N-benzylbenzamide derivative (SBM685) as a novel MDR1 inhibitor for overcoming 5 fluorouracil resistance in gastric cancer through computational and in vitro analysis

Abstract

Background

The overexpression of Multidrug Resistance Protein 1 (MDR1) contributes to the failure of existing chemotherapeutic agents like 5-fluorouracil (5FU). This study aims to identify and evaluate a novel small molecule inhibitor of MDR1 in 5FU-resistant gastric cancer (GC).

Methods

Comprehensive in silico approach using Discovery Studio Visualizer, Protein-Ligand Interaction Profiler, GROMACS, and GMX_MMPBSA methods were employed to identify potential MDR1 inhibitors from the ZINC natural product-like compound library. MKN-45 and SNU-5 cells were utilized in cell proliferative and flow cytometry assays for in vitro validations.

Results

Virtual screening identified SBM685 as a promising MDR1 inhibitor, with a docking score of -9.4 kcal/mol. Root Mean Square Deviation (RMSD) values were around 0.2 nm. Gibbs binding free energy calculations indicated a highly favorable binding energy of -49.02 kcal/mol. SBM685 reduced the MDR1-positive (MDR1⁺) cell population in MKN-45 and SNU-5 gastric cancer cells. SBM685 also inhibited the proliferation of parental MKN-45 cells as well as MDR1⁺ MKN-45 and MDR1⁺ SNU-5 cells. In contrast, 5-fluorouracil (5-FU) showed limited efficacy in suppressing proliferation in MDR1⁺ gastric cancer cells. In addition, SBM685 induced apoptosis in both parental and MDR1⁺ gastric cancer cells, whereas 5-FU failed to promote apoptosis in MDR1⁺ cells.

Conclusion

The combination of computational and in vitro evaluations indicates that SBM685 is a potent MDR1 inhibitor which is also effective in MDR1⁺ GC cells where 5FU exhibited resistance. The findings of this study highlight SBM685 as a promising candidate for further preclinical evaluations, that could pave the way for new therapeutic strategies in overcoming the MDR1-mediated chemoresistance of GC.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12672-026-04767-x.

Introduction

Gastric cancer (GC) is one of the most prevalent malignancies globally, ranking as the fifth most common cancer and the third leading cause of cancer-related deaths [1]. This aggressive disease is often diagnosed at an advanced stage, contributing to its poor prognosis and high mortality rates [2]. The pathogenesis of GC involves complex genetic and environmental factors, where key molecular pathways such as Wnt/β-catenin, PI3K/AKT/mTOR, and p53 are frequently implicated. These pathways play crucial roles in cell proliferation, apoptosis, and differentiation, and their dysregulation contributes to the initiation and progression of GC [3, 4]. Despite advancements in surgical techniques and chemotherapy, the survival rate for advanced GC remains low, underscoring the need for more effective therapeutic strategies [5].

Among the various chemotherapeutic agents used in treating GC, 5-fluorouracil (5FU) has been a cornerstone due to its ability to inhibit thymidylate synthase, thereby disrupting DNA synthesis and inducing cell death [6]. However, the clinical efficacy of 5FU is often compromised by the development of drug resistance [7]. Overexpression of multidrug resistance protein 1 (MDR1), also known as P-glycoprotein (P-gp), is one of the main mechanisms behind this resistance [8]. MDR1 functions as an ATP-dependent efflux transporter, expelling chemotherapeutic drugs from cancer cells and thus reducing their intracellular concentrations [9]. This sort of efflux action diminishes the cytotoxic effects of chemotherapeutic drugs like 5FU, leading to treatment failure and disease progression.

The importance of MDR1 in 5FU resistance cannot be overstated, as its overexpression is correlated with poor therapeutic outcomes and reduced patient survival [10]. Inhibiting MDR1 has emerged as a promising approach to overcoming resistance, augmenting the intracellular accumulation of chemotherapeutic agents, and restoring their efficacy. Several methods have been explored to inhibit MDR1, which includes the use of inhibitors, monoclonal antibodies, and RNA interference [11]. However, the clinical success of these strategies has been limited by issues such as toxicity, off-target effects, and insufficient potency. Therefore, there is a critical need for the discovery and development of novel MDR1 inhibitors that are both effective and safe.

