In silico screening and in vitro biological evaluation reveal Queuine as a promising MAP4K4 inhibitor for treating pancreatic cancer

Abstract

Pancreatic cancer (PC) remains one of the deadliest cancer types, with limited success in treatment despite advances in research. MAP4K4 is overexpressed in pancreatic tumors and linked to disease progression, making it a promising target for PC therapy. This study aimed to identify bioactive nutraceutical molecules targeting MAP4K4 using molecular docking, molecular dynamics (MD) simulations, and MM-GBSA calculations. The computational findings were validated through in vitro MTT cell viability assays and MAP4K4 enzyme ELISA tests. Queuine and Thiamine were identified as potent MAP4K4 inhibitors with comparable docking scores to the approved drug Gemcitabine. MD simulations confirmed stable binding for 100 ns (3 runs), with average binding free energy values of -50 kcal/mol for Queuine, -47 kcal/mol for Thiamine, and − 18 kcal/mol for Gemcitabine. In vitro assays showed that Thiamine was non-cytotoxic at high concentrations, while Queuine had a significantly lower IC₅₀ (5.95 µM) compared to Gemcitabine (64.17 µM), making it nearly ten times more potent. MAP4K4 ELISA tests confirmed Queuine’s superior binding and enzyme inhibition compared to Gemcitabine. Synergy studies combining Queuine (0.25–1.25 µM) and Gemcitabine (0.05–2.5 µM) revealed strong synergistic effects, suggesting enhanced efficacy at lower doses. These findings highlight Queuine as a promising natural therapeutic agent for PC, with potential for combination therapy with Gemcitabine. Further in vivo studies are recommended to explore its therapeutic potential.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12896-025-01033-w.

Introduction

Cancer is the uncontrolled division of cells that results from the disruption of the control mechanisms that ensure growth and development. It is one of the most important causes of death worldwide and remains a challenging health problem today [1, 2]. There are several treatment methods for cancer. Common strategies used to treat cancer in the clinic include surgery, chemotherapy, radiotherapy, and immunotherapy. In most cases, however, such treatments fail because of variations in drug resistance, side effects, and drug specificity problems [3, 4]. Pancreatic cancer (PC) is one of the most malignant tumors and the leading cause of cancer-related death worldwide. The annual incidence of pancreatic cancer has increased by 1% since 2000 and continues to rise. The prevalence of PC is expected to rise, with projections indicating that 765,261 people will succumb to the disease by 2040 [5]. PC is often undetected in its early stages and remains asymptomatic until it metastasizes, making diagnosis challenging. Even with surgery and chemotherapy, treatment remains difficult. Additionally, because PC symptoms are subtle, most patients are diagnosed at an advanced stage. Consequently, severe metastasis and invasiveness render these patients inoperable [6].

Currently, surgical methods are the main treatment for PC, yet immunotherapy and targeted therapies can be considered new approaches [7]. Chemotherapeutic drugs such as 5-fluorouracil, Gemcitabine, and nab-paclitaxel are used in standard drug treatment for PC. Gemcitabine was the first drug approved by the FDA and is more effective than 5-fluorouracil [8]. Nevertheless, Gemcitabine treatment did not prolong the survival time of patients beyond 6 months. Therefore, new therapeutic approaches are urgently needed for PC [9]. Researchers currently emphasize the use of phytochemicals such as alkaloids, glycosides, flavonoids, terpenoids, phenolics, and saponins to prevent the negative side effects of chemotherapeutics and prolong and improve quality of life [10]. Although the molecular mechanisms of these compounds have not yet been fully elucidated, natural products have played an important role in the development of antitumor drugs for decades. Natural molecules can generally be defined as components of plant matter, insects, marine organisms, microorganisms, or their metabolites. Many natural products, such as paclitaxel, v-vincristine, or their analogs, are widely used in clinical applications [11]. These natural products exert their antitumor activity through diverse mechanisms. The use of phytochemical compounds such as phenolic or flavonoid compounds in the prevention and treatment of cancer also has a significant healing effect [12, 13]. For example, these organic compounds are extracted from plants and microorganisms and represent more than 50% of all modern clinical drugs [14, 15]. Moreover, phytochemicals found in some commonly consumed foods have an antioxidant capacity to be effective against the proliferation and differentiation of important cancer cells [16, 17]. It has been reported that natural therapeutics rich in phenolic and flavonoid compounds are powerful drugs that protect against cancer cells because of their antiapoptotic properties [18].

In a recent review, the efficiency and use of nutraceutical molecules in PC therapy were discussed thoroughly. Current evidence from clinical studies conducted with four natural products, namely, curcumin, thymoquinone, genistein, and Ginkgo biloba, has been presented [19]. This study reported that standalone treatment and a combination of these substances with chemoradiotherapy did not directly or significantly enhance the treatment response of PC patients. Nevertheless, these substances exhibited notable effectiveness in the treatment of diabetes, a condition closely associated with PC. Diabetes has been linked to an increased risk of PC, i.e., diabetic patients with insulin resistance were reported to have a twofold increased risk of PC development [20]. Consequently, these interventions may indirectly contribute to PC therapy. Among the natural products, curcumin, which is a polyphenolic compound found in the spice Indian saffron extracted from the plant Curcuma longa L., also known as turmeric, is the only metabolite or botanical drug that is currently in clinical trials (Phase II: NCT00094445, registration date: 2004-10-18) for the treatment of PC [21]. From 2004 to 2010, a total of 44 patients diagnosed with adenocarcinoma of pancreatic neoplasms participated in a phase II clinical trial of curcumin. It has a wide range of pharmacological effects, with anti-inflammatory, antioxidant, and antitumor properties. It is also applied to increase sensitivity to radiotherapy and chemotherapy and to protect liver and kidney functions [22]. It has been widely studied in a wide variety of cancer types, including acute cancers. Among the cancer types in which the effects of curcumin have been investigated, in addition to those of PC, the effects of curcumin include myeloid leukemia [23], prostate cancer [24], breast cancer, and lung cancer [25]. Several other natural products or metabolites that have not yet entered clinical trials have been reported, such as triptolide, toosendamin, libertellenone, propolis, Panax notoginseng saponins, xanthohumol, pterostilbene, and cordycepin [21].

