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14 February 2026

Computational and Experimental Analysis of Sophora alopecuroides L. Chloroform Fraction: Active Components and Anti-Breast Cancer Resistance Mechanisms

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College of Chemistry and Chemical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China
2
Shanghai Frontiers Science Research Center for Druggability of Cardiovascular Noncoding RNA, Institute for Frontier Medical Technology, Shanghai University of Engineering Science, Shanghai 201620, China
3
School of Medicine, Xizang Minzu University, Wenhui Road East, Weicheng District, Xianyang 712082, China
4
Engineering Research Center of Tibetan Medicine Detection Technology, Ministry of Education, Xianyang 712082, China
Molecules2026, 31(4), 660;https://doi.org/10.3390/molecules31040660
This article belongs to the Special Issue Advancement in Phytochemistry and Pharmacology of Medicinal Plants
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Abstract

We discovered that the chloroform extracted from Sophora alopecuroides L. exhibited the capacity to counteract multidrug resistance in breast cancer significantly. However, the precise active ingredients and their underlying mechanisms of action remain to be elucidated, necessitating the urgent undertaking of in-depth studies. In this study, an extract of Sophora alopecuroides L. was obtained through ethanol extraction and chloroform solvent extraction. Subsequent isolation and multi-round screening using MCF-7/ADR cells yielded the highly active chloroform derivative SaL-30. The active compound group of Sophora alopecuroides L. (SACG), consisting of 13 compounds, was confirmed by HPLC-QTOF-MS/MS and compositional screening. Network pharmacological analysis and molecular docking technology demonstrated that SACG reversed breast cancer resistance through an intricate multi-component (flavonoids/alkaloids), multi-target (AKT1/TNF/CDK2), and multi-pathway (PI3K-AKT/FoxO/MAPK) synergistic mode of action, with the PI3K-AKT pathway acting as the core regulator. Cell experiments further demonstrate that SaL-30 has strong toxicity against MCF-7/ADR by cellular assay, with an IC50 value of 8.941 ± 0.327 µg/mL and a synergistic index of CI = 0.3258, exhibiting a strong synergistic anti-breast cancer effect when co-administered with Adriamycin. These findings provide a theoretical foundation for elucidating the anti-drug resistance mechanism of Sophora alopecuroides L.