The search for novel MDR1 inhibitors has increasingly relied on advanced computational methods, such as virtual screening, MD, and MDS, to identify promising candidates from vast chemical libraries [12]. These techniques enable the efficient and cost-effective screening of compounds, allowing researchers to pinpoint molecules with high binding affinity and favorable pharmacokinetic properties [13]. Subsequently, preclinical evaluations are essential to validate the efficacy and safety of these candidates. This study aims to contribute to this endeavor by identifying a new small molecule inhibitor of MDR1 through a combination of computational and experimental approaches. By targeting the ATP-binding domain of MDR1, this study ought to develop a compound that can effectively inhibit its efflux function, thereby improving the therapeutic outcomes of 5FU in resistant GC.

Materials and methods

Materials

Reagents and chemicals were sourced from Sigma Aldrich (St. Louis, MO, USA). The Vero, MKN-45, and SNU-5 cell lines were acquired from the American Type Culture Collection (ATCC, Rockville, MD, USA). The Annexin V assay kit was supplied by Merck Millipore (Burlington, MA, USA). The anti-MDR1 polyclonal primary antibody and the FITC-tagged secondary antibody were obtained from Thermo Fisher Scientific (USA).

Methods

Structure retrieval and high-throughput virtual screening

The crystal structure of MDR1 (PDB ID: 4KSB) [14] was sourced from the Protein Data Bank (https://www.rcsb.org/structure/4KSB) and prepared for docking studies using Discovery Studio Visualizer. During preprocessing, after removing the water molecules, the polar hydrogens were inserted into the protein structure to ensure accurate interaction modeling. Any missing side chains and atoms were reconstructed using the SwissPDB viewer to complete the protein structure. A docking grid box centered on the protein-protein interaction interface was defined with dimensions of 20 units on each side. This setup facilitated the identification of potential binding sites for inhibitors. High-throughput Virtual Screening (HTVS) was performed using the ZINC natural product-like compound library (https://zinc.docking.org/substances/ZINC000008918500/ ). The Diversity-based High-Throughput Virtual Screening (D-HTVS) module from SiBioLEAD (https://sibiolead.com/), as detailed elsewhere [15], was employed to screen the library efficiently. Protein-ligand interactions were analyzed using the Protein-Ligand Interaction Profiler (PLIP) plugin, providing detailed insights into the binding modes and interaction profiles of the screened compounds with MDR1. The results were visualized using Discovery Studio Visualizer, allowing for a comprehensive evaluation of the potential binding interactions and aiding in the selection of promising MDR1 inhibitors.

Molecular dynamics (MD) simulation

The Molecular Dynamics (MD) simulation of the MDR1 protein, both in complex with the target ligand and as a control (unbound), was carried out using an MD simulation server available at www.sibiolead.com, which utilizes the GROMACS simulation package. The ligand topology was generated using AMBERTOOLS and the ACPYPE package, while the OPLS/AA force field was applied to parameterize the simulation system [16].

To achieve appropriate hydration, the MDR1-ligand complex was first immersed in a triclinic box containing Simple Point Charge (SPC) water. To duplicate physiological conditions, the system was neutralized with NaCl counterions and then replenished with 0.15 M NaCl. The simulation setup, including the protein-ligand complex, SPC water, and salt ions, was energy minimized over 5000 steps using the steepest descent approach. Following that, the system was equilibrated for 300 ps at constant temperature and pressure using the NVT/NPT procedure. The MD simulation was then run for 100 ns using a leap-frog integrator, with trajectory frames saved every 10 ps. Analysis of the simulation trajectories was performed using GROMACS in-built scripts, and results were visualized with xmgrace. This detailed analysis provided insights into the dynamic behavior and stability of the MDR1-ligand complex over the simulation period.

Gibbs binding free energy calculation

The Gibbs binding free energy (ΔG_binding) for the protein-ligand complexes was calculated using the GMX_MMPBSA method [17]. Trajectory frames saved at 2 ns intervals throughout the entire 100 ns simulation period were used for this analysis. The calculated binding free energies provided valuable insights into the energetics of the MDR1-ligand interactions, supporting the detailed exploration of their dynamic behavior and stability.

