Tyr407 (30% and 22%) and shows a particularly persistent π-π stacking interaction with Tyr444 (77%). Moreover, the 3,5-dichlorophenyl ring forms a π-π interaction with Tyr407 (28%) and a cation-π interaction with Lys305 (11%), adding to the overall interaction diversity observed throughout the simulation (Fig. 8a). Consistently, Asn181, Tyr407, Tyr444, Gln215, and Met445 display the highest interaction frequencies over the trajectory (Fig. 8e).

Fig. 8.

The 250 ns MD simulation analysis of 5n–MAO-A complex. (a) 2D key ligand-protein interactions, (b) RMSD of ligand and protein atoms, (c) RMSF of protein atoms, (d) RMSF of ligand atoms, (e) fractional interaction histogram.

From a dynamic stability standpoint, the 5n–MAO-A complex remains well equilibrated during the simulation, with an average Cα RMSD of 2.5 Å for the protein and an average ligand RMSD of 2.5 Å. The ligand RMSD deviation is limited to 1.0 Å, indicating the preservation of a stable binding pose (Fig. 8b). RMSF analysis supports this observation, revealing moderate and uniform flexibility for both the protein and the ligand, with average RMSF values of 1.0 Å for each. Approximately fifteen persistent protein-ligand contacts are maintained throughout the simulation (Fig. 8c,d).

MM-GBSA energy decomposition analysis

To gain deeper insight into the energetic contributions governing ligand-protein stabilization, MM-GBSA binding free energy decomposition analysis was performed. This approach enables the quantitative dissection of total binding free energy into individual energetic components, thereby elucidating the relative roles of van der Waals interactions, electrostatic forces, and solvation effects in complex formation. Such analysis provides a mechanistic understanding of the driving forces responsible for ligand affinity and complements both docking and molecular dynamics results⁵⁹. In this context, energy decomposition analyses of the 5n–AChE, 5n–BChE, and 5n–MAO-A complexes were carried out, and the detailed results are summarized in Table 4.

Table 4.

MM-GBSA energy decomposition analysis of 5n–AChE, 5n–BChE, and 5n–MAO-A complexes.

Energy decomposition (kcal/mol)	5n–AChE	5n–BChE	5n–MAO-A
MM-GBSA ΔG Bind Coulomb	13.59	9.37	3.22
MM-GBSA ΔG Bind Covalent	5.64	2.92	4.91
MM-GBSA ΔG Bind Hbond	-1.08	-1.14	-0.96
MM-GBSA ΔG Bind Lipo	-32.31	-25.55	-37.10
MM-GBSA ΔG Bind Solv GB	13.77	29.65	32.61
MM-GBSA ΔG Bind vdW	-72.83	-60.68	-76.41

For all three targets, van der Waals (vdW) interactions represent the major driving force for binding, with highly favorable contributions observed for AChE (-72.83 kcal/mol), BChE (-60.68 kcal/mol), and MAO-A (-76.41 kcal/mol). This finding is consistent with the extensive π-π stacking and hydrophobic contacts identified in docking and MD interaction analyses.

Lipophilic contributions further support complex formation, particularly in the 5n–MAO-A complex, which exhibited the most favorable lipo term (-37.10 kcal/mol), followed by AChE (-32.31 kcal/mol) and BChE (-25.55 kcal/mol). These results indicate that hydrophobic packing within the enzyme active sites plays a critical role in ligand stabilization.

Hydrogen bonding contributions were modest yet consistently favorable across all complexes (-0.96 to -1.14 kcal/mol), suggesting that hydrogen bonds primarily serve to orient and stabilize the ligand rather than dominate binding energetics. In contrast, electrostatic (Coulomb) and solvation (GB) terms contributed unfavorably, reflecting the energetic penalty associated with desolvation upon ligand binding, an effect commonly observed in hydrophobic binding pockets.

As a result, the energy decomposition profiles reinforce that the binding of compound 5n to AChE, BChE, and MAO-A is predominantly governed by vdW and lipophilic interactions, in strong agreement with the structural and dynamic interaction patterns observed in molecular docking and MD simulations.

ADME predictions

To further assess the drug-likeness and pharmacokinetic feasibility of the synthesized compounds, in silico ADME (Absorption, Distribution, Metabolism, and Excretion) predictions were performed. ADME analysis is a crucial step in early-stage drug discovery, as it provides valuable insight into a compound’s oral bioavailability, membrane permeability, metabolic stability, and overall pharmacokinetic behavior prior to costly in vivo studies. This approach enables the identification of potential liabilities related to absorption or distribution while guiding the selection of promising lead candidates with favorable drug-like profiles^60–62. In the present study, the predicted ADME properties of the compounds and reference inhibitors were evaluated, and the obtained results are summarized in Table 5.

Table 5.

ADME prediction of the compounds and reference inhibitors.

Compounds	MW	aHB	dHB	QPlogPo/w	QPlogBB	QPlogS	QPPCaco	QPPMDCK	%HOA	Ro5	Ro3
5a	427.32	9	3	2.634	-0.970	-5.411	251	1621	85	0	0
5b	441.35	9	2	3.498	-0.455	-5.896	769	5393	100	0	1
5c	469.40	9	2	4.312	-0.399	-6.759	1095	7799	100	0	1
5d	483.43	9	2	4.723	-0.458	-7.058	1153	7768	100	0	1
5e	509.47	9	2	5.136	-0.485	-8.067	1034	7963	85	2	1
5f	517.45	9	2	5.116	-0.402	-7.014	1108	8618	85	2	1
5g	535.44	9	2	5.544	-0.457	-8.171	991	10,000	87	2	1
5 h	531.47	9	2	5.625	-0.610	-8.405	960	7334	87	2	1
5i	503.42	9	2	4.840	-0.703	-7.575	734	4484	94	1	1
5j	521.41	9	2	5.071	-0.570	-7.873	756	8442	82	2	1
5k	537.87	9	2	5.327	-0.469	-8.131	868	10,000	85	2	1
5l	537.87	9	2	5.324	-0.553	-8.296	733	10,000	83	2	1
5m	537.87	9	2	5.259	-0.514	-8.081	766	10,000	83	2	1
5n	572.31	9	2	5.745	-0.340	-8.713	872	10,000	87	2	1
5o	582.32	9	2	5.400	-0.544	-8.407	733	10,000	84	2	1
5p	548.42	10	2	4.079	-1.908	-7.524	93	451	73	1	1
5q	531.47	9	2	5.488	-0.602	-8.485	932	5927	86	2	1
5r	531.47	9	2	5.327	-0.563	-7.983	971	5258	86	2	1
5s	533.45	9	2	4.909	-0.798	-7.730	729	4283	94	1	1
5t	533.45	9	2	4.886	-0.736	-7.596	791	4654	94	1	1
Galantamine	287.36	5	1	2.114	0.443	-2.386	900	488	92	0	0
Clorgyline	272.17	3	1	4.076	0.832	-3.671	2222	7443	100	0	0
Sorafenib	464.83	6	3	4.102	-0.997	-7.058	323	1713	95	0	1

MW: 130–725 (molecular weight); dHB: 0–6 (H-bond donors); aHB: 2–20 (H-bond acceptors); QPlogPo/w: -2–6.5 (octanol/water partition coefficient); QPlogS: -6.5–0.5 (aqueous solubility, log S); QPPCaco: <25 poor, > 500 great (intestinal permeability); QPlogBB: -3–1.2 (brain/blood partition); QPPMDCK: <25 poor, > 500 great (BBB permeability); %HOA: >80 high, < 25 poor (oral absorption); Ro5: ≤4 (Lipinski); Ro3: ≤3 (Jorgensen).