1. Introduction

Breast cancer was responsible for the highest number of new cases of malignant tumors among women worldwide, with a total of 2.31 million cases reported in 2022 [1,2]. Chemotherapy constitutes the primary treatment for metastatic breast cancer. While it exhibits a high cure rate for early-stage breast cancer, the treatment also possesses drawbacks, including systemic toxicity and multidrug resistance [3]. Among the factors that contribute to treatment failure and recurrence, intrinsic and acquired resistance are of primary significance [4,5]. Multidrug resistance (MDR) is a phenomenon in which neoplastic cells exhibit cross-resistance to multiple anticancer drugs, each of which possesses a distinct structural and mechanistic characteristic [3]. Multidrug resistance reversal agents have been shown to extend the effectiveness of first-line chemo drugs. But current reversal agents have issues like high toxicity and limited effectiveness, showing the need for better, safer ones.
The Chinese medicinal herb Sophora alopecuroides L. is a perennial plant belonging to the genus Sophora of the family Leguminosae. The herb’s long history of application in Traditional Chinese Medicine (TCM) is well documented, as is its wide distribution in the arid-semiarid regions of northwestern China. These regions include Xinjiang, west-central Inner Mongolia, Ningxia, and the Hexi Corridor of Gansu [6,7]. As indicated in the “Compendium of Materia Medica” and other relevant medical records, Sophora alopecuroides L. is classified as a cold substance with a pronounced bitter taste [8]. Recent studies have demonstrated the antitumor and reversal of drug resistance properties of its alkaloids and flavonoid components [7,9]. Chang et al. [10] found that picrasidine can induce prostate cancer cell death and reverse the EMT process by activating UPR/ERS. Huang et al. [11] implied that picloram could inhibit the growth of H22 graft tumors by promoting GADD45B expression. Conversely, oxidized picrasidine exerts a protective effect in cerebral ischemia–reperfusion injury by modulating the p-Akt/GSK3β/HO-1/Nrf-2 signaling pathway, thereby attenuating apoptosis and oxidative stress [12]. Pourahmad et al. [13] found that an extract of Sophora alopecuroides L. substantially inhibited drug-resistant Escherichia coli. The extract did this by down-regulating the efflux pump gene acrA, reducing the MIC of ciprofloxacin, and increasing intracellular drug accumulation. The preceding investigation ascertained that the chloroform fraction of Sophora alopecuroides L. can potently counteract multidrug resistance in breast cancer, yet the principal active ingredient and its mechanism of action are yet to be elucidated, underscoring the urgent necessity for further research.
Network pharmacology studies the pharmacological effects of traditional Chinese medicine. It uses high-throughput screening and cost-effectiveness. By constructing a network model of “components-targets-pathways” and integrating data from multiple groups, we can efficiently screen TCM ingredients, predict efficacy targets, and elucidate mechanisms [14]. Moreover, there is molecular docking technology, which is capable of accurately simulating drug-target interactions and validating network predictions at the molecular level [15]. The adoption of the “component-target-pathway” integration strategy of network pharmacology, in conjunction with molecular docking technology, has been demonstrated to enhance the prediction accuracy. Shang et al. [16] systematically analyzed the neuroprotective effects of Sophora alopecuroides alkaloids using network pharmacology, revealing that the therapeutic effects of these substances are exerted through cholinergic receptors and calcium signaling pathways. Dong et al. [17] found that flavonoid components of Sophora alopecuroides L. (e.g., quercetin, kaempferol) are involved in the regulation of cancer and inflammation through VEGFA, JUN, and other targets. These components form a multicomponent synergistic network with the alkaloids through a network pharmacology study.
In this study, the active chloroform moieties obtained from the preliminary separation and screening were analyzed via HPLC-QTOF-MS/MS to obtain their major components as the analytical dataset. In conjunction with the ADME prediction analysis and the “component-target” network, the Sophora alopecuroides L. anti-breast cancer resistance active compound group (SACG) was identified. The network pharmacology methodology was implemented to construct the “component-target-pathway” network of SACG. This methodological approach facilitated the identification of the target function and pathway mechanism through GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis. Furthermore, molecular docking was employed to validate the binding capability of the key compounds to the target. The cytotoxic effects of the active optimal components on MCF-7/ADR cells and their ability to reverse resistance to Adriamycin (ADR) were evaluated through a series of cellular experiments. This comprehensive strategy enabled the elucidation of the mechanism of SACG’s action in the context of multidrug resistance in breast cancer. It also provided a theoretical foundation for subsequent studies.

2. Results

The extraction and separation of chloroform fractions from Sophora alopecuroides L. [18], screening of active components, and LC-MS analysis results of active components are presented in the Supplementary Material Figure S1 (Results of Extraction and Preliminary Separation of Sophora alopecuroides L.), Figure S2 (Screening results of the chloroform fraction of Sophora alopecuroides for reversing drug resistance in breast cancer cells MCF-7/ADR), Figure S3 (Active component mass spectrometry total ion flow chromatogram) and Table S1 (IC50 values of fractions with reversal drug resistance activity).

2.1. Compositional Analysis and Characterization of Active Fractions of Sophora alopecuroides L. Against Breast Cancer Multidrug Resistance

The mass spectra of the optimal chloroform fraction Sophora alopecuroides L.-30 (SaL-30) for combined ADR reversal of resistance activity are shown in Figure S3. A comprehensive HPLC-Q-TOF-MS/MS analysis revealed the presence of 56 chemical constituents, predominantly quinolizidine alkaloids and flavonoids, within the most active fraction (SaL-30) extracted from the chloroform site of Sophora alopecuroides L. Detailed compound information is available in the Supplementary Material (Table S2, Mass spectrometry compound analysis of fraction SaL-30).