Mitogen-activated protein kinase kinase kinase kinase 4 (MAP4K4) belongs to the serine/threonine-protein kinase superfamily. Its 3D structure comprises an N-terminal kinase domain, a helicase domain, a C-terminal hydrophobic leucine-rich (CNH) domain, and regions that interact with both the N-terminal kinase and CNH domains. The N-terminal kinase domain plays a pivotal role in MAP4K4 phosphorylation and activation in the human body [26]. MAP4K4 is expressed in the human brain and liver, where it phosphorylates the moesin substrate, facilitating membrane extension and retraction during epithelial cell migration [27].

Several studies have shown that MAP4K4 is associated with systemic inflammation, lung tissue inflammation [28], and malignancies such as cancer [29]. Recently, MAP4K4 was shown to manipulate the activity of the JNK signaling pathway, leading to cell proliferation and metastasis, thereby contributing to the progression of PC [30–32]. Additionally, MAP4K4 was found to be overexpressed in approximately half of patients compared with healthy individuals. Clinicopathological evidence also suggests that the overexpression of MAP4K4 in PC is associated with poor overall survival. Additionally, tumor size and metastasis are associated with MAP4K4 expression [33]. It has been reported that in cancer cells, downregulation of MAP4K4 causes the induction of apoptosis [34–36] and the cell cycle [37, 38], hence preventing cancer progression. Another study concluded that MAP4K4-regulated signaling pathways play a crucial role in cancer progression [29], as MAP4K4 is involved in growth, proliferation [37, 38], migration, and invasion [39–41]. Therefore, the suppression of MAP4K4 and its associated signaling pathways has emerged as a novel therapeutic strategy for preventing pancreatic tumor formation and progression. Gemcitabine, currently marketed as a Gemzar for treating PC, has limitations because of its low bioavailability, necessitating high doses and high off-target cytotoxicity. This study proposes novel nutraceutical molecules that can serve as more reliable and effective alternatives to Gemcitabine for PC treatment by inhibiting MAP4K4 enzymatic activity. We utilized a systematic computational approach involving virtual screening, molecular docking, protein-ligand interaction monitoring, ADMET evaluations, molecular dynamics simulations, Molecular mechanics with generalized Born and surface area solvation (MM-GBSA) binding free energy calculations to identify potent MAP4K4-binding molecules. The inhibitory effects of our lead compounds were validated in vitro via cell culture assays on PANC-1 cells and chemically via MAP4K4 ELISA tests. Cell viability was analyzed to determine the IC50 values of Gemcitabine and selected nutraceuticals in PANC-1 cells, and the potential anticancer activities of our candidate drug molecules compared with those of Gemcitabine were assessed. ELISA was used to quantitatively assess target enzyme‒drug binding. Furthermore, the potential synergistic effect of the hit promising molecule obtained in combination therapy with Gemcitabine was also explored.

Materials and methods

Protein preparation

The protein preparation is managed using Schrödinger’s Maestro Molecular Modeling Suite, version 13.1 [42, 43], via the Protein Preparation Wizard module [44]. The crystal structure of MAP4K4 (PDB ID: 4OBP) complexed with a co-crystal small molecule was obtained from the Protein Data Bank (PDB) and prepared by correcting bond orders, and missing hydrogen atoms. The prime module was utilized to construct any missing side chains or loops. Since the active site is determined around the native ligand, all heteroatoms other than the co-crystal ligand were removed. To account for the crucial interactions of the protein-ligand complex within the binding cleft, water molecules of around 5 Å were preserved, while the rest were deleted. The pH was kept at 7.0 and the protonation states were assigned using PROPKA. Optimized Potentials for Liquid Simulations 2005 (OPLS2005) force field was selected for restrained minimization with a 0.3 Å RMSD threshold [45].

Ligand preparation and screening procedure

To prepare the database for docking simulations the molecules are first prepared using the LigPrep module in Schrödinger’s Maestro program [43, 44]. In this module, Epik is used in the generation of the ionization states and tautomers for each ligand, keeping the pH around 7.0 ± 2.0 [46]. The stereoisomers were derived based on the chiralities of the ligands’ 3D structures. The natural product library that was screened consisted of 3,200 natural source metabolites and nutraceutical molecules obtained from the DrugBank database [47]. This library was processed using LigPrep, generating 15,203 conformers, which were subsequently docked into the MAP4K4 active site.

Molecular docking

A standard precision algorithm of the Glide module was selected to conduct the molecular docking calculations. The receptor grid was generated using the receptor grid generation module, focusing on the MAP4K4 binding region that is centered around the co-crystal ligand. The binding site was defined as a 20 Å region around the co-crystal ligand (HET ID: 2QU). Ligands were treated as flexible, and Epik state penalties were incorporated into the binding scores. A total of 15,203 drug-like molecules, generated through LigPrep, were directly docked into the MAP4K4 binding site generated. Molecules exhibiting higher binding affinity than the control benchmark drug, Gemcitabine, were selectively chosen for further analysis. To validate the docking protocol we redocked the co-crystal ligand present in the MAP4K4 crystal structure yielding a RMSD value of 0.17 Å. Thus, it can be concluded that the protocol can accurately reproduce the crystallographic pose of the co-crystal ligand.