The ADME predictions indicate that the synthesized thiosemicarbazone derivatives generally exhibit acceptable drug-like and pharmacokinetic profiles within the recommended ranges (Table 5). The molecular weights of the compounds (427–582 g/mol) are higher than those of the reference inhibitors galantamine and clorgyline but remain within the acceptable upper limit for orally active small molecules. Most derivatives display limited Lipinski and Jorgensen rule violations, with no compound exceeding two Ro5 violations and only a single Ro3 violation observed for most of the series.

Lipophilicity values (QPlogP_o/w) ranged from moderate to high (2.63–5.75), exceeding that of galantamine (2.11) but comparable to clorgyline (4.08) and sorafenib (4.10). This increased lipophilicity is consistent with the strong hydrophobic and van der Waals contributions observed in docking, MD, and MM-GBSA analyses. Correspondingly, aqueous solubility values (QPlogS) were lower than those of galantamine and clorgyline but remained within acceptable limits for CNS-active compounds.

Importantly, most compounds demonstrated favorable intestinal permeability, as evidenced by high QPPCaco values (> 500) comparable to or exceeding those of the reference drugs. Similarly, QPPMDCK values indicated very good membrane and BBB permeability, surpassing galantamine and approaching or exceeding clorgyline in many cases. The predicted brain/blood partition coefficients (QPlogBB) for the series fell within the optimal range for CNS penetration and were generally superior to sorafenib, supporting their suitability for Alzheimer’s disease-related targets.

Oral absorption predictions further reinforced these findings, with %HOA values exceeding 80% for nearly all compounds and approaching those of galantamine and clorgyline. Notably, the most promising multitarget inhibitor 5n displayed balanced ADME characteristics, including high intestinal and BBB permeability, acceptable lipophilicity, and minimal rule violations, comparable to or surpassing the reference inhibitors.

As a result, the ADME profiles suggest that the synthesized compounds, particularly 5n, possess favorable pharmacokinetic properties compatible with CNS drug development, supporting their further consideration as multitarget therapeutic candidates for Alzheimer’s disease.

Density functional theory (DFT) analysis

Geometry optimization and frontier molecular orbitals

The optimized geometries and frontier molecular orbitals (FMO) of in vitro most active five compounds, 5h, 5l, 5m, 5n, and 5o were calculated using the DFT/B3LYP method with the 6-31G basis set to gain insight into their electronic properties and reactivity^63,64. The calculated HOMO and LUMO energy levels, along with the corresponding HOMO–LUMO energy gaps (ΔE), are summarized in Table 6. Both compounds exhibit negative HOMO and LUMO energies, indicating their thermodynamic stability and suitability for participating in electronic interactions and charge-transfer processes relevant to biological activity.

Table 6.

HOMO-LUMO energies of selected compounds.

Compounds	HOMO (eV)	LUMO (eV)	ΔE (eV)
5h	-0.190579	-0.092139	0.098440
5l	-0.210380	-0.096408	0.113972
5m	-0.212324	-0.096612	0.115712
5n	-0.213397	-0.097120	0.116277
5o	-0.208988	-0.097075	0.111913

The FMO results in Table 6 demonstrate that all compounds (5h, 5l, 5m, 5n, and 5o) exhibit negative HOMO and LUMO energies, confirming their thermodynamic stability and electronic suitability for biomolecular interactions. The HOMO–LUMO gaps range between 0.098 and 0.116 eV, indicating relatively high electronic responsiveness across the series. Notably, compound 5 h shows the lowest ΔE (0.098 eV), suggesting the highest electron mobility and reactivity, whereas 5n presents the highest ΔE (0.116 eV), indicating relatively greater stability and reduced softness. Compounds 5l (0.1139 eV), 5m (0.1157 eV), and 5o (0.1119 eV) display intermediate gaps, reflecting a balanced reactivity profile. These values imply that subtle structural differences modulate the electronic behavior of the compounds while maintaining favorable reactivity characteristics relevant to biological activity. The frontier molecular orbital distributions of the selected most active compounds are illustrated in Fig. 9.

Fig. 9.

Frontier molecular orbital (HOMO–LUMO) distributions of compounds 5h, 5l, 5m, 5n, and 5o.

The FMO distributions clearly demonstrate that the HOMO orbitals of all five compounds are predominantly localized over the thiosemicarbazone moiety, particularly around the C = S functional group, indicating that this region is the primary electron-donating and reactive site during nucleophilic interactions. In contrast, the LUMO orbitals are mainly concentrated on the 3,5-dichlorobenzenesulfonamide fragment, highlighting this portion as the preferred electron-accepting region responsible for electrophilic interactions and charge-transfer processes.

Molecular electrostatic potential analysis

The molecular electrostatic potential (MEP) maps of compounds 5h, 5l, 5m, 5n, and 5o and related data are given in Table 7; Fig. 10 respectively. They clearly illustrate the charge distribution pattern governing their potential interaction behavior. In all molecules, the most negative ESP regions (red zones) are predominantly localized around the sulfonyl oxygen atoms and thiosemicarbazone functionalities, reflecting strong nucleophilic character and a high tendency to form hydrogen bonds or electrostatic interactions with positively charged or polar amino acid residues.

Table 7.

ESP descriptors of compounds 5h, 5l, 5m, 5n, and 5o.

Compounds	ESP local polarity (eV)	ESP max (eV)	ESP min (eV)	ESP neg mean (eV)	ESP pos mean (eV)
5h	0.5885	21.669	−2.2584	−0.6643	0.5590
5l	0.5798	27.324	−1.8330	−0.5355	0.6227
5m	0.5737	28.000	−1.5498	−0.5165	0.6275
5n	0.5243	25.750	−1.8230	−0.4848	0.5629
5o	0.5685	27.098	−1.8026	−0.5260	0.6101

Fig. 10.

Molecular electrostatic potential (MEP) maps of compounds 5h, 5l, 5m, 5n, and 5o.

This observation is consistent with the ESPmin values, which range from − 2.2584 eV (5h) to -1.5498 eV (5m), indicating pronounced electron-rich domains particularly in 5h. Conversely, the positive ESP regions (blue zones) are mainly positioned over hydrogen atoms and aromatic frameworks, consistent with ESPmax values between 21.669 and 28.000 eV, indicating potential electrophilic interaction sites. Among the series, 5h exhibits the highest local polarity (0.5885 eV), suggesting the strongest overall charge separation and potential for stronger electrostatic complementarity in biological environments, while 5n shows the lowest polarity (0.5243 eV), implying comparatively reduced charge contrast. The mean negative and positive ESP values further support this balanced donor-acceptor character across the molecules, collectively indicating favorable electrostatic properties that may facilitate stable ligand-protein interactions.

Global chemical reactivity (GCR) descriptors

Global chemical reactivity (GCR) descriptors, including electronegativity (χ), chemical potential (µ), hardness (η), softness (S), and electrophilicity (ω), provide insights into a molecule’s reactivity, stability, and potential bioactivity. They are useful for predicting interactions with enzymes or receptors and guiding drug design⁶⁵. The GCR descriptors of the most active derivatives are summarized in Table 8.