2.2. Screening of Anti-Breast Cancer Resistant Active Compound Group in Sophora alopecuroides L.

The 56 compounds identified by the aforementioned liquid-quality analysis were subsequently analyzed with the core targets of Sophora alopecuroides L., anti-breast cancer resistance based on the web-based pharmacology database. The 56 compounds were initially screened through the TCMSP and SwissADME databases, with compounds exhibiting OB > 30% and DL ≥ 0.18, or compounds that satisfied the five principles of the Lipinski class of drugs, being prioritized. This initial screening resulted in the identification of 27 compounds.
The integration of network ranking and mass spectrometry analysis yielded 13 compounds among the 27 candidate components that have the potential to contribute significantly to the MCF-7/ADR response. These compounds have been classified into the Sophora alopecuroides L. The anti-breast cancer resistance active compound group (SACG) includes compounds 1 (matrine, MT), 2 (Oxymatrine, OMT), 3 (Sophoridine, SRI), 4 (Oxysophoridine, OSd), 5 (Sophocarpine, Scp), 6 (Oxysophocarpine, Osp), 7 (Cytisine, Cts), 8 (N-methylcytisine, NMC), 9 (Formononetin, FMN), 10 (Glycitein, Gly), 11 (Kaempferide, Ka), 12 (2-(3,4-dihydroxyphenyl)-5,7-dihydroxy-6,8-dimethoxychromen-4-one, DOF), and 13 (Kurarinone, Krn). The structure is depicted in Figure 1.
Figure 1. Compounds structure of SACG.

2.3. Prediction of Major Targets of SACG Anti-Breast Cancer Resistance

The Gene Card and OMIM databases for 13 compounds in SACG revealed 618 unique disease-targeting genes associated with breast cancer multidrug resistance. After removing duplicate genes, 2032 from Gene Card and 666 from OMIM, the analysis identified 2618 disease-targeting genes. SwissTargetPrediction (http://www.swisstargetprediction.ch/index.php, accessed on 20 June 2024) predicted the top 100 most relevant groups for 13 compounds.
The target genes of 13 compounds in SACG and breast cancer were checked, and 163 target genes were found (Figure 2A). The construction of the PPI network was initiated with the upload of 163 potential action targets associated with breast cancer multidrug-resistant SACG to the STRING database (https://cn.string-db.org/, accessed on 20 June 2024). This process yielded a total of 161 nodes and 4110 edges. The intricate interconnections between these targets were demonstrated in Figure 2B. Interactions had a confidence score of >0.90. The output data were then visualized and analyzed using the Cytoscape 3.10.2 (Cytoscape Consortium, La Jolla, CA, USA; https://cytoscape.org/, accessed on 20 June 2024). Proteins are represented by the nodes of the network, and the edges represent the associated protein–protein interactions (Figure 2C).
Figure 2. (A) Venn diagram of breast cancer multidrug resistance-related targets under SACG treatment.; (B) PPI network obtained by entering potential targets into the string database; (C) PPI network (CentiScaPe 2.2 plug-in) with core targets marked in yellow, Visualized core targets (Degree from largest to smallest, color from darkest to lightest).
The PPI network was analyzed using CentiScaPe 2.2 to filter the core target points with the parameters of Betweenness > 169.7391, Closeness > 0.0031, and Degree > 51.0559. The core target points have 36 nodes, 780 edges, and degree values of 72 and above. Fifteen targets have degree values over 100, including AKT1 (serine/threonine-protein kinase), TNF, and EGFR. Others have values of 202, 180, and 178. Core targets include ABCB1 (P-glycoprotein 1) and CDK2 (cyclin-dependent kinase 2), all with a value of 90.