Cell proliferation assay

Cancer cells and Vero cells were grown in a complete growth medium under standard conditions. Assays were performed once the cells reached 80% confluency. Cell proliferation was assessed using the MTT assay, as detailed elsewhere [18]. Briefly, MKN-45, SNU-5, or Vero cells (5 × 10³ cells/well) were seeded into 96-well plates with standard growth medium. The cells were treated with varying concentrations of SBM685 or 5FU for 48 h. Following the treatment, the medium was removed, and the cells were incubated with 100 µL of MTT solution (1 mg/mL) for 4 h. The formazan crystals formed were dissolved in 200 µL of DMSO, and absorbance was measured at 560 nm. Percent inhibition was calculated with GraphPad Prism 6.0 to determine the 50% Growth Inhibition (GI₅₀) values.

MDR1 analysis by flow cytometry

MKN-45 or SNU-5 cells were initially treated with 2.20 µM or 2.75 µM of SBM685, respectively, and incubated for 4 h in a 5% CO₂ environment at 37 °C, alongside appropriate untreated and induction controls. After this pre-treatment, the cells, including those in the induction control group, were exposed to 2.5 µM 5-azacytidine (5AC) and 100 ng/ml Trichostatin A (TSA) for 48 h. Following this, the cells were washed twice with sterile PBS and resuspended in HBSS buffer. The cells were then incubated with 1 µg/ml of anti-MDR1 polyclonal unconjugated antibody for 30 min, followed by a 30-minute incubation with a FITC-conjugated secondary antibody in the dark. Afterward, the cells were washed twice with PBS and resuspended in HBSS buffer. Flow cytometric analysis was performed by acquiring 10,000 events using the Guava easyCyte flow cytometer.

Cytotoxicity assay in MDR1 expressed GC cells

MKN-45 or SNU-5 cells were exposed to 2.5 µM 5-azacytidine (5AC) and 100 ng/ml Trichostatin A (TSA) for 48 h to induce the cells. Followingly, the cells were collected and plated at a density of 5 × 10³ cells per well in 96-well culture plates with standard growth medium. They were then treated with different concentrations of SBM685 or 5FU for 48 h. Cell viability was assessed using the MTT assay as detailed in Sect.  2.2.4.

Apoptosis analysis by annexin V assay

MKN-45 or SNU-5 cells were treated with 2.5 µM 5-azacytidine (5AC) and 100 ng/ml Trichostatin A (TSA) for 48 h to induce them. Following treatment, the cells were collected, washed with sterile PBS, and resuspended in the standard growth medium. They were then seeded at a density of 0.5 × 10⁶ cells per well in 6-well plates and exposed to various concentrations of SBM685 or 5-5FU. The cells were incubated in a 5% CO₂ environment at 37 °C for 48 h. After incubation, the cells were harvested, washed with buffer from the kit, and stained with 0.25 µg/mL Annexin V reagent for 15 min in the dark. Following two additional washes, the cells were resuspended in a kit buffer with 0.5 µg/mL propidium iodide. Flow cytometry was conducted by a Guava easyCyte system, and with InCyte software. Data was presented using GraphPad Prism software (version 6.0; La Jolla, CA, USA).

Results

High-throughput virtual screening of natural product-like compounds against MDR1

To discover potential inhibitors of MDR1 activity, natural product-like compounds from the ZINC database were screened. The process utilized a high-resolution experimental structure of MDR1 retrieved from the PDB (4KSB), revealing three key domains: the substrate binding domain, transmembrane region, and nucleotide-binding domain (Fig. 1a). The analysis predicted a spacious ligand-binding cavity flanking the nucleotide-binding region (Fig. 1b), targeted for inhibition of MDR1 activation (Fig. 1c).

Fig. 1.

Structure of MDR1 and Targeted Binding Regions: a High-resolution structure of MDR1 (PDB ID: 4KSB) highlighting three critical domains: the substrate binding domain, the transmembrane region, and the nucleotide-binding domain. b Predicted ligand-binding cavities within the MDR1 structure, emphasizing the large pocket at both sides of the nucleotide-binding region. c Targeting strategy for inhibiting MDR1 activation, focusing on the nucleotide-binding region

Diversity-based high-throughput virtual screening (D-HTVS) focused on identifying small molecules with high affinity for the ATP-binding site of MDR1 from the ZINC database. From approximately 275,000 compounds, D-HTVS identified 1692 potential candidates based on docking scores (Fig. 2a). Further refinement included filtering compounds scoring below − 8.9 kcal/mol, which represented less than 2 standard deviations from the mean (Fig. 2b).