Table 8.

GCR descriptors* of compounds 5h, 5l, 5m, 5n, and 5o.

Compounds	ΔE (eV)	µ (eV)	η (eV)	S (eV− 1)	χ (eV)	ω (eV)
5h	0.098440	−0.141359	0.049220	10.158	0.141359	0.203
5l	0.113972	−0.153394	0.056986	8.774	0.153394	0.206
5m	0.115712	−0.154468	0.057856	8.642	0.154468	0.206
5n	0.116277	−0.155258	0.058139	8.600	0.155258	0.207
5o	0.111913	−0.153031	0.055957	8.936	0.153031	0.209

*GCR descriptors: Energy Gap (ΔE) = E_LUMO - E_HOMO; Chemical Potential (µ) = (E_HOMO + E_LUMO)/2; Global Hardness (η) = (E_LUMO - E_HOMO)/2; Global Softness (S) = 1/2η; Electronegativity (χ) = -1/2 (E_HOMO + E_LUMO); Global Electrophilicity Index (ω) = µ²/2η.

According to the GCR data given in Table 8, all molecules exhibit small ΔE values (0.098–0.116 eV), indicating high electronic reactivity and good charge-transfer capability, which is consistent with their biological potential. Among them, 5h displays the lowest energy gap and highest softness (S = 10.158 eV^− 1), suggesting the greatest electronic flexibility and highest reactivity. In contrast, 5n shows the highest hardness (η = 0.058139 eV) and lowest softness, implying comparatively greater kinetic stability. Compounds 5l, 5m, and 5o exhibit intermediate ΔE and η values, indicating balanced stability-reactivity characteristics.

All compounds possess negative µ values and corresponding positive χ values, confirming their electron-accepting capability, while the electrophilicity index (ω = 0.203–0.209 eV) shows only slight variation, suggesting a relatively similar electrophilic power across the series. These results demonstrate that subtle structural modifications fine-tune the global reactivity of the molecules, with 5h being the most electronically adaptable and 5n the most stable within the series.

Conclusion

In this study, a novel series of indole-based thiosemicarbazone derivatives was designed, synthesized, and evaluated as multitarget candidates for Alzheimer’s disease. The compounds exhibited potent inhibitory activity against AChE, BChE, and MAO-A, with several derivatives surpassing the reference inhibitors. Cytotoxicity studies demonstrated selective antiproliferative effects toward SH-SY5Y cells while showing relatively lower toxicity against HUVEC cells, indicating a favorable preliminary safety profile. Among the series, compound 5n emerged as the most promising multitarget candidate. Experimental findings were supported by in silico analyses, including molecular docking, MM-GBSA, and molecular dynamics simulations, which confirmed stable ligand-enzyme interactions. DFT calculations further provided insights into the electronic properties and reactivity profiles of the most active compounds. ADME predictions suggested that the compounds possess properties consistent with potential CNS-active agents.

The thiosemicarbazone linker employed in this study is generally stable under physiological pH and temperature, as supported by literature reports. Although hydrolysis or degradation can occur under strongly acidic or oxidative conditions, such environments are unlikely in vivo. This stability profile supports the scaffold’s suitability for early-stage drug development, while potential metabolic liabilities should be considered in future pharmacokinetic optimization studies.

Despite these promising results, certain limitations remain. MAO-B inhibitory activity was not assessed, limiting the evaluation of selectivity, and pharmacokinetic properties were predicted in silico without in vivo validation. Therefore, further studies, including MAO-B inhibition assays, in vivo pharmacokinetic and toxicity evaluations, and additional mechanistic investigations, are warranted to fully establish the therapeutic potential of this compound series.

The results indicate that the indole-thiosemicarbazone scaffold provides a promising framework for the development of multitarget-directed ligands against Alzheimer’s disease and serves as a solid foundation for future optimization studies.

Materials and methods

Chemistry

All chemicals used in this study were obtained from various commercial suppliers. Melting points of the synthesized compounds were measured using a WRS-2 A Microprocessor Melting-point Apparatus and are reported without correction. ¹H NMR spectra were acquired using a Bruker 400 MHz spectrometer, while ¹³C NMR spectra were obtained on a Bruker 100 MHz instrument. Chemical shifts are reported in δ (ppm) relative to tetramethylsilane (TMS, δ 0.00 singlet) using deuterated dimethyl sulfoxide (DMSO-d₆) as solvents. HRMS data were acquired via Thermo Fisher Scientific Q Exactive™ Hybrid Quadrupole-Orbitrap™ instrument. HPLC chromatograms were recorded using the Waters preparative HPLC and PDA detector.

Synthesis

Synthesis of 1-((3,5-dichlorophenyl)sulfonyl)-1H-indole-3-carbaldehyde (3)

Indole-3-carbaldehyde (25 mmol) was dissolved in THF (40 mL), and 3,5-dichlorobenzenesulfonyl chloride (25 mmol) was added. The reaction mixture was cooled in an ice bath, and a solution of triethylamine (30 mmol) in 20 mL THF was added dropwise under stirring. Upon completion of the addition, the mixture was refluxed for three hours, then allowed to reach room temperature and filtered. The solvent was removed under reduced pressure, and the resulting crude product was purified by recrystallization from ethanol to afford the desired sulfonamide intermediate (Scheme 2)⁶⁶.

Synthesis of target thiosemicarbazone derivatives (5a-t)

Intermediate 3 (1 mmol), was dissolved in methanol (20 mL), and about 3–4 drops of glacial acetic acid were added as a catalyst. Then, the thiosemicarbazide derivative (4a-t) (1 mmol) was put into the reaction mixture, which was then refluxed for some 4–6 h. After completion, the mixture was cooled to room temperature, and the resulting crude product was collected by filtration and purified through recrystallization from ethanol to afford the desired thiosemicarbazone derivatives (5a-t) (Scheme 2)⁶⁷.

(E)-2-((1-((3,5-Dichlorophenyl)sulfonyl)-1 H-indol-3-yl)methylene)-2l4-diazane-1-carbothioamide (5a)

Yellow solid, yield: 90%, mp: 236–238 °C. ¹H NMR (400 MHz, DMSO) δ 11.54 (s, 1H), 8.41 (s, 1H), 8.35 (d, J = 7.8 Hz, 1H), 8.28 (s, 2 H), 8.17 (d, J = 1.8 Hz, 2 H), 8.05–8.02 (m, 2 H), 7.65 (s, 1H), 7.47 (t, J = 7.8 Hz, 1H), 7.37 (t, J = 7.9 Hz, 1H). ¹³C NMR (101 MHz, DMSO) δ 178.0, 139.8, 138.0, 136.1, 135.2, 135.0, 130.6, 127.1, 126.6, 126.0, 125.3, 124.2, 118.8, 113.5. HRMS-ESI (m/z): chemical formula: C₁₆H₁₃Cl₂N₄O₂S₂, calculated [M + H]⁺: 426.9857, found: 426.9850. HPLC-PDA: λ 300 nm, MeCN: MeOH (1:1), Rt: 7.75 min, 98.24%.