2.4. GO and KEGG Analysis of the SACG Anti-Breast Cancer Resistance Pathway

GO analysis of SACG genes for breast cancer multidrug-resistant genes identified 623 biological processes, 110 cellular components, and 180 molecular functions, ranked by corrected p-values. With respect to molecular function, protein binding, ATP binding, metal ion binding, and enzyme binding were identified as the predominant activities. The cellular composition analysis indicated that SACG primarily exerted its effects at the levels of the plasma membrane, cytoplasm, and nucleoplasm. It has been posited that SACG exerts its primary effects on the plasma membrane, cytoplasm, nucleoplasm, and other sites. The mechanism of action of this agent involves binding to proteins, ATP, metal ions, enzymes, and other substances. This binding facilitates the reversal of the resistance of breast cancer cells to adriamycin through the regulation of apoptosis, transcription, protein phosphorylation, gene expression, and other processes (Figure 3A).
Figure 3. (A) GO (BP, CC, MF) enrichment analysis; (B) KEGG enrichment analysis; (C) KEGG secondary classification; (D) Component-target-pathway diagram of SACG for breast cancer multidrug resistance, purple rectangles represent therapeutic targets.
KEGG pathway analysis of the target genes revealed 150 pathways, with the top 30 identified by p-value correction. These results suggest that SACG may play a role in multidrug-resistant breast cancer treatment (Figure 3B) and imply a complex interaction between these pathways.
The KEGG pathways were classified as demonstrated in Figure 3C. KEGG pathways mainly act on cell cycle and focal adhesion, and play a role in breast cancer, HPV infection, chemical carcinogenesis (e.g., reactive oxygen species), prostate cancer, microRNAs in cancer, etc., by regulating the PI3K-AKT and Ras, Rap1, MAPK, and FoxO signaling pathways. Many cancers and diseases are affected.

2.5. “Component-Target-Pathway” Network Analysis Indicates That SACG Acts Through Multiple Pathways Corresponding to Multiple Targets

A “component-target-pathway” network was constructed using 13 important compounds and their targets for treating multidrug resistance in breast cancer, along with the signaling pathways of the environmental information process. This network has 183 nodes and 538 edges (Figure 3D). Each active ingredient corresponds to many targets, and each Sophora alopecuroides L. breast cancer multidrug resistance target is connected to multiple pathways. These connections suggest that Sophora alopecuroides L. can treat multidrug resistance by acting on multiple components, targets, and pathways.
The degree values of the components in the “Component-Target-Pathway” network reveal that DOF, Ka, and Krn have the highest values of 62, 58, and 53. They may be the key compounds of Sophora alopecuroides L. In the ongoing battle against multidrug resistance in breast cancer, a comprehensive analysis has identified the top 15 targets as being EGFR, CHRNA3, IGF1R, FLT3, ESR2, ACHE, ROCK2, AKT1, HSP90AA1, PARP1, CHRM1, DPP9, RAF1, KIT, and CDK2. Notably, EGFR, CDK2, and CHRNA3 emerged as the most prevalent targets, with EGFR being targeted in 10 cases and CDK2 in 6. The five pathways (PI3K-Akt, Rap1, Ras, MAPK, and FoxO) had a degree of 33, 18, 17, 17, and 15, respectively, indicating that SACG acted through multiple pathways.

2.6. Molecular Docking Results

Network pharmacology and molecular docking validated the top five active ingredients (2-(3,4-dihydroxyphenyl)-5,7-dihydroxy-6,8-dimethoxychromen-4-one, kaempferide, formononetin, glycitein, and kurarinone), as well as eight active ingredients with the highest mass spectral abundance (oxysophoridine, cytisine, oxysophocarpine, sophoridine, sophocarpine, N-methylcytisine, matrine, and ammothamnine), with Top 5 SACG targets (AKT1, TNF, EGFR, ESR1, and HSP90AA1) and a total of 30 targets involved with each signaling pathway (Figure 4). The targets (e.g., AKT1, TNF, CDK2, and SIRT1) and the compounds (e.g., Krn and Gly) are demonstrated in 2D and 3D (Figure 5).
Figure 4. Molecular docking energy between SACG compounds and core target molecules.
Figure 5. 2D, 3D Visualization Diagrams of the combination of SACG key targets and focused compounds.
SACG’s molecular docking scores were more negative than −5.5 kcal/mol, and many compounds reached −9, indicating good binding affinity for breast cancer multidrug resistance-related targets. Among the compounds, Krn had the strongest binding ability to multiple targets, such as TNF −10.3 kcal/mol, AKT1 −10 kcal/mol, CDK2 −9.9 kcal/mol, DRD2 −9.9 kcal/mol, PLA2G2A −9.9 kcal/mol, and so on, through multiple hydrogen bonding connections and other binding modes.