Fig. 2.

High-Throughput Virtual Screening (HTVS) Results: a Ranking of compounds from the ZINC database based on docking scores, showing the distribution of scores and highlighting top candidates. b Identification of lead compounds with docking scores below − 8.9, indicating high-affinity binding to the ATP-binding region of MDR1. c Binding pose analysis of SBM685 within the nucleotide-binding region of MDR1, demonstrating its preferred binding conformation. d 2D representation of SBM685, showing its chemical structure and functional groups

The top-ranked compound, N-benzylbenzamide derivative ( https://www.molport.com/shop/compound/MolPort-002-523-962 ) (Internal reference code-SBM685), exhibited a promising docking score of -9.4 kcal/mol, warranting detailed analysis (Fig. 2c). SBM685 was found to bind preferentially to the nucleotide-binding region of MDR1, as depicted in its 2D representation (Fig. 2d).

Protein-ligand interaction analysis shows SBM685 binds effectively to MDR1

The number and strength of interactions between SBM685 and MDR1 were analyzed using the protein-ligand interaction profiler from Discovery Studio Visualizer. An interaction energy of -9.4 kcal/mol for SBM685 with MDR1 was observed. Hydrogen bonds were formed by SBM685 with Asp1196, and pi-pi stacking interactions were noted with critical amino acid residues at the ATP-binding domain, including Ile1111, Tyr1040, and Val1076 (Fig. 3a & b). The analysis also indicated that SBM685 fits well within the ATP binding region of MDR1, suggesting that SBM685 binds efficiently to MDR1 and may inhibit its activation.

Fig. 3.

Protein-Ligand Interaction Analysis: a Detailed interaction map of SBM685 with MDR1, illustrating hydrogen bonds with Asp1196 and pi-pi stacking interactions with Ile1111, Tyr1040, and Val1076. b Energy profile of SBM685 interactions with MDR1, indicating a binding energy of -9.4 kcal/mol

Molecular dynamic simulation of SBM685 bound to MDR1

To comprehensively understand the binding stability and dynamics of SBM685 in complex with MDR1, an extensive 100-nanosecond (ns) fully-solvated atomistic molecular dynamics (MD) simulation was conducted. The MDR1::SBM685 complex was placed within a triclinic simulation box, fully solvated with Simple Point Charge (SPC) water. To mimic physiological conditions, counterions (NaCl) were added, achieving a concentration of 0.15 M NaCl. Before the main simulation, a crucial energy minimization step of 5000 steps using the steepest descent method was employed to eliminate steric clashes and optimize the system for equilibration. Subsequently, the system underwent a 300-picosecond equilibration period, allowing it to attain a stable state before initiating the main 100ns simulation run.

The GROMACS simulation software, accessed through a web-based application (www.sibiolead.com), was utilized to observe the dynamic behavior of SBM685 bound to MDR1 over the specified time frame. Snapshots taken at different points during the 100ns simulation indicated a consistent and stable binding of SBM685 to MDR1 (Fig. 4a & b). The Root Mean Square Deviation (RMSD) of the ligand SBM685 was monitored throughout the simulation, with RMSD values consistently remaining around 0.2 nm, signifying a stable binding interaction (Fig. 4c). Additionally, hydrogen bond (H-bond) analysis demonstrated a robust and stable H-bond pattern for SBM685 throughout the simulation, indicating sustained interactions between the ligand and the receptor (Fig. 4d). These findings collectively affirm the stability and enduring nature of the binding between SBM685 and MDR1, providing valuable insights into their dynamic interaction.

Fig. 4.

Molecular Dynamics (MD) Simulation of MDR1::SBM685 Complex: a Snapshot of the initial configuration of the MDR1::SBM685 complex at the start of the 100 ns MD simulation. b Snapshot of the MDR1::SBM685 complex after 100 ns of simulation, showing consistent binding of SBM685. c Root Mean Square Deviation (RMSD) plot of SBM685 over the 100 ns simulation period, demonstrating stable binding with values around 0.2 nm. d Hydrogen bond (H-bond) analysis of SBM685 with MDR1 throughout the simulation, shows a stable interaction pattern

MMPBSA-based gibbs binding free energy estimation of SBM685

To further elucidate the binding stability of SBM685 with MDR1, Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) based binding energy calculations were conducted. A total of 50 frames, selected from the 100-nanosecond (ns) simulation trajectory, were utilized for this analysis. The gmx_MMPBSA tool was employed to estimate the binding free energy. The results revealed a highly favorable binding energy estimate of -49.02 kcal/mol for SBM685, as depicted in Fig. 5a. This value strongly indicates a robust and stable binding interaction between SBM685 and MDR1. The negative binding energy signifies that the binding process is energetically favorable, reinforcing the notion of a strong affinity between the ligand and the protein.