Molecular dynamics (MD) simulations

Molecular dynamics (MD) simulations represent a widely accepted method based on a physics model to discern real-time movements at the atomic level of biological molecules and comprehend the stability of drug molecules within the active region. With the use of the Desmond module for molecular dynamics simulations, bound complex systems were simulated for a duration of 100 ns (3 runs). For each system, which encompasses the apo form of MAP4K4, and for the Queuine, Thiamine, and Gemcitabine (control)-bound forms, three simulations were conducted. A time step of 100 ps was employed, resulting in 1,000 recorded frames. The trajectory is analyzed using the average data obtained from the frames throughout the entire duration. Each system was subjected to two iterations. The dimensions of the system box were 10 × 10 × 10 Å and were configured in an orthorhombic shape. The solvent model employed was TIP3P. The system is neutralized by introducing 0.15 M NaCl salt. In all runs, constant temperature (300 K) and pressure (1.0 bar) NPT ensemble Nose–Hoover chain thermostat and Martyna–Tobias–Klein barostat were selected. OPLS2005 force field and RESPA integrator were utilized for simulations and calculating the interactions, such as Coulomb, nonbonded, and van der Waals forces.

MM-GBSA free energy calculations

Docking scores provide only a relative comparison between compounds, as binding free energy is determined by the sum of enthalpic and entropic contributions. To achieve a more precise estimation of binding free energy, MM-GBSA calculations were made using the Prime module of the Schrödinger Suite, where the binding free energy calculations are conducted for each frame and average values are obtained over 100 frames for the protein-ligand systems. Ligand and receptor files were extracted from a 100 ns molecular dynamics simulation, recorded at 0.1 ns intervals, generating 1001 frames. For every 100 frames, MM-GBSA calculations were performed, with the average values of 10 frames used for free energy analysis. The VSGB 2.0 model was selected which is suitable for modeling biological systems and drug discovery. Minimization was employed by keeping the residues around 3 Å of the ligand flexible using the OPLS2005 force field as before.

Cell culture

In this study, Panc-1 cells were obtained from the University of Health Sciences, Istanbul, Turkey. Panc-1 cells were cultured in DMEM (HG) which was supplemented by 1% penicillin-streptomycin and 10% FBS at 37 °C in a CO2 (5%) incubator. The medium was changed once a week, and the cells were passaged once every five days. These cells were reported to exhibit a greater level of MAP4K4 gene expression than did pancreatic adenocarcinoma cells (AsPC-1) in previous studies [32]. The higher levels of MAP4K4 in the Panc-1 cell line suggest that our lead compounds may have a more sensitive effect on inhibiting MAP4K4 activity, growth, and proliferation in this cellular model. Therefore, we assumed that changes in cell survival in response to the selected compounds would be reliably measured in this cellular pancreatic cancer model.

Drug preparation and treatment

Panc-1 cells (5 × 10³/well) were seeded in 96-well plates 24 h before treatment. Queuine hydrochloride (Santa Cruz) was dissolved in dimethyl sulfoxide (DMSO). Gemcitabine hydrochloride and Thiamine hydrochloride (Sigma Aldrich, St. Louis, MO, USA) were dissolved in nuclease-free sterile water as described previously [48]. Further dilutions were made in the growth medium used for regular cell culture. Queuine hydrochloride, Thiamine hydrochloride, and Gemcitabine hydrochloride were used at concentrations of 0–5 µM, 0–10,200 µM, and 0–50 µM, respectively. A combination treatment was performed using 0.25 µM or 1.25 µM Queuine hydrochloride and 5 different concentrations of gemcitabine hydrochloride (0.05, 0.1, 0.5, 1.25, and 2.5 µM). Wells containing cells without drug treatment were chosen as control groups.

Cell viability (MTT) tests

To evaluate cell survival, an MTT assay was conducted on drug-treated cells as previously described [48]. Briefly, after 48 h of drug treatment, 50 µl of 1X MTT (ElabScience, E-CK-A341) solution was added to each well, with three additional wells containing only MTT solution for blank measurement. The plate was incubated at 37 °C with 5% CO2 for 4 h. Following incubation, the medium was discarded, and 150 µl of DMSO was added to each well and incubated for 10 min at room temperature. Spectrophotometric absorbance readings were taken using a microplate reader (Omega) with a 570 nm background, measured at 480 nm. The resulting data were used to calculate percent viability with respect to the control and to generate a dose-response curve for each drug.

ELISA assay procedure

The ELISA was performed following the protocol provided by the Human Mitogen-activated Protein Kinase 4 (MAP4K4) ELISA Kit, which is intended for the quantitative detection of MAP4K4 (BT Lab, Cat. no. E5689Hu) with slight modifications. The procedure included the addition of 50 µL of an enzyme solution at a concentration of 0.8 µg/L to wells pre-coated with a human MAP4K4 antibody. This was followed by incubation of the samples with 50 µL of various concentrations of Queuine (0.5, 1, 3, or 6 µM) and Gemcitabine (5, 10, 30, or 60 µM), while the control group was left without any drug treatment. Subsequently, 50 µL of streptavidin-HRP conjugate, which binds to the biotinylated MAP4K4 antibody, was added. The plate was then incubated at 37 °C for 1 h. Following incubation, unbound streptavidin-HRP was removed through a washing step. A substrate solution was then added, and after a 10-minute incubation at 37 °C, the reaction was stopped by adding 50 µL of an acidic stop solution. The intensity of color development, which is directly proportional to the amount of human MAP4K4, was measured by measuring the absorbance at 450 nm.

Statistical analysis

The results are presented as the standard error of the mean from three replicate experiments. The data was analyzed using GraphPad Prism 10.2.3 software. The analysis includes ordinary one-way ANOVA together with Tukey’s multiple comparisons test. The statistical significance was evaluated according to a p-value of < 0.05.