2.7. Enhancement of ADR Toxicity on Drug-Resistant MCF-7/ADR Cells by Active Fractions of Sophora alopecuroides L.

The present study investigates the synergistic antitumor effect of Sophora alopecuroides L. active fraction SaL-30 with ADR. The effect of SaL-30 in combination with ADR was demonstrated in Figure 6A, Sophora alopecuroides L. The total alkaloid active fraction, SaL-30, in combination with Adriamycin (ADR), exhibited prominent concentration-dependent antitumor activity. The results demonstrated that SaL-30 effectively inhibited the proliferative activity of breast cancer-resistant cells (MCF-7/ADR), and the inhibitory effect was enhanced in a gradient (p < 0.05) with the increase in administered concentration (0–300 μg/mL). As demonstrated in Table 1, the IC50 of SaL-30 was considerably lower than that of the classical resistance reversal agent verapamil (VRP), indicating its enhanced resistance reversal efficacy.
Figure 6. The reversal effect of SaL-30 combined with ADR on MCF-7/ADR cells. (A) MCF-7/ADR cell activity diagram after 48 h of combined administration of SaL-30 and ADR; (B) Activity diagram of MCF-7/ADR cells after 48 h of combined administration of ADR and the single compound contained in SaL-30. Statistical significance is indicated as follows: ** p < 0.01, *** p < 0.001, **** p < 0.0001.
Table 1. The IC50 values of different concentrations of SaL-30 combined with ADR administration on MCF-7/ADR cells.
The phenomenon of resistance reversal, as observed in the context of single fractions, warrants further examination. As demonstrated in Figure 6B and Table 2, the individual alkaloidal components extracted from SaL-30 exhibited notable resistance reversal activity at elevated concentrations, reaching levels 2–3 orders of magnitude higher than the total extract. It is noteworthy that Sophocarpine demonstrated remarkable anti-resistance properties, with an IC50 value of 7.92 μM when used in combination with ADR. This result was sensibly more effective than the IC50 values observed for the other alkaloidal constituents (IC50 > 20 μM). However, the high dosage (300 μg/mL) required for optimal efficacy suggests that the potential side effects should be carefully evaluated for clinical use.
Table 2. IC50 value of the single compound in SaL-30 combined with ADR administration on MCF-7/ADR cells.
Collaboration index CI = (7.97 μM)/(78.07 μM) + (2 μg/mL)/(8.94 μg/mL) = 0.1021 + 0.2237 = 0.3258. CI measures synergy: 0.8–0.9 is low, 0.6–0.8 is medium, 0.4–0.6 is high, and 0.2–0.4 is strong. SaL-30 is strongly synergistic with ADR.

2.8. Fluorescent Staining Confirms That Active Fractions of Sophora alopecuroides L. Enhance the Apoptotic Effect of ADR on Drug-Resistant MCF-7/ADR Cells