(E)-2-((1-((3,5-Dichlorophenyl)sulfonyl)-1 H-indol-3-yl)methylene)-N-methylhydrazine-1-carbothioamide (5b)

Off-white solid, yield: 80%, mp: 250–252 °C. ¹H NMR (400 MHz, DMSO) δ 11.55 (s, 1H), 8.39 (s, 1H), 8.37 (d, J = 7.8 Hz, 1H), 8.29 (s, 1H), 8.17 (s, 2 H), 8.11–8.02 (m, 3 H), 7.48 (t, J = 8.3 Hz, 1H), 7.40 (t, J = 7.9 Hz, 1H), 3.08 (d, J = 4.5 Hz, 3 H). ¹³C NMR (101 MHz, DMSO) δ 177.9, 139.8, 137.7, 136.2, 135.2, 135.0, 130.5, 127.1, 126.6, 126.0, 125.2, 124.1, 118.9, 113.6, 31.7. HRMS-ESI (m/z): chemical formula: C₁₇H₁₅Cl₂N₄O₂S₂, calculated [M + H]⁺: 441.0013, found: 441.0002. HPLC-PDA: λ 300 nm, MeCN: MeOH (1:1), Rt: 7.42 min, 99.31%.

(E)-2-((1-((3,5-Dichlorophenyl)sulfonyl)-1 H-indol-3-yl)methylene)-N-isopropylhydrazine-1-carbothioamide (5c)

White solid, yield: 83%, mp: 232–234 °C. ¹H NMR (400 MHz, DMSO) δ 11.57 (s, 1H), 8.42 (s, 1H), 8.30 (s, 1H), 8.17 (d, J = 1.8 Hz, 2 H), 8.15 (s, 1H), 8.08 (d, J = 8.2 Hz, 1H), 7.65 (d, J = 8.4 Hz, 1H), 7.49 (t, J = 8.3 Hz, 1H), 7.43 (t, J = 7.8 Hz, 1H), 4.48 (dq, J = 13.2, 6.6 Hz, 1H), 1.27 (d, J = 6.6 Hz, 6 H). ¹³C NMR (101 MHz, DMSO) δ 176.1, 139.7, 137.5, 136.1, 135.1, 130.3, 127.2, 126.6, 126.0, 125.3, 123.3, 118.9, 113.8, 46.0, 22.4. HRMS-ESI (m/z): chemical formula: C₁₉H₁₉Cl₂N₄O₂S₂, calculated [M + H]⁺: 469.0326, found: 469.0318. HPLC-PDA: λ 300 nm, MeCN: MeOH (1:1), Rt: 6.64 min, 97.79%.

(E)-2-((1-((3,5-Dichlorophenyl)sulfonyl)-1 H-indol-3-yl)methylene)-N-isobutylhydrazine-1-carbothioamide (5d)

Yellow solid, yield: 89%, mp: 207–209 °C. ¹H NMR (400 MHz, DMSO) δ 11.56 (s, 1H), 8.40 (s, 1H), 8.30 (s, 1H), 8.26 (d, J = 7.8 Hz, 1H), 8.16 (d, J = 1.8 Hz, 2 H), 8.07–8.01 (m, 3 H), 7.48 (t, J = 8.3 Hz, 1H), 7.39 (t, J = 8.0 Hz, 1H), 3.47 (t, J = 6.5 Hz, 2 H), 2.01 (dp, J = 13.5, 6.8 Hz, 1H), 0.92 (d, J = 6.8 Hz, 6 H). ¹³C NMR (101 MHz, DMSO) δ 177.4, 139.7, 137.6, 136.2, 135.2, 135.1, 130.5, 127.2, 126.7, 126.0, 125.2, 123.7, 118.9, 113.7, 51.2, 28.3, 20.4. HRMS-ESI (m/z): chemical formula: C₂₀H₂₁Cl₂N₄O₂S₂, calculated [M + H]⁺: 483.0483, found: 483.0472. HPLC-PDA: λ 300 nm, MeCN: MeOH (1:1), Rt: 6.77 min, 98.29%.

(E)-2-((1-((3,5-Dichlorophenyl)sulfonyl)-1 H-indol-3-yl)methylene)-N-cyclohexylhydrazine-1-carbothioamide (5e)

Yellow solid, yield: 89%, mp: 228–230 °C. ¹H NMR (400 MHz, DMSO) δ 11.60 (s, 1H), 8.41 (s, 1H), 8.29 (s, 1H), 8.17 (d, J = 1.8 Hz, 2 H), 8.12 (d, J = 7.6 Hz, 1H), 8.07 (d, J = 8.2 Hz, 1H), 8.02 (t, J = 1.8 Hz, 1H), 7.64 (d, J = 8.4 Hz, 1H), 7.48 (t, J = 7.7 Hz, 1H), 7.42 (t, J = 7.1 Hz, 1H), 4.20–4.12 (m, 1H), 1.92 (d, J = 9.0 Hz, 2 H), 1.70 (d, J = 12.7 Hz, 2 H), 1.58 (d, J = 12.3 Hz, 1H), 1.48–1.19 (m, 5 H). ¹³C NMR (101 MHz, DMSO) δ 176.0, 139.7, 137.5, 136.1, 135.2, 135.1, 130.5, 127.2, 126.7, 126.0, 125.3, 123.2, 118.8, 113.8, 52.6, 32.1, 25.5, 25.0. HRMS-ESI (m/z): chemical formula: C₂₂H₂₃Cl₂N₄O₂S₂, calculated [M + H]⁺: 509.0639, found: 509.0630. HPLC-PDA: λ 300 nm, MeCN: MeOH (1:1), Rt: 6.86 min, 99.63%.

(E)-2-((1-((3,5-Dichlorophenyl)sulfonyl)-1 H-indol-3-yl)methylene)-N-benzylhydrazine-1-carbothioamide (5f)

Yellow solid, yield: 86%, mp: 216–218 °C. ¹H NMR (400 MHz, DMSO) δ 11.71 (s, 1H), 8.63 (t, J = 6.1 Hz, 1H), 8.42 (s, 1H), 8.32 (d, J = 6.5 Hz, 2 H), 8.18 (d, J = 1.8 Hz, 2 H), 8.05 (d, J = 8.7 Hz, 2 H), 7.47 (t, J = 7.5 Hz, 1H), 7.38–7.22 (m, 6 H), 4.90 (d, J = 6.1 Hz, 2 H). ¹³C NMR (101 MHz, DMSO) δ 177.8, 139.9, 139.7, 138.1, 136.2, 135.2, 135.0, 130.7, 128.7, 127.4, 127.2, 126.7, 126.0, 125.2, 123.9, 118.8, 113.6, 47.2. HRMS-ESI (m/z): chemical formula: C₂₃H₁₉Cl₂N₄O₂S₂, calculated [M + H]⁺: 517.0326, found: 517.0320. HPLC-PDA: λ 300 nm, MeCN: MeOH (1:1), Rt: 7.07 min, 95.34%.