Results

Virtual screening of natural molecule library using molecular docking

The inhibitory activities of nutraceutical and metabolite molecules delivered from the Drug Bank [47] database were tested against MAP4K4. Figure 1 illustrates the schematic summary of the approach used. The in silico part of the study involved screening the database and docking the generated conformers to the MAP4K4 binding site, followed by in vitro chemical and biological validations of the identified hit molecules. The approved drug Gemcitabine was used as the reference compound for comparison purposes. Among the 15,203 natural molecules and corresponding conformers, 4 hit molecules were captured as they were docked to the MAP4K4-binding site. The hit molecules have good docking scores and perform crucial interactions with the active site when compared to Gemcitabine. These candidates are listed in Table 1.

Fig. 1.

Schematic representation of the in silico and in vitro methodologies

Table 1.

Molecular properties of hit compounds compared with approved drug gemcitabine

Molecule name	DrugBank ID	Class	Previously mentioned in cancer studies?/type of cancer	Reference
Queuine	DB14732	nutraceutical	yes/ leukemia and lymphomas colon, ovarian, brain, lung cancers	[49–53]
Thiamine	DB00152	nutraceutical	yes/ hematological cancers, breast, colon, pancreatic cancers	[54–57]
Melatonin	DB01065	nutraceutical	yes/breast, ovarian, colon, lung, liver and pancreatic cancers	[58–63]
Lipoic acid	DB00166	nutraceutical	yes/lung, colon, breast, pancreatic cancer,	[64–67]
Gemcitabine	DB00441	FDA approved	marketed as Gemzar/ovarian, breast, lung, and pancreatic cancer	[68–70]

Among these 4 candidate molecules, many published works have investigated the effects of melatonin and lactic acid in the treatment of PC. To the best of our knowledge, there have been no studies on Queuine and relatively few published works on Thiamine activity concerning PC. Hence, we selected Queuine and Thiamine for further in silico and in vitro tests. We recently investigated the protective effects of these two molecules in neuroblastoma cell lines for their anti-acetylcholinesterase activity in the treatment of Alzheimer’s disease and focused our attention on any possible anticancer effects of Queuine and Thiamine [48].

Molecular docking simulations revealed the relative binding energies for the ligands binding to the MAP4K4 protein and the main interacting residues contributing to the binding energy. The binding scores for Queuine and Thiamine are − 7.11 and − 8.76 kcal/mol, respectively, surpassing Gemcitabine (-6.67 kcal/mol). Gemcitabine interacts with the MAP4K4 active site via hydrogen bonding with Glu 106. In addition to these crucial interactions, Queuine and Thiamine are involved in additional pi-cation, pi-pi interactions, and hydrogen bonding, as provided in Table 2.

Table 2.

Docking analysis of the proposed nutraceutical compounds Queuine and thiamine compared with the control molecule gemcitabine

Target Protein	Ligand	Binding Energy (kcal/mol)	Interacting Residues on MAP4K4 binding site
MAP4K4 (PDB ID: 4OBP)	Gemcitabine (control drug)	-6.67	Glu 106
	Thiamine	-8.76	Tyr 36, Glu 106, Cys 108, Asp 171
	Queuine	-7.11	Glu 106, Cys 108

Figure 2 displays docked conformations of the control drugs Gemcitabine, Queuine, and Thiamine for 3D and 2D through panels A, B, and C, respectively. Important residues that play crucial roles in contributing to active site interactions with MAP4K4 are colored in magenta. Figure 2A shows the complex of Gemcitabine with the MAP4K4 protein active site. The most significant interaction is performed via hydrogen bonding between Gemcitabine and the Glu106 residue. Glu 106 hydrogen bonding is also observed in the case of Queuine and Thiamine. Additionally, as presented in Fig. 2B, Queuine maintains another hydrogen bond with Cys108, and Thiamine forms hydrogen bonds with Glu106, Cys108, and Asp171 (Fig. 2C). Moreover, in the case of Thiamine, pi-cation and pi-pi interactions are obtained simultaneously with Tyr36 of the MAP4K4 binding site.

Fig. 2.

Interaction analysis of the control drug Gemcitabine and the proposed nutraceutical therapeutics Queuine and Thiamine with the MAP4K4 binding site. (A) 3D binding pose of Gemcitabine (left) and 2D representation (right) of Gemcitabine docked in the MAP4K4 binding site. (B) 3D and 2D binding pose of Queuine (C) 3D and 2D binding pose of Thiamine. Coloring schemes: hydrogen bonding (purple arrows), pi-pi stacking (green line), and pi-cation interactions (red line)

Molecular dynamics (MD) simulations

The sustainability and stability of these interactions were analyzed through 100 ns molecular dynamics simulations and MM-GBSA binding free energy calculations. Figure 3 presents the root mean square deviation (RMSD) (A) and root mean square fluctuation (RMSF) (B) plots for the apo (unbound), Gemcitabine, Queuine, and Thiamine-bound MAP4K4 complexes. The RMSD profiles (Fig. 3A) indicate that all trajectories converge within 3.0 Å, confirming system equilibration and simulation stability. In comparison to the complexes, unbound MAP4K4 appears more stable, with an RMSD of less than 2.0 Å. The Gemcitabine, Queuine, and Thiamine-bound forms exhibit similar RMSD profiles. Changes in protein flexibility induced by ligand binding are revealed through RMSF values (Fig. 3B), where the peaks represent highly mobile (flexible) regions, and the minima (hinges) indicate more stable, less flexible regions of the protein during the simulation. Notably, Glu 106 and Cys 108, key amino acids involved in ligand interactions, are located in the minima (hinge) of the fluctuation profile.

Fig. 3.