In this study, a blank control group (no addition) and an experimental group (both containing 20 μM ADR) were established. The experimental group was supplemented with 0, 0.5, 1, and 2 μg/mL of Sophora alopecuroides L. active fraction (SaL-30). The changes in the cellular status were observed by ADR autofluorescence and Hoechst-33342 staining, respectively.
Sophora alopecuroides L. active fraction SaL-30, when used with ADR, was demonstrated to affect cell accumulation (Figure 7). Hoechst-33342 staining indicated no considerable change in cell morphology when 20 μM ADR was used alone. However, a dose-dependent change in intracellular ADR autofluorescence was observed when 20 μM ADR was used with SaL-30. The intensity of intracellular ADR autofluorescence was significantly enhanced with an increase in SaL-30 concentration (0.5–2 μg/mL). Hoechst-33342 staining implied typical nuclei crumpling and a marked diminution in cell density when the concentration of SaL-30 was ≥ 0.5 μg/mL. This phenomenon was attributed to the characteristics of ADR and the change in cell state.
Figure 7. Fluorescence staining plots of different concentrations of Sophora alopecuroides L. SaL-30 in combination with ADR.
The proportions of PI-positive (red fluorescent) cells increased substantially (p < 0.01) with the increase in SaL-30 concentration gradient (0–2 μg/mL), suggesting that the number of drug-induced late apoptotic/necrotic cells increased in a dose-dependent manner (Figure 7). In terms of cell morphology, nuclei in the control group were intact and rounded; those of the drug-administered group implied typical apoptotic characteristics. In addition, low-concentration (0.5–1 μg/mL) cells indicated prominent aggregation and flocculent clusters, and high-concentration (2 μg/mL) cells exhibited a considerable reduction in adhesion rate. The highest concentration group lost cells due to loss of membrane integrity in the late apoptotic stage, down-regulated cell–matrix adhesion molecules, and removal of apoptotic vesicles and suspended cells during the washing process.
The synergistic pro-apoptotic effect of SaL-30 combined with ADR was verified by Hoechst-33342 with the AM/PI double staining method. Hoechst-33342 staining revealed characteristic apoptotic morphological alterations in the nuclei of cells within the combination group, including nuclear condensation and chromatin condensation. In contrast, only minimal nuclear morphology changes were observed in the combination group alone. The AM/PI double staining results further confirmed that the proportion of PI-positive cells in the co-administration group increased approximately 2.3-fold compared with that in the single-agent group (p < 0.01), suggesting a notable escalation in the degree of impaired cell membrane integrity. The following mechanisms may be responsible for this synergistic effect: SaL-30 enhanced the DNA damage effect of ADR, synergistically activated the caspase apoptosis pathway, and inhibited SaL-30 enhanced the DNA damage effect of ADR, activated the caspase apoptosis pathway, and inhibited Bcl-2 expression. The research findings fully demonstrated the pronounced synergistic effect of SaL-30 in combination with ADR in inducing apoptosis in tumor cells.