Fig. 5.

Binding Free Energy Calculation: a Gibbs binding free energy (ΔG_binding) of SBM685 calculated using the Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) method from 50 frames over the 100 ns simulation period, showing a highly favorable binding energy of -49.02 kcal/mol

Collectively, the Molecular Dynamics (MD) simulation results, coupled with the MMPBSA-based binding energy estimate, suggest that SBM685 exhibits avid and stable binding to MDR1.

SBM685 inhibited GC cell proliferation

The efficacy of the lead compound SBM685 was tested in MKN-45 and SNU-5 GC cell lines. The compound dose effectively inhibited the proliferation of both these cells. The GI₅₀ value was identified as 2.19 µM and 2.74 µM for MKN-45 and SNU-5 cells respectively (Fig. 6a). Alongside this, the efficacy of 5FU was also tested in these cancer cells. 5FU exhibited GI₅₀ values of 1.06 µM and 1.60 µM in MKN-45 in MKN-45 and SNU-5 cells respectively (Fig. 6b). Besides these evaluations, the non-lethal dose of SBM685 in non-cancerous Vero cells was tested. The compound did not make a change to the viability of Vero cells up to 100 µM, while a decrease in the cell viability of Vero cells was observed beyond this concentration (Fig. 6c).

Fig. 6.

SBM685 inhibits gastric cancer cell proliferation. Dose–response curves and corresponding GI₅₀ (50% growth inhibition) values for MKN-45 and SNU-5 gastric cancer cells treated with a SBM685 (0.001–100 µM) and b 5-fluorouracil (5-FU; 0.001–100 µM) are shown. c The effect of SBM685 (0.001–100 µM) on the viability of non-malignant Vero cells is presented. Cells were treated for 72 h, and cell proliferation/viability was assessed using the MTT assay. Data represent mean ± SD from three independent biological experiments (n = 3), each performed in triplicate wells. GI₅₀ values were calculated by nonlinear regression using a four-parameter logistic model in GraphPad Prism version 6.0

SBM685 decreased MDR1 expression

To augment the computational predictions, we analyzed the MDR1 expression in MKN-45 and SNU-5 cells. Induction with 2.5 µM 5AC + 100 ng/ml TSA increased the MDR1 positive (MDR1⁺) population from 4.01 ± 1.34% to 61.47 ± 4.69% in MKN-45 cells (Fig. 7a) and 6.38 ± 1.08% to 54.19 ± 5.48% in SNU-5 cells (Fig. 7b). Treatment with SBM685 reduced the MDR1⁺ population to 11.32 ± 2.70% and 09.67 ± 3.19% in MKN-45 and SNU-5 cells respectively (Fig. 7a, b).

Fig. 7.

SBM685 reduces MDR1 expression in gastric cancer cells. The proportion of MDR1-positive cells in a MKN-45 and b SNU-5 gastric cancer cells was quantified by flow cytometry. MDR1 expression was induced by treatment with 5-azacytidine (5-AC; 2.5 µM) and trichostatin A (TSA; 100 ng/mL) for 48 h, followed by pre-treatment with SBM685 (2.2 µM for MKN-45 and 2.5 µM for SNU-5) for 24 h. Representative flow cytometry analyses and quantification of MDR1-positive populations are shown. Data represent mean ± SD from three independent experiments (n = 3), each performed in triplicate. Statistical analysis was conducted using one-way ANOVA followed by Tukey’s post hoc test, with p < 0.05 considered statistically significant

Effect of SBM685 and 5 FU in MDR1-induced GC cell proliferation

The efficacy of the lead compound SBM685 in the MDR1-induced GC cells in comparison to the standard 5FU compound was evaluated. SBM685 retained the antiproliferative effects in MDR1⁺ GC cells, with GI₅₀ values of 2.08 µM and 2.97 µM in MDR1⁺ MKN-45 and MDR1⁺ SNU-5 cells respectively (Fig. 8a). However, the efficacy of 5FU was greatly reduced with GI₅₀ values of 18.22 µM and 15.75 µM in MDR1⁺ MKN-45 and MDR1⁺ SNU-5 cells respectively (Fig. 8b).