Protein-ligand complex root mean square deviation (RMSD) (A) and root mean square fluctuation (RMSF) (B) plots for the apo, Gemcitabine, Queuine, and Thiamine bound forms of the MAP4K4 protein

Protein-ligand contacts that are maintained for more than 30% of the simulation time are depicted in Fig. 4.

Fig. 4.

Schematic showing the durability of ligand-protein interactions during MD simulations. (A) Queuine-protein contacts prolonged for more than 50% of the simulation time. (B) Thiamine has shorter-lived less prolonged contacts

Figure 4A illustrates the Queuine-protein interactions over a 100 ns molecular dynamics (MD) simulation. Specifically, residues such as Val 170, Cys 108, Gln 157, and Asp 171, through water bridges, interact with Queuine for more than 50% of the simulation time. Interestingly, compared with Queuine, Thiamine results in shorter-lived contacts, and despite Thiamine initially demonstrating more interactions with the target in docking simulations, these contacts appear to decrease during MD simulations, as depicted in Fig. 4B, where Tyr 36 emerges as the sole residue maintaining contact for approximately 50% of the simulation time.

Ligand-protein interactions are monitored and finally, the snapshots resulting at the end of the MD simulations are shown in Fig. 5. As shown, both Queuine and Thiamine have remained stable in the binding region (Fig. 5A and B) and stayed bound until the end of the simulation, whereas Gemcitabine (Fig. 5C) seems to diffuse out of the binding site. These results, together with those of the docking analysis, suggest that compared with Gemcitabine, Queuine, and Thiamine serve as stable and potent MAP4K4 inhibitors, providing stronger binding and inhibition effects on MAP4K4. Additional parameters for Queuine, Thiamine, and Gemcitabine were monitored throughout the MD simulations, including the radius of gyration, polar surface area, and solvent-accessible surface area. These results are provided as Supporting Information (Figure S1–S3).

Fig. 5.

Final snapshots at the end of the 100 ns MD simulations for Queuine (A), Thiamine (B), and Gemcitabine (C)

Molecular mechanics-generalized born surface area (MM-GBSA)

Docking simulations and binding affinities require validation, and the free energy of ligand binding can be estimated using the MM-GBSA method, which provides a more accurate representation of actual binding energies [71]. In this approach, for each 100 ps frame, MM-GBSA energies are calculated and averaged over 10 frames which are provided in Table 3. Crucial energy contributions such as coulombic (ΔEcoulomb), covalent (ΔEcovalent), solvation (ΔEsolvGB), and van der Waals (ΔEvdW) contributions are displayed. As presented in the last row, the overall free energy of binding values (ΔGbindtotal) accounting for all energy contributions for Gemcitabine, Queuine, and Thiamine are estimated to be approximately − 18, -50, and − 47 kcal/mol, respectively. These results agree with the results of the molecular docking and molecular dynamics simulations, suggesting that Queuine and Thiamine may be stronger binders and inhibitors than Gemcitabine.

Table 3.

MM-GBSA results showing energy terms and total free energy of binding of drug molecules

Energy Terms (kcal/mol)	Gemcitabine	Queuine	Thiamine
ΔEcoulomb1	-13.53 -/+7.75	-37.27 -/+5.08	7.55 -/+6.85
ΔEcovalent2	0.48 -/+1.73	3.32 -/+1.51	8.42 -/+3.45
ΔEsolvGB3	13.69 -/+7.90	44.32 -/+2.69	-6.64 -/+4.28
ΔEvdW4	-12.32 -/+6.87	-31.20 -/+2.56	-29.23 -/+4.72
ΔG bind total 5	-18.00 -/+9.54	-50.07 -/+4.57	-47.21 -/+12.10

¹ Coulomb energy contribution

² Covalent binding energy contribution

³ Generalized Born electrostatic solvation energy contribution

⁴ van der Waals energy contribution

⁵ Total binding free energy

ADMET analysis

The analysis of drug-like and ADMET properties is tabulated in Table 4. Molecules are nontoxic in mutagenic potential (AMES) tests. More ADME and Toxicity parameters are presented in the supporting file (Tables S1 and S2).

Table 4.

Compared with those of the control drug gemcitabine, the drug-like and ADMET properties of Queuine and thiamine

Molecule name	MW1 (g/mol)	HBD2	HBA3	log P4	HIA5 (%)	AMES6 toxicity	TPSA7 (Å)
Gemcitabine	263.2	3	7	0.14	98	-	110.6
Queuine	277.3	6	5	-1.6	94.6	-	140
Thiamine	265.4	2	3	-2.1	90	-	104.2

¹ Molecular weight (Pubchem) [72]

² H-bond donors (Drug Bank) [47]

³ H-bond acceptors (Drug Bank)

⁴ Partition coefficient (ALOGPS) [73]

⁵ Human intestinal absorption (admetSAR) [74]

⁶ Mutagenic potential (admetSAR)

⁷ Topological polar surface area (Drug Bank)

Effects of reagents on cell viability (MTT assays)

The effects of Queuine, Gemcitabine, and Thiamine on the viability of the Panc-1 cell line were evaluated via the MTT assay as described previously [48]. The results are depicted in Fig. 6. Compared with those of the control group (without drug treatment), the survival rates of the groups treated with 5 µM Queuine and 25 µM Gemcitabine for 48 h were significantly lower (53%, 66%) (p < 0.05), whereas the groups treated with concentrations below these concentrations presented at least 80% viability (Fig. 6A and C). Furthermore, the survival rates of the cells treated with 50 µM Gemcitabine were significantly lower than those of the control cells (p < 0.01) (Fig. 6).

Fig. 6.