3. Discussion

Multidrug resistance (MDR) is the primary cause of chemotherapy failure in breast cancer. Its complex mechanism involves the overexpression of drug efflux pumps, the escape of apoptotic cells, and the abnormal activation of multiple signaling pathways. The search for highly efficient, low-toxic, natural MDR reversal agents is a current focus and challenge in anti-tumor research. This study systematically revealed the powerful potential and mechanism of action of the chloroform fraction of Sophora alopecuroides L. (SaL-30) and its active compound group (SACG) in reversing multidrug resistance (MDR) in breast cancer for the first time using an integrated approach of in vitro pharmacodynamic experiments and computational pharmacology methods.
The present study confirmed that SaL-30, enriched with multiple alkaloids and flavonoids, exhibited pronounced cytotoxicity (IC50 = 8.94 ± 0.33 μg/mL) against MCF-7/ADR-resistant cell lines. SaL-30 was also able to induce apoptosis in a concentration-dependent manner. Furthermore, SaL-30 demonstrated excellent synergistic effects when combined with the first-line clinical drug adriamycin (ADR) (CI = 0.3258). A low dose of SaL-30 (2 µg/mL) markedly reduced the ADR IC50 and resistance index (RI) from 68.01 to 6.94 (p < 0.001) and increased the reversal multiplicity by up to 9.80-fold. The pro-apoptotic effect of SaL-30 was comparable to that of the classical reversal agent verapamil (VRP, 10 µM) at a concentration of 0.5 µg/mL. These robust data suggest that SaL-30 can directly kill drug-resistant cells and is a highly efficient chemosensitizer. Its reversal efficacy far exceeds that of traditional chemoreversal agents, making it valuable for developing and applying SaL-30.
In this study, we confirmed that the chloroform site of Sophora alopecuroides L. (SaL-30) contained more than 90% of alkaloids, such as sophocarpine and oxidized sophocarpine. These alkaloids significantly reversed multidrug resistance by concentration-dependent induction of apoptosis in MCF-7/ADR cells. The dual features of early apoptosis (nuclear marginalization) and late apoptosis (nuclear fragmentation) suggest a potential synergistic interaction with the death receptor pathway through the activation of the mitochondrial apoptotic pathway. The CI value was as low as 0.3258 after combining with Adriamycin, suggesting that it may restore the intracellular accumulation capacity of ADR through inhibition of the P-glycoprotein (P-gp)-mediated ADR exocytosis or down-regulation of the MDR1 gene expression. This finding is consistent with the results reported by Pourahmad et al. [13], who observed the reversal of E. coli drug resistance by total alkaloids from Sophora alopecuroides L. This observation suggests the potential for cross-species universality of alkaloidal compounds in the reversal of drug resistance.
Hoechst staining revealed that the pro-apoptotic effect of 0.5 μg/mL SaL-30 was equivalent to that of 10 μM verapamil (VRP, a classical P-gp inhibitor), and its reversal multiplicity (9.80-fold) was substantially higher than that of most single-target inhibitors. The observed advantage may be attributable to the multicomponent properties of the substances in question. This finding aligns with investigations into the drug resistance properties of alkaloid-flavonoid dimers derived from Sophora alopecuroides L. through extraction and modification [19,20,21].
To further elucidate the molecular mechanism of Sophora alopecuroides L., we formed the Sophora alopecuroides L. Active compound group (SACG), consisting of five flavonoids and eight alkaloids. Network pharmacological analysis revealed that SACG acts through a synergistic “multi-component-multi-target-multi-pathway” mode. The study identified 36 core targets, including AKT1, TNF, and EGFR. The targets are involved in key biological processes, such as the negative regulation of apoptosis. KEGG pathway analysis implied that the PI3K-AKT signaling pathway is the core hub of SACG’s action. This pathway regulates cell survival, proliferation, metabolism, and drug resistance and is a key signaling axis. Aberrant activation of this pathway is closely associated with multidrug resistance (MDR) in breast cancer [22,23,24]. Our predictions suggest that SACG may deregulate the inhibition of apoptosis and attenuate drug resistance by inhibiting the PI3K-AKT pathway. This is consistent with recent literature on other natural products (e.g., chelidonine and polydatin) that have reversed drug resistance in MCF-7/ADR cells by inhibiting the PI3K-AKT pathway [22,25,26]. Additionally, the network indicated that SACG is cross-regulated with Ras, MAPK, and FoxO pathways, suggesting it may modulate the multidrug resistance (MDR) phenotype through a synergistic network of multiple pathways.
The molecular docking results indicated that several components of SACG (e.g., flavonoids such as Kurarinone and Formononetin) exhibited a high degree of affinity for core targets (e.g., AKT1 and CDK2). Recent studies employing a combination of computational modeling and experimental methods have demonstrated the remarkable potential of flavonoids in the suppression of CDK2 and MAPK3 [27,28,29]. The emergence of resistance to CDK4/6 inhibitors represents a novel challenge in the treatment of hormone receptor-positive breast cancer [30]. As indicated by the findings of our study, SACG has the potential to impede the progression of the cell cycle by simultaneously targeting pivotal kinases such as PI3K/AKT signaling and CDK2 [30,31]. These kinases have the capacity to halt the cell cycle and induce cell death, a process that could facilitate the overcoming of more sophisticated mechanisms of drug resistance.
In summary, the present study validates that Sophora alopecuroides L. chloroform site (SaL-30) and its active compound group (SACG) are promising agents for reversing multidrug resistance in breast cancer from the perspectives of “mechanism prediction” and “experimental validation.” The mechanism by which SACG exerts its effects is likely attributable to a combination of chemical compounds, including alkaloids and flavonoids. These chemicals function in concert to impede a specific pathway in the body from transmitting signals, while concurrently regulating other pathways associated with cell growth and death. This combination of chemicals enhances the drug’s efficacy in combating drug resistance.
The study is not without its limitations. However, the study did not elucidate the specific contribution of each alkaloid component. Further exploration into chromatographic separation techniques is necessary to validate the single-component effect. Moreover, the paucity of experimental data from studies conducted on living subjects precludes the ability to ascertain a clinical difference. The utilization of a breast cancer xenograft model facilitates the observation of the drug’s movement within the body [32]. Utilizing proteomics technology facilitates the elucidation of the mechanism by which it modulates the PI3K-AKT/FoxO/MAPK pathway and counteracts drug resistance. The outcomes of network pharmacology must be validated through comprehensive molecular biology experiments. In subsequent studies, the research team will concentrate on the analysis of the individual components of SACG and their subsequent testing in animal models to ascertain their functionality. This will enable the development of novel medications capable of reversing multidrug resistance in breast cancer.

4. Materials and Methods

4.1. Consumables and Instruments