(E)-2-((1-((3,5-Dichlorophenyl)sulfonyl)-1 H-indol-3-yl)methylene)-N-(4-fluorobenzyl)hydrazine-1-carbothioamide (5 g)

White solid, yield: 89%, mp: 224–226 °C. ¹H NMR (400 MHz, DMSO) δ 11.70 (s, 1H), 8.65 (t, J = 6.2 Hz, 1H), 8.42 (s, 1H), 8.33 (d, J = 6.1 Hz, 2 H), 8.17 (d, J = 1.8 Hz, 2 H), 8.06–8.03 (m, 2 H), 7.48 (t, J = 7.7 Hz, 1H), 7.42–7.36 (m, 3 H), 7.16 (t, J = 8.9 Hz, 2 H), 4.88 (d, J = 6.1 Hz, 2 H). ¹³C NMR (101 MHz, DMSO) δ 177.8, 161.6 (d, J = 242.0 Hz), 139.8, 138.2, 136.1 (d, J = 12.4 Hz), 135.1 (d, J = 14.4 Hz), 130.6, 129.5 (d, J = 8.0 Hz), 127.1, 126.6, 126.0, 125.2, 123.9, 118.8, 115.4 (d, J = 21.2 Hz), 113.6, 46.5. HRMS-ESI (m/z): chemical formula: C₂₃H₁₈Cl₂FN₄O₂S₂, calculated [M + H]⁺: 535.0232, found: 535.0221. HPLC-PDA: λ 300 nm, MeCN: MeOH (1:1), Rt: 7.3 min, 95.29%.

(E)-2-((1-((3,5-Dichlorophenyl)sulfonyl)-1 H-indol-3-yl)methylene)-N-(4-methylbenzyl)hydrazine-1-carbothioamide (5 h)

Off-white solid, yield: 85%, mp: 222–224 °C. ¹H NMR (400 MHz, DMSO) δ 11.68 (s, 1H), 8.57 (t, J = 6.2 Hz, 1H), 8.41 (s, 1H), 8.32–8.30 (m, 2 H), 8.17 (d, J = 1.8 Hz, 2 H), 8.05 (d, J = 8.3 Hz, 1H), 8.02 (t, J = 1.8 Hz, 1H), 7.47 (t, J = 8.3 Hz, 1H), 7.35 (t, J = 7.9 Hz, 1H), 7.24 (d, J = 8.0 Hz, 2 H), 7.13 (d, J = 7.9 Hz, 2 H), 4.85 (d, J = 6.1 Hz, 2 H), 2.27 (s, 3 H). ¹³C NMR (101 MHz, DMSO) δ 177.7, 139.7, 138.0, 136.7, 136.2, 136.1, 135.2, 135.0, 130.6, 129.2, 127.5, 127.1, 126.6, 126.0, 125.2, 123.9, 118.8, 113.6, 47.0, 21.1. HRMS-ESI (m/z): chemical formula: C₂₄H₂₁Cl₂N₄O₂S₂, calculated [M + H]⁺: 531.0483, found: 531.0473. HPLC-PDA: λ 300 nm, MeCN: MeOH (1:1), Rt: 6.55 min, 99.64%.

(E)-2-((1-((3,5-Dichlorophenyl)sulfonyl)-1 H-indol-3-yl)methylene)-N-phenylhydrazine-1-carbothioamide (5i)

Yellow solid, yield: 90%, mp: 232–234 °C. ¹H NMR (400 MHz, DMSO) δ 11.92 (s, 1H), 9.79 (s, 1H), 8.49 (s, 1H), 8.40 (s, 1H), 8.33 (d, J = 7.8 Hz, 1H), 8.18 (d, J = 1.8 Hz, 2 H), 8.06 (d, J = 8.3 Hz, 1H), 8.03 (t, J = 1.8 Hz, 1H), 7.59 (d, J = 7.6 Hz, 2 H), 7.48 (t, J = 7.4 Hz, 1H), 7.42–7.37 (m, 3 H), 7.22 (t, J = 7.4 Hz, 1H). ¹³C NMR (101 MHz, DMSO) δ 176.3, 139.8, 139.6, 138.3, 136.2, 135.2, 135.0, 130.6, 128.6, 127.2, 126.6, 126.2, 126.0, 125.8, 125.2, 123.8, 118.8, 113.6. HRMS-ESI (m/z): chemical formula: C₂₂H₁₇Cl₂N₄O₂S₂, calculated [M + H]⁺: 503.0170, found: 503.0158. HPLC-PDA: λ 210 nm, MeCN: MeOH (1:1), Rt: 6.7 min, 98.49%.

(E)-2-((1-((3,5-Dichlorophenyl)sulfonyl)-1 H-indol-3-yl)methylene)-N-(4-fluorophenyl)hydrazine-1-carbothioamide (5j)

Yellow solid, yield: 85%, mp: 230–232 °C. ¹H NMR (400 MHz, DMSO) δ 11.93 (s, 1H), 9.78 (s, 1H), 8.48 (s, 1H), 8.39 (s, 1H), 8.35 (d, J = 7.8 Hz, 1H), 8.17 (d, J = 1.8 Hz, 2 H), 8.07–8.05 (m, 2 H), 7.56 (dd, J = 8.9, 5.1 Hz, 2 H), 7.48 (t, J = 7.7 Hz, 1H), 7.39 (t, J = 7.5 Hz, 1H), 7.21 (t, J = 8.8 Hz, 2 H). HRMS-ESI (m/z): chemical formula: C₂₂H₁₆Cl₂FN₄O₂S₂, calculated [M + H]⁺: 521.0076, found: 521.0058. HPLC-PDA: λ 300 nm, MeCN: MeOH (1:1), Rt: 6.21 min, 99.63%.

(E)-2-((1-((3,5-Dichlorophenyl)sulfonyl)-1 H-indol-3-yl)methylene)-N-(2-chlorophenyl)hydrazine-1-carbothioamide (5k)

Light yellow solid, yield: 84%, mp: 222–224 °C. ¹H NMR (400 MHz, DMSO) δ 12.13 (s, 1H), 9.72 (s, 1H), 8.50 (s, 1H), 8.41 (d, J = 7.0 Hz, 2 H), 8.19 (d, J = 1.8 Hz, 2 H), 8.07 (d, J = 8.3 Hz, 1H), 8.04 (t, J = 1.8 Hz, 1H), 8.00 (dd, J = 8.0, 1.3 Hz, 1H), 7.57 (dd, J = 8.0, 1.4 Hz, 1H), 7.48 (t, J = 8.3 Hz, 1H), 7.39 (dd, J = 9.0 Hz, 2 H), 7.30 (td, J = 7.8, 1.6 Hz, 1H). ¹³C NMR (101 MHz, DMSO) δ 176.2, 139.7, 139.1, 136.7, 136.2, 135.3, 135.0, 131.4, 129.8, 129.7, 129.2, 127.9, 127.6, 127.0, 126.8, 126.0, 125.2, 123.9, 118.5, 113.7. HRMS-ESI (m/z): chemical formula: C₂₂H₁₆Cl₃N₄O₂S₂, calculated [M + H]⁺: 536.9780, found: 536.9771. HPLC-PDA: λ 300 nm, MeCN: MeOH (1:1), Rt: 6.42 min, 97.05%.