Viability of Panc-1 cells compared with that of the control group after exposure to different concentrations of Queuine (A), Thiamine (B) and Gemcitabine (C) for 48 h. The results represent the average ± SEM of the results from each experiment, which were repeated three times at different times with the same concentration ranges. The statistical significance was evaluated according to a p-value of < 0.05.Compared with the control, *p< \0.05, **p< \0.01

In conclusion, cytotoxic effects were observed at concentrations of 5 µM for Queuine and 50 µM for Gemcitabine (51%). In contrast, Panc-1 cell viability was reduced to at most 80%, even at high Thiamine concentrations, such as 10,200 µM (Fig. 6B). Consequently, Queuine was found to be more effective than Gemcitabine at lower concentrations. Our MTT results confirmed the ability of our candidate molecules to penetrate the cellular barrier and exert effects on this PC model cell line. When IC₅₀ values were compared, Queuine was found to be almost 10 times more effective than Gemcitabine (Table 5).

Table 5.

Half inhibitory concentration (IC₅₀) values of the test compounds

Test Compound	IC50 ± SEM(µM)
Gemcitabine	64.17 ± 4.82
Queuine	5.95 ± 5.88

MAP4K4 enzyme activity by ELISA tests

The inhibitory effects of a naturally active compound, namely, Queuine, and the FDA-approved control drug Gemcitabine on MAP4K4 activity were investigated via ELISA method. The MAP4K4 enzyme was quantified in the presence or absence of Queuine or Gemcitabine at the end of the series of reactions as described in the kit protocol. Our results indicated that, compared with those in the control group, the enzyme activity in the Queuine (0.5–6 µM) and Gemcitabine (5–60 µM) treated groups decreased in a dose-dependent manner (Fig. 7). The reduction in enzyme levels with Queuine treatment was statistically significant across all the concentrations (p < 0.001) (Fig. 7A). For Gemcitabine, the difference was significant up to a concentration of 30 µM (p < 0.001), but the significance decreased at 60 µM (p < 0.1) (Fig. 7B). Furthermore, a comparative analysis between Queuine and Gemcitabine revealed that Queuine at a low concentration (0.5 µM) reduced enzyme levels approximately fourfold more than Gemcitabine at a low concentration.

Fig. 7.

Effects of different concentrations of Queuine and Gemcitabine on MAP4K4 activity. Absorbance values on the y-axis represent the enzyme amount measured using an ELISA kit, with different concentrations of Queuine (A) and Gemsitabine (B) indicated on the x-axis. The differences between the bar pairs marked with * (p < 0.05) and *** (p < 0.001) are significant

Combination therapy studies

Combination therapy studies were carried out using Queuine and Gemcitabine to explore the potential for a synergistic effect. Figure 8 demonstrates the cell viability of the Panc-1 cells treated with different combination concentrations of Queuine and Gemcitabine. Queuine at concentrations of 0.25 and 1.25 µM were combined with Gemcitabine at concentrations of 0.05–2.5 µM. The results indicate that there is a significant effect of the combination of Queuine and Gemcitabine on cell viability with a higher efficacy at lower doses. Queuine was previously shown to be more potent at lower concentrations compared to Gemcitabine in individual use (Fig. 6A and C). The concentrations of 0.25 and 1.25 µM resulted in approximately 94% and 86% cell viability whereas Gemcitabine alone has resulted in 99 − 87% cell viability at investigated concentrations.

Fig. 8.

Viability of Panc-1 cells compared with that of the control group after exposure to combined treatment of Queuine (QUE) and Gemcitabine (GEM) for 48 h. A) Queuine (0.25 µM) with gemcitabine combination, B) Queuine (1.25 µM) with gemcitabine combination

In contrast, the combined treatment of Queuine (0.25 µM) and Gemcitabine (0.05–0.1 µM) demonstrated significant therapeutic effects, with notably reduced viabilities of 84–86% compared to monotherapy. Particularly, survival rates were significantly lower (65%, 66%, p < 0.05) in groups treated with 0.25 µM Queuine and 0.5–1.25 µM Gemcitabine. Conversely, a surprising increase in cell viability to 79% was observed with Gemcitabine 2.5 µM and Queuine 0.25 µM treatment (Fig. 8A). At a higher concentration of Queuine (1.25 µM) combined with a similar Gemcitabine range (0.05–0.1 µM), further decreases in cell viability were observed (72% and 73%). The group treated with 1.25 µM Queuine and 0.5 µM Gemcitabine also exhibited significantly lower survival rates (65%, p < 0.05). Similarly, cell viability increased to 77–78% with Gemcitabine 1.25–2.5 µM and Queuine 1.25 µM treatment, respectively (Fig. 8B).

Additionally, we performed a synergistic effect study of Queuine and Gemcitabine on MAP4K4 activity detected by ELISA test. The combination of different concentrations of both molecules showed significant enzyme inhibition at (p < 0.001), compared to the control group (only enzyme). Figure 9 depicts the MAP4K4 ELISA tests results for the combined use of Queuine and Gemcitabine specifically for the three significant combinations obtained in Fig. 8.

Fig. 9.

Synergetic effects of Queuine and Gemcitabine on MAP4K4 activity. Absorbance values represent the enzyme amount measured using an ELISA kit. The difference between bar pairs marked with *** are significant at p < 0.001

Among the three combination therapy concentrations, the lowest amount of free enzyme was observed for 0.25µM Queuine + 0.5µM Gemcitabine. Increasing concentrations of Gemcitabine shifted the interaction from a synergistic to a suppressive effect due to drug-drug interactions and the emergence of competitive mechanisms.