Fig. 8.

Effect of SBM685 and 5-fluorouracil on proliferation of MDR1-induced gastric cancer cells. Dose–response curves and corresponding GI₅₀ values for MDR1-induced (MDR1⁺) MKN-45 and SNU-5 cells treated with a SBM685 and b 5-fluorouracil (5-FU) are shown. MDR1 induction was performed using 5-azacytidine (2.5 µM) and trichostatin A (100 ng/mL) for 48 h prior to drug treatment. Cells were exposed to increasing concentrations of each compound (0.001–100 µM) for 72 h, and cell proliferation was assessed using the MTT assay. Data are expressed as mean ± SD from three independent biological experiments (n = 3), each performed in triplicate wells. GI₅₀ values were calculated by nonlinear regression using a four-parameter logistic model in GraphPad Prism version 6.0

SBM685 efficiently induced apoptosis when compared to 5FU in MDR1⁺ induced GC cells

We next checked the apoptosis-inducing efficacy of SBM685 and 5FU in MKN-45 and SNU-5 cells. The near GI₅₀ values of SBM685 (2 µM for MKN-45; 3 µM for SNU-5 cells) and 5FU (1 µM for MKN-45; 1.5 µM for SNU-5 cells) were tested. SBM685 treatment increased total apoptotic cells from 3.11% to 31.80% and 3.65% to 38.1% in MKN-45 cells and SNU-5 cells respectively (Fig. 9a). 5FU treatment resulted in 37.7% and 32.1% total apoptotic cells in MKN-45 and SNU-5 cells respectively, while untreated MKN-45 and SNU-5 cells had 2.92% and 3.23% total apoptotic population in MKN-45 and SNU-5 cells respectively (Fig. 9b). When these concentrations were tested in MDR1-induced MDR1⁺ GC cells, SBM685 treatment increased total apoptotic cells from 2.56% to 28.83% and 2.73% to 35.53% in MDR1⁺ MKN-45 cells and MDR1⁺ SNU-5 cells respectively (Fig. 9c). However, 5FU treatment did not result in a significant apoptotic population in both MDR1⁺ GC cells tested (Fig. 9d).

Fig. 9.

SBM685 induces apoptosis in parental and MDR1-induced gastric cancer cells. Apoptosis was assessed by Annexin V–FITC/PI staining followed by flow cytometric analysis in MKN-45 and SNU-5 gastric cancer cells. Cells were treated for 48 h with a SBM685 (2 µM for MKN-45 and 3 µM for SNU-5) or b 5-fluorouracil (5-FU; 1 µM for MKN-45 and 1.5 µM for SNU-5). Quantification of early and late apoptotic populations is shown for parental cells and MDR1-induced (MDR1⁺) cells, including c MDR1⁺ MKN-45 and d MDR1⁺ SNU-5 cells. Data are presented as mean ± SD from three independent biological experiments (n = 3), each performed in triplicate. Statistical significance was determined using one-way ANOVA followed by Tukey’s post hoc test, with p < 0.05 considered statistically significant

Discussion

MDR1 plays a pivotal role in the development of chemoresistance in GC, particularly against the widely used chemotherapeutic agent 5-fluorouracil (5FU). MDR1 functions as an efflux transporter, actively pumping chemotherapeutic drugs out of cancer cells, thereby reducing their intracellular concentrations and diminishing their cytotoxic effects [19]. Overexpression of MDR1 (MDR1⁺) has been implicated in the failure of chemotherapy regimens, as it effectively lowers the accumulation of drugs within the tumor cells, leading to treatment resistance and poor clinical outcomes [20]. To address the challenge of MDR1-mediated drug resistance, a virtual screening approach was undertaken to identify potential inhibitors from a library of natural product-like compounds in the ZINC database. Utilizing the high-resolution structure of MDR1 (PDB ID: 4KSB), the screening specifically targeted the nucleotide-binding domain, a critical region for the transporter’s function. The diversity-based high-throughput virtual screening (D-HTVS) identified 1692 compounds with favorable docking scores from an initial pool of approximately 275,000. Further refinement, based on docking scores, led to the selection of SBM685, which demonstrated a top-ranking score of -9.4 kcal/mol. This score indicated strong potential for effective binding to the ATP-binding domain of MDR1 [21].