(E)-2-((1-((3,5-Dichlorophenyl)sulfonyl)-1 H-indol-3-yl)methylene)-N-(4-chlorophenyl)hydrazine-1-carbothioamide (5 L)

Yellow solid, yield: 85%, mp: 231–233 °C. ¹H NMR (400 MHz, DMSO) δ 11.99 (s, 1H), 9.84 (s, 1H), 8.49 (s, 1H), 8.40 (s, 1H), 8.33 (d, J = 7.9 Hz, 1H), 8.17 (d, J = 1.8 Hz, 2 H), 8.06 (d, J = 8.3 Hz, 1H), 8.02 (t, J = 1.8 Hz, 1H), 7.63 (d, J = 8.8 Hz, 2 H), 7.48 (t, J = 8.2 Hz, 1H), 7.43 (d, J = 8.7 Hz, 2 H), 7.39 (t, J = 7.7 Hz, 1H). ¹³C NMR (101 MHz, DMSO) δ 176.3, 139.8, 138.7, 138.7, 136.2, 135.2, 135.0, 130.8, 129.8, 128.5, 127.9, 127.2, 126.7, 126.0, 125.2, 123.8, 118.7, 113.6. HRMS-ESI (m/z): chemical formula: C₂₂H₁₆Cl₃N₄O₂S₂, calculated [M + H]⁺: 536.9780, found: 536.9775. HPLC-PDA: λ 300 nm, MeCN: MeOH (1:1), Rt: 7.2 min, 99.92%.

(E)-2-((1-((3,5-Dichlorophenyl)sulfonyl)-1 H-indol-3-yl)methylene)-N-(3-chlorophenyl)hydrazine-1-carbothioamide (5 m)

Off-white solid, yield: 80%, mp: 226–228 °C. ¹H NMR (400 MHz, DMSO) δ 12.05 (s, 1H), 9.88 (s, 1H), 8.50 (s, 1H), 8.41 (s, 1H), 8.33 (d, J = 7.8 Hz, 1H), 8.17 (s, 2 H), 8.06 (d, J = 8.3 Hz, 1H), 7.79 (s, 1H), 7.56 (d, J = 8.8 Hz, 1H), 7.48 (t, J = 7.7 Hz, 1H), 7.40 (t, J = 7.9 Hz, 2 H), 7.26 (d, J = 9.0 Hz, 1H). ¹³C NMR (101 MHz, DMSO) δ 176.2, 141.2, 139.7, 138.9, 136.2, 135.2, 135.0, 132.7, 130.9, 130.1, 127.2, 126.7, 126.0, 125.6, 125.5, 125.2, 124.8, 123.9, 118.7, 113.6. HRMS-ESI (m/z): chemical formula: C₂₂H₁₆Cl₃N₄O₂S₂, calculated [M + H]⁺: 536.9780, found: 536.9771. HPLC-PDA: λ 300 nm, MeCN: MeOH (1:1), Rt: 8.22 min, 98.85%.

(E)-2-((1-((3,5-Dichlorophenyl)sulfonyl)-1 H-indol-3-yl)methylene)-N-(2,3-dichlorophenyl)hydrazine-1-carbothioamide (5n)

Yellow solid, yield: 79%, mp: 223–225 °C. ¹H NMR (400 MHz, DMSO) δ 12.18 (s, 1H), 9.77 (s, 1H), 8.50 (s, 1H), 8.42 (t, J = 3.8 Hz, 2 H), 8.18 (d, J = 1.8 Hz, 2 H), 8.08–8.02 (m, 2 H), 7.86 (d, J = 8.1 Hz, 1H), 7.57 (d, J = 8.1 Hz, 1H), 7.50–7.36 (m, 3 H). ¹³C NMR (101 MHz, DMSO) δ 176.4, 139.7, 139.3, 139.0, 136.2, 135.3, 135.0, 132.0, 131.5, 129.4, 128.8, 128.5, 128.0, 127.0, 126.8, 126.0, 125.2, 124.0, 118.5, 113.6. HRMS-ESI (m/z): chemical formula: C₂₂H₁₅Cl₄N₄O₂S₂, calculated [M + H]⁺: 570.9391, found: 570.9383. HPLC-PDA: λ 300 nm, MeCN: MeOH (1:1), Rt: 6.39 min, 98.78%.

(E)-2-((1-((3,5-Dichlorophenyl)sulfonyl)-1 H-indol-3-yl)methylene)-N-(4-bromophenyl)hydrazine-1-carbothioamide (5o)

Yellow solid, yield: 88%, mp: 231–233 °C. ¹H NMR (400 MHz, DMSO) δ 12.00 (s, 1H), 9.83 (s, 1H), 8.49 (s, 1H), 8.40 (s, 1H), 8.33 (d, J = 7.9 Hz, 1H), 8.17 (d, J = 1.8 Hz, 2 H), 8.06 (d, J = 8.3 Hz, 1H), 8.02 (t, J = 1.8 Hz, 1H), 7.59–7.55 (m, 4 H), 7.48 (t, J = 7.9 Hz, 1H), 7.39 (t, J = 7.6 Hz, 1H). ¹³C NMR (101 MHz, DMSO) δ 176.2, 139.8, 139.1, 138.7, 136.2, 135.2, 135.0, 131.4, 131.3, 130.8, 128.1, 127.2, 126.7, 126.0, 125.2, 123.8, 118.7, 118.0, 113.6. HRMS-ESI (m/z): chemical formula: C₂₂H₁₆BrCl₂N₄O₂S₂, calculated [M + H]⁺: 580.9275, found: 582.9247 (⁸¹Br). HPLC-PDA: λ 300 nm, MeCN: MeOH (1:1), Rt: 7.13 min, 99.63%.

(E)-2-((1-((3,5-Dichlorophenyl)sulfonyl)-1 H-indol-3-yl)methylene)-N-(3-nitrophenyl)hydrazine-1-carbothioamide (5p)

Yellow solid, yield: 77%, mp: 218–220 °C. ¹H NMR (400 MHz, DMSO) δ 12.19 (s, 1H), 10.12 (s, 1H), 8.66 (t, J = 2.1 Hz, 1H), 8.51 (s, 1H), 8.43 (s, 1H), 8.36 (d, J = 7.8 Hz, 1H), 8.18 (d, J = 1.8 Hz, 2 H), 8.07–8.02 (m, 4 H), 7.66 (t, J = 8.2 Hz, 1H), 7.48 (t, J = 7.3 Hz, 1H), 7.40 (t, J = 7.3 Hz, 1H). ¹³C NMR (101 MHz, DMSO) δ 176.3, 147.8, 141.0, 139.7, 139.4, 136.2, 135.2, 135.0, 132.4, 131.1, 129.8, 127.2, 126.7, 126.0, 125.2, 123.9, 120.1, 118.6, 113.6. HRMS-ESI (m/z): chemical formula: C₂₂H₁₆Cl₂N₅O₄S₂, calculated [M + H]⁺: 548.0021, found: 548.0015. HPLC-PDA: λ 300 nm, MeCN: MeOH (1:1), Rt: 6.51 min, 95.04%.

(E)-2-((1-((3,5-Dichlorophenyl)sulfonyl)-1 H-indol-3-yl)methylene)-N-(2,4-dimethylphenyl)hydrazine-1-carbothioamide (5q)

Off-white solid, yield: 86%, mp: 243–245 °C. ¹H NMR (400 MHz, DMSO) δ 11.83 (s, 1H), 9.49 (s, 1H), 8.47 (s, 1H), 8.40 (d, J = 10.1 Hz, 2 H), 8.17 (d, J = 1.8 Hz, 2 H), 8.07–8.02 (m, 2 H), 7.47 (t, J = 7.8 Hz, 1H), 7.36 (t, J = 7.5 Hz, 1H), 7.24 (d, J = 7.9 Hz, 1H), 7.09 (s, 1H), 7.04 (d, J = 8.0 Hz, 1H), 2.30 (s, 3 H), 2.21 (s, 3 H). ¹³C NMR (101 MHz, DMSO) δ 177.0, 139.8, 138.1, 136.2, 136.0, 135.3, 135.2, 135.0, 131.0, 130.6, 128.9, 127.2, 126.9, 126.6, 126.0, 125.1, 124.0, 118.9, 113.6, 21.1, 18.2. HRMS-ESI (m/z): chemical formula: C₂₄H₂₁Cl₂N₄O₂S₂, calculated [M + H]⁺: 531.0483, found: 531.0472. HPLC-PDA: λ 300 nm, MeCN: MeOH (1:1), Rt: 6.91 min, 99.87%.