Discussion

In the present study, novel natural source compounds were proposed to substitute the FDA-approved drug Gemcitabine with superior activity and less toxicity to combat PC. In silico studies were validated by in vitro chemical and biological tests to elucidate that Queuine might be a promising nutraceutical molecule serving as a MAP4K4 inhibitor. Molecular docking, supported by molecular dynamics simulations, is a widely used and effective approach in recent cancer-related studies for discovering novel drugs and identifying critical mutation sites [75]. Queuine was shown to bind to the enzyme with a greater affinity than Gemcitabine via both in silico analysis, consisting of molecular docking and molecular dynamics simulations, as well as chemical analysis via enzyme-linked immunosorbent assay (ELISA) and biological analysis via in vitro cell culture experiments. Docking simulations demonstrated that Gemcitabine has the most significant interaction with MAP4K4 through hydrogen bonding with Glu 106. On the other hand, Queuine interacts with the enzyme via Cys108 in addition to Glu106, which results in stronger hydrogen bonding than does Gemcitabine (Fig. 1; Table 2). These amino acids reside in the minima of the fluctuation profiles, which is consistent with previous studies reporting that the hinge regions of RMSF generally overlap with functionally important conserved areas pointing to the binding interface and interacting residues [76, 77]. Queuine interacts with the MAP4K4 binding site for more than 50% of the simulation time, whereas the contacts of Thiamine are shorter-lived. These findings suggest that Queuine may be a stronger binder than can be achieved with Thiamine or Gemcitabine. Gemcitabine was observed to diffuse out of the binding site by the end of the MD simulations.

We obtained a promising IC₅₀ value for Queuine, approximately 5.95 µM, whereas that of Gemcitabine was approximately 64.17 µM, demonstrating the almost tenfold potency of Queuine over the benchmark FDA-approved drug (Fig. 5; Table 5). The other nutraceutical molecule, Thiamine, is nontoxic and safe even at elevated concentrations. In our previous research involving neuroblastoma cell lines, similar results were obtained for Thiamine at a wide range of concentrations [48]. Other studies have shown that Thiamine can inhibit the growth of cancer cell lines at very high doses [78]. This study aimed to explore the impact of low-dose Thiamine on the PANC-1 cell line. These findings indicated that low doses of Thiamine promoted the growth of cancer cells, whereas high doses, although not toxic at the concentrations tested here, resulted in reduced cell viability. The mechanism underlying this dose-dependent effect of Thiamine remains incompletely understood and warrants further investigation. Other studies investigating the impact of Thiamine on PC reported that, owing to its role in regulating energy metabolism, Thiamine deficiency impacts cells and tissues. Unfortunately, either a protective or cancer-inducing role of Thiamine has been hypothesized; thus, the available data are limited and conflicting [79, 80]. Previous studies reported IC₅₀ values of Gemcitabine in PANC-1 cell lines ranging from 10 to 500 µM [81–84]. The IC₅₀ value of Gemcitabine was approximately 60 µM in the present study, which is within this range. Gemcitabine is an approved medication for pancreatic cancer; however, there is no clear evidence directly linking its mechanism of action to MAP4K4 inhibition. While MAP4K4 may not be Gemcitabine’s primary target, it could still play a contributory role. Therefore, to the best of our knowledge, the inhibition of MAP4K4 by both Gemcitabine and Queuine may represent a novel finding that has not yet been reported in the literature. Here, we selected Gemcitabine as a control to compare its relative effectiveness with the proposed molecules. Our findings indicate that both Gemcitabine and Queuine exhibit inhibitory effects on MAP4K4, supported by both in silico and in vitro evidence. Furthermore, we discovered a potential synergistic effect when they were used in combination.

The potency of Queuine was also validated via ELISA, which provides a quantitative analysis of the MAP4K4 enzyme level. The level of unbound free MAP4K4 enzyme was significantly lower in the presence of Queuine than in the presence of Gemcitabine (Fig. 7). We propose that Queuine may interfere with the enzyme’s active site in the ELISA by binding to the N-terminal kinase domain or C-terminal citron-homology domain, potentially disrupting the enzyme structure and function. These findings were confirmed by molecular docking and molecular dynamics simulations, indicating that Queuine may serve as a more potent inhibitor than Gemcitabine. Furthermore, the synergic effect study revealed that Queuine is able to inhibit the enzyme with higher potential than when it is in combination with Gemcitabine.

In our recently published study, we identified Queuine and Thiamine as potential acetylcholinesterase (AChE) inhibitors for the treatment of Alzheimer’s disease [48]. Interestingly, the present study also highlighted these nutraceutical group molecules as potential MAP4K4 inhibitors via in silico screening, as validated by chemical and biological evaluations, which need further clarification via in vivo experiments. The results obtained in this study paved the way for the proposal of Queuine as a promising novel MAP4K4 inhibitor and anticancer agent, in addition to its previously discovered neuroprotective effect. Previous studies have reported a positive correlation between cholinergic and kinase pathways, supporting our findings. AChE inhibitors act through the cholinergic pathway, as elevated levels of acetylcholine stimulate muscarinic and nicotinic receptors. Consequently, the activation of protein kinase C (PKC) and/or the mitogen-activated protein (MAP) kinase pathway increases soluble amyloid precursor protein alpha (sAPPa) levels and reduces Ab [85].