A detailed interaction analysis using the Discovery Studio Visualizer revealed multiple stabilizing interactions formed by SBM685 with key residues in the ATP-binding domain of MDR1. The hydrogen bond interaction by the compound with Asp1196 and pi-pi stacking interactions with Ile1111, Tyr1040, and Val1076 are crucial as they indicate strong binding affinity and the ability of SBM685 to occupy and potentially inhibit the functional site of MDR1 [22]. The fitting of SBM685 within the ATP-binding region suggests that the binding and hydrolysis of ATP may be effectively blocked, thereby inhibiting the efflux function of MDR1 [23].

To gain deeper insights into the binding stability and dynamics of SBM685, a 100-nanosecond fully-solvated atomistic molecular dynamics (MD) simulation was conducted. The Root Mean Square Deviation (RMSD) values for SBM685 remained around 0.2 nm, further corroborating the stability of the binding interaction [24]. The binding stability of SBM685 was further elucidated through Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) based binding energy calculations. Utilizing 50 frames from the MD simulation trajectory, the binding free energy of SBM685 to MDR1 was estimated using the gmx MMPBSA tool. The results of the binding energy were highly favorable, indicating a robust and stable interaction [24]. The negative binding energy suggests that the binding process is energetically favorable, which strongly indicates the potential effectiveness of SBM685 in inhibiting MDR1’s function [25].

SBM685 exhibited efficacy in controlling the GC cell proliferation when tested in vitro. The compound was nontoxic to the noncancerous cells at several folds of concentration of its biological efficacy in the GC cells. This broad window can be attributed as an advantage for a safer therapeutic dose of SBM685 [26]. The DNA methyltransferase inhibitor 5AC and the histone deacetylase (HDAC) inhibitor TSA are shown to induce MDR1 mRNA expression in several GC cells [27]. Our observation was on par with this study where 5AC + TSA induced MDR1⁺ populations largely in both MKN-45 and SNU-5 cells. Additionally, the computational observations of MDR1-SBM685 binding were further supported by this study, where SBM685 efficiently controlled MDR1⁺ populations in both GC cells tested.

5-Fluorouracil (5-FU) is still a frontline chemotherapeutic in GC treatment [28]. However, reports indicate 5FU resistance in several cancer models with MDR1 association/overexpression [28]. On the other hand, studies have demonstrated that anticancer agents that can down-regulate protein expression of MDR1 in drug-resistant gastric cancer cells could reverse resistance characteristics of gastric cancer [29, 30]. Observations of this study align with the aforementioned statement, where SBM685 exhibited antiproliferative and apoptosis-inducing efficacy in MDR1⁺ GC cells that were resistant to 5FC treatments.

Conclusion

In conclusion, through an integrative approach combining virtual screening, detailed interaction profiling, and in vitro evaluations, SBM685 was identified as a lead compound with strong and stable binding affinity to the ATP-binding domain of MDR1. The comprehensive analysis presented in this study underscores the potential of SBM685 as a promising inhibitor of MDR1, that showed efficacy in normal and 5FU resistance GC cells. These findings highlight the therapeutic potential of SBM685 and lay the groundwork for further preclinical and clinical investigations to validate its efficacy in overcoming MDR1-mediated chemoresistance.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

Conceptualization, methodology, validation, formal analysis, writing, and funding acquisition A.A.D and M.A. The authors have agreed to publish this version of the manuscript.

Funding

The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Research Project under grant number RGP2/154/46.

Data availability

The authors declare that the data supporting the findings of this study are available within the paper and its supplementary information files. Should any raw data files be needed in another format they are available from the corresponding author upon reasonable request.PDB accession ID: https://www.rcsb.org/structure/4KSBSiBioLEAD server: https://sibiolead.com/ (requires login/registration)ZINC natural product database: https://zinc.docking.org/substances/ZINC000008918500/.

Declarations

Ethics approval and consent to participate

Not applicable. This study did not involve human participants or animals.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.