(E)-2-((1-((3,5-Dichlorophenyl)sulfonyl)-1 H-indol-3-yl)methylene)-N-(2,6-dimethylphenyl)hydrazine-1-carbothioamide (5r)

White solid, yield: 87%, mp: 259–261 °C. ¹H NMR (400 MHz, DMSO) δ 11.80 (s, 1H), 9.45 (s, 1H), 8.46 (t, J = 3.8 Hz, 2 H), 8.38 (s, 1H), 8.17 (d, J = 1.8 Hz, 2 H), 8.07–8.03 (m, 1H), 7.47 (t, J = 8.1 Hz, 1H), 7.36 (t, J = 7.5 Hz, 1H), 7.14–7.10 (m, 3 H), 2.21 (s, 6 H). ¹³C NMR (101 MHz, DMSO) δ 177.0, 139.8, 138.0, 137.9, 137.1, 136.1, 135.2, 135.0, 130.5, 128.0, 127.4, 127.2, 126.6, 126.0, 125.2, 124.2, 119.0, 113.5, 18.5. HRMS-ESI (m/z): chemical formula: C₂₄H₂₁Cl₂N₄O₂S₂, calculated [M + H]⁺: 531.0483, found: 531.0472. HPLC-PDA: λ 210 nm, MeCN: MeOH (1:1), Rt: 6.75 min, 98.65%.

(E)-2-((1-((3,5-Dichlorophenyl)sulfonyl)-1 H-indol-3-yl)methylene)-N-(3-methoxyphenyl)hydrazine-1-carbothioamide (5s)

Light yellow solid, yield: 81%, mp: 227–229 °C. ¹H NMR (400 MHz, DMSO) δ 11.93 (s, 1H), 9.75 (s, 1H), 8.49 (s, 1H), 8.39 (s, 1H), 8.31 (d, J = 7.9 Hz, 1H), 8.18 (d, J = 1.8 Hz, 2 H), 8.07–8.04 (m, 2 H), 7.48 (t, J = 7.7 Hz, 1H), 7.40 (t, J = 7.4 Hz, 1H), 7.32–7.26 (m, 2 H), 7.18 (d, J = 8.0 Hz, 1H), 6.79 (dd, J = 8.2, 2.1 Hz, 1H), 3.77 (s, 3 H). ¹³C NMR (101 MHz, DMSO) δ 176.0, 159.5, 140.7, 139.8, 138.3, 136.2, 135.2, 135.0, 130.7, 129.3, 127.2, 126.7, 126.0, 125.2, 123.7, 118.8, 118.0, 113.7, 111.5, 111.2, 55.6. HRMS-ESI (m/z): chemical formula: C₂₃H₁₉Cl₂N₄O₃S₂, calculated [M + H]⁺: 533.0276, found: 533.0265. HPLC-PDA: λ 300 nm, MeCN: MeOH (1:1), Rt: 5.94 min, 99.91%.

(E)-2-((1-((3,5-Dichlorophenyl)sulfonyl)-1 H-indol-3-yl)methylene)-N-(4-methoxyphenyl)hydrazine-1-carbothioamide (5t)

Light yellow solid, yield: 83%, mp: 245–247 °C. ¹H NMR (400 MHz, DMSO) δ 11.84 (s, 1H), 9.67 (s, 1H), 8.48 (s, 1H), 8.38 (s, 1H), 8.35 (d, J = 7.8 Hz, 1H), 8.17 (d, J = 1.8 Hz, 2 H), 8.07–8.02 (m, 2 H), 7.49–7.36 (m, 4 H), 6.94 (d, J = 9.0 Hz, 2 H), 3.77 (s, 3 H). ¹³C NMR (101 MHz, DMSO) δ 176.7, 157.5, 139.8, 138.1, 136.2, 135.2, 135.0, 132.5, 130.5, 128.1, 127.2, 126.6, 126.0, 125.2, 123.9, 118.8, 113.8, 113.6, 55.7. HRMS-ESI (m/z): chemical formula: C₂₃H₁₉Cl₂N₄O₃S₂, calculated [M + H]⁺: 533.0276, found: 533.0264. HPLC-PDA: λ 300 nm, MeCN: MeOH (1:1), Rt: 7.29 min, 99.94%.

Enzyme inhibition assay

Cholinesterases inhibition

AChE from Electrophorus electricus (electric eel; specific activity 200–1,000 U/mg protein) and BChE obtained from equine serum (≥ 10 U/mg protein) were purchased from Sigma Aldrich (St. Louis, MO, USA). Acetylthiocholine chloride (ATChCl) and butyrylthiocholine iodide (BTChI) were employed as the specific substrates for AChE and BChE, respectively. All assay solutions were freshly prepared in 0.1 M Tris–HCl buffer (pH 8.0). Cholinesterase inhibitory activities were determined spectrophotometrically using a modified Ellman’s method⁶⁸. The enzymatic reactions were initiated by the addition of the appropriate substrate, and the generation of the yellow-colored product was continuously monitored at 412 nm using a UV–Vis spectrophotometer. Galantamine was used as the reference inhibitor for both AChE and BChE assays. For kinetic evaluation, inhibition constant (K_i) values were calculated by assessing enzyme activity at multiple inhibitor concentrations under steady-state conditions. Initial reaction rates were measured at varying substrate concentrations in both the absence and presence of inhibitors. Lineweaver-Burk double-reciprocal plots (1/V versus 1/[S]) were constructed to determine the inhibition mode and K_i values based on the observed changes in slope and intercepts^69,70.

MAO-A inhibition

Human monoamine oxidase A was obtained from Sigma-Aldrich (M7316 and M7441), and all assays were conducted according to the manufacturer’s recommendations. The inhibitory activity of the synthesized compounds against human monoamine oxidase A was evaluated using an in vitro fluorometric assay. The method is based on a horseradish peroxidase (HRP)-coupled reaction, in which hydrogen peroxide (H₂O₂), generated during the oxidative deamination of tyramine (used as the MAO-A substrate), is quantitatively detected. The produced H₂O₂ reacts with the Amplex Red reagent (10-acetyl-3,7-dihydroxyphenoxazine), yielding a highly fluorescent resorufin product that allows sensitive monitoring of enzymatic activity. Initially, each compound was screened at concentrations of 10^{− 3} and 10^{− 4} M to assess preliminary inhibitory effects⁷¹. Compounds exhibiting more than 50% inhibition were subsequently evaluated over a wider concentration range (10^{− 5}–10^{− 9} M) to determine their IC₅₀ values against the MAO-A. Clorgyline was used as the reference inhibitor. Fluorescence measurements were performed under optimized assay conditions to ensure steady-state kinetics.