In a study conducted on 861 PC patients to increase the effectiveness of Gemcitabine, it was given in combination with albumin-bound nab-paclitaxel [86, 87]. As a result of this study, the survival time was reported to be 8.5 months in 35% of patients receiving Gemcitabine + paclitaxel treatment, while the value was 6.7 months in 22.2% of patients receiving only Gemcitabine, which led to the preference for Gemcitabine + paclitaxel combined therapy as the primary treatment for PC patients in the metastatic stage. Although this combined treatment significantly increased overall survival and response rate, it caused serious side effects by increasing the rates of peripheral neuropathy and myelosuppression. In the later stages of Gemcitabine and related treatments, the effectiveness of the treatments becomes insufficient due to the resistance of PC cells. It has also been reported that Gemcitabine treatment causes the development of resistance in a short time, making chemotherapy ineffective [88]. Another combined drug treatment is FOLFIRINOX, which consists of combinations of 5-fluorouracil, folic acid, irinotecan, and oxaliplatin, but its side effects are much more toxic [89, 90]. In the present study, synergistic therapy and dose determination were conducted based on previous studies. While Gemcitabine has documented synergy studies in the literature, no such studies exist for Queuine. Therefore, the synergy experiments were performed within safe dose ranges. The safe dose was identified as up to 2.5 µM for Gemcitabine and 1.25 µM for Queuine (Fig. 6), and these ranges were used accordingly. Two different doses of Queuine were tested, while a range of concentrations was explored for Gemcitabine. This approach allowed us to observe the combined effects of Queuine at both low and high doses with Gemcitabine. The combination therapy of Queuine and Gemcitabine investigated in the present study, exhibited a strong synergistic effect, significantly suppressing PC cell proliferation at low doses. This finding contrasts with the results of current clinical trials using high-dose Gemcitabine and Paclitaxel combinations, which often induce severe adverse effects. Analysis of both Queuine concentrations with the Gemcitabine combination yielded significant cell death as the Gemcitabine concentration increased, yet after a point, this effect was observed to be lowered (Figs. 8 and 9). Especially, drug-drug interactions and suppressive effects can be evident in the combination of drugs leading to similar results. This result is in good agreement with a recent combination therapy study about PC, implying the fact that “when more is less”. Authors reported suppressive interactions in three-drug combinations, Cisplatin, Gemcitabine and PD-1 immunotherapy antibody. Cisplatin and Gemcitabine unexpectedly exerted opposite effects on the therapeutic activity of PD-1 antibody. Gemcitabine was observed to antagonize the therapeutic effect of PD-1 antibody in human PC tissues, while in contrast, Cisplatin showed synergistic activity with PD-1 [91]. The findings from this study suggest that combining Queuine with Gemcitabine may enhance the therapeutic potential by increasing Gemcitabine’s effectiveness at lower concentrations. This approach could enable reduced therapeutic doses, potentially leading to the development of safer and more effective treatments for pancreatic cancer (PC).

Conclusion

This study aims to discover novel natural compounds with enhanced efficacy and lower toxicity compared to FDA-approved drugs like Gemcitabine for treating PC. In silico discovery, followed and validated by in vitro assays was conducted to determine the half-maximal inhibitory concentrations (IC₅₀) for the target enzyme MAP4K4. MAP4K4 ELISA tests were performed to analyze the target protein interactions and quantify biomolecular binding. Thus, the inhibitory activities of Queuine and Gemcitabine on this enzyme were compared. Our results suggest that Queuine, a nutraceutical compound, could be a promising MAP4K4 inhibitor. Queuine binds to the enzyme’s active site with a higher affinity resulting in lower binding free energy when compared with Gemcitabine. The IC₅₀ values indicate that Queuine is nearly ten times more effective. Additionally, Thiamine, another nutraceutical molecule, shows a high IC₅₀ value, indicating that it is safe even at elevated concentrations. Our findings demonstrated that Queuine was more potent than Gemcitabine, even at lower concentrations. However, the most striking result was observed when the two drugs were combined. The combination, particularly at low doses, exhibited a higher-than-expected cytotoxic effect, suggesting a synergistic interaction between the two drugs. In contrast, when combined with Gemcitabine at equal or higher concentrations, Gemcitabine exhibited an inhibitory effect on Queuine, suggesting a competitive interaction and resulting in competitive enzyme inhibition. These findings highlight the potential of combining Queuine and Gemcitabine as a novel therapeutic strategy for PC, as well as the importance of balancing the concentrations of the two drugs. Future research could further clarify the effects of Queuine using in vivo PC models.

Supplementary Information

Below is the link to the electronic supplementary material.

Abbreviations

PC

Pancreatic cancer

IC₅₀

Half inhibitory concentration

DMEM

Dulbecco’s Modified Eagle Medium

FBS

Fetal Bovine Serum

DMSO

Dimethyl sulfoxide

MAP4K4

Human Mitogen-activated Protein Kinase 4

MD

Molecular dynamics

RMSF

Root mean square fluctuation

RMSD

Root mean square deviation

MM-GBSA

Molecular Mechanics-Generalized Born Surface Area

ΔEcoulomb

Coulombic energy contribution

ΔEcovalent

Covalent energy contribution

ΔEsolvGB

Generalized born solvation energy contribution

ΔEvdW

van der Waals contribution

ΔGbindtotal

Total free energy of binding

ADMET

Absorption-Distribution-Metabolism-Excretion-Toxicity

MW

Molecular Weight

HBD

Hydrogen bond donor

HBA

Hydrogen bond acceptor

log P

Octanol/water partition coefficient

HIA

Human intestinal absorption

AMES

Mutagenicity

TPSA

Topological polar surface area

Author contributions

N.K.C has conceptualized the project, conducted the simulations and experiments, prepared the figures, and wrote the main manuscript. M.G. has conceptualized the project, conducted the simulations and experiments, prepared the figures, and wrote the main manuscript. N.D.F. conducted the experiments. T.B. conducted the experiments and wrote the main manuscript. S.T. conducted the experiments and wrote the main manuscript.All authors reviewed the manuscript.

Funding

The authors declare that no funding was received.

Data availability

The data underlying this study are available in the published article and supporting information. Molecules used in this study are downloaded from Drug Bank (www.drugbank.com). Protein structure is retrieved from Protein Data Bank (www.rcsb.org). All simulations are performed with commercial software Schrodinger Maestro Suite, version 13.1 (www.schrodinger.com). Further experimental data analyzed during the current study are available from the corresponding author upon request.

Declarations

Ethical approval

Not applicable.

Consent for publication

No humans/animals were used for studies that are the basis of this research.

Competing interests

The authors declare no competing interests.