Cytotoxicity assay

Cell culture, cell viability, and homogenization

The human neuroblastoma cell line SH-SY5Y (ATCC CRL-2266) and the human umbilical vein endothelial cell line HUVEC (ATCC CRL-1730) were maintained in DMEM/F-12 medium supplemented with 10% heat-inactivated fetal bovine serum (FBS) and 1% penicillin–streptomycin. Cells were cultured at 37 °C in a humidified atmosphere containing 5% CO₂.

For cytotoxicity evaluation, cells were seeded into 96-well plates at a density of 5 × 10³ cells per well and allowed to adhere overnight. Subsequently, the cells were treated with increasing concentrations of the test compounds for 24 h. Cell viability was determined using the crystal violet staining assay. After incubation, the cells were fixed and stained, and the bound dye was solubilized using a sodium citrate/ethanol solution. Absorbance was measured at 600 nm using a microplate reader, and cell viability was expressed as a percentage relative to untreated control cells. Sorafenib was employed as the reference drug for cytotoxicity assays to allow direct comparison with the synthesized compounds. The IC₅₀ values obtained for the tested derivatives were evaluated relative to sorafenib under identical experimental conditions, enabling assessment of both cytotoxic potency and selectivity toward the SH-SY5Y neuroblastoma cell line. All experiments were performed in triplicate and repeated in three independent experiments¹⁶.

For cell homogenization, SH-SY5Y and HEK-293 cells were seeded at a density of 1 × 10⁶ cells/mL in culture flasks and incubated for 24 h. Cells were then harvested and lysed in homogenization buffer containing 0.1 M phosphate buffer, 2 mM EDTA, 0.2% Triton X-100, 0.3 mM ε-aminocaproic acid (ε-ACA), 1 mM dithiothreitol (DTT), and 0.5 mM phenylmethylsulfonyl fluoride (PMSF). Homogenization was carried out by sonication on ice, and total protein concentration was determined using the BCA protein assay with bovine serum albumin (BSA) as standard⁷².

IC₅₀ determination and statistical analysis

The half-maximal inhibitory concentration (IC₅₀) values were calculated from dose–response curves generated by nonlinear regression analysis using GraphPad Prism 9.0 software (GraphPad Software, San Diego, CA, USA). Cell viability data were expressed as mean ± standard deviation (SD) of three independent experiments, each performed in triplicate. Statistical comparisons between treated and control groups were conducted using one-way analysis of variance (ANOVA), followed by Tukey’s post hoc test (multiple groups). Differences were considered statistically significant at p < 0.05⁷³.

Computational studies

Molecular docking and MD simulations were carried out using the Schrödinger Molecular Modeling Suite (version 2025-1) through the Maestro graphical user interface (v14.3), with MD simulations performed in the Desmond module. Protein and ligand preparation procedures followed previously established in-house protocols^74,75. The crystallographic structures of AChE (PDB ID: 4M0F)⁵⁵, BChE (PDB ID: 6EQP)⁵⁶, and MAO-A (PDB ID: 2Z5X)⁵² were retrieved from the Protein Data Bank and processed using the Protein Preparation Wizard to ensure proper protonation states, bond orders, and structural optimization. Molecular docking was conducted using the Glide XP algorithm in combination with the IFD approach to explicitly account for receptor flexibility during ligand binding. For each ligand, twenty binding poses were generated, and the most favorable conformations were selected based on IFD scoring criteria. Subsequently, binding free energies of the selected complexes were estimated by Prime MM-GBSA calculations employing the VSGB solvation model^76,77.

MD simulations were carried out using the Desmond module implemented in the Schrödinger Suite (Release 2024-3). Protein-ligand complexes obtained from docking studies were prepared by removing crystallographic water molecules located beyond 10 Å from the bound ligand. Appropriate protonation states corresponding to physiological pH (7.0) were assigned, and hydrogen-bonding networks were optimized prior to simulation. Each system was embedded in an orthorhombic simulation box with a 10 Å padding in all directions and solvated using the TIP4P explicit water model. System neutrality was achieved by the addition of Na⁺ or Cl⁻ counterions, followed by the incorporation of 0.15 M NaCl to mimic physiological ionic strength. Energy-minimized systems were gradually heated from 0 to 300 K over 200 ps under the NVT ensemble, employing the Nosé-Hoover thermostat with a relaxation time of 1.0 ps. Subsequent pressure equilibration was performed for 1 ns under NPT conditions at 1.01325 bar using the Martyna-Tobias-Klein barostat (relaxation time: 2 ps), while applying positional restraints to the protein backbone atoms. Following equilibration, 250 ns production MD simulations were executed at 300 K and 1.01325 bar in the NPT ensemble using a 2 fs integration time step. Long-range electrostatic interactions were treated with the particle mesh Ewald (PME) method, and van der Waals interactions were truncated at a cutoff distance of 9 Å. Trajectory frames were saved at 100 ps intervals for subsequent analysis. System stability and dynamic behavior were evaluated through RMSD and RMSF analyses of protein backbone atoms and ligand heavy atoms. In addition, hydrogen-bonding patterns and ligand binding modes were continuously monitored throughout the simulation trajectories to assess the stability and persistence of protein-ligand interactions^72,78.

The pharmacokinetic properties of the synthesized compounds were predicted using the QikProp module implemented in the Schrödinger Suite (2024), which allows estimation of essential ADME-related parameters. These in silico assessments were performed to evaluate the drug-likeness, oral bioavailability, and overall pharmacokinetic suitability of the compounds. The predicted ADME profiles were used to complement the experimental findings and to support a comprehensive characterization of the molecular properties^72,78.

DFT calculations were performed to optimize the geometrical structures of the investigated compounds at the B3LYP/6-311G(d, p) level of theory. All quantum chemical computations were carried out using Gaussian 16, and the optimized geometries were visualized and analyzed with GaussView 6.0. The electronic properties of the molecules were explored through frontier molecular orbital (HOMO–LUMO) analysis, which provides insight into electron distribution, charge-transfer tendencies, and electronic excitation behavior^63,64. In addition, several global reactivity descriptors, including ionization potential, electron affinity, electronegativity, chemical hardness, chemical potential, and electrophilicity index, were calculated based on the corresponding frontier orbital energies. These parameters offer valuable information regarding the chemical reactivity, kinetic stability, and electronic interaction potential of the compounds. Furthermore, molecular electrostatic potential (MEP) surfaces were generated to identify regions prone to electrophilic and nucleophilic attacks, and the resulting surfaces were visualized using the Avogadro software⁶⁵.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

Khawar Abbas, Furkan Çakır: Investigation, Formal analysis. Feyzi Sinan Tokali, Halil Şenol: Writing-original draft, Data curation. Rima D. Alharthy, Asif Rasool: Formal analysis, Validation, Data curation. Mohamed Rahmtalla Elamin, Funding acquisition, Biological Activity, Data curation, Software. Parham Taslimi: Biological Activity, Data curation, Software. Nadeem Raza, Mostafa E. Salem: Reviewing and editing, Data curation, Resources.: Zahid Shafiq: Writing-original draft, Supervision, Conceptualization.

Funding

This work was supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University (IMSIU) (grant number IMSIU-DDRSP2601).

Data availability

The datasets generated and/or analysed during the current study are available in this published article [and its supplementary information files].

Declarations

Competing interests

The authors declare no competing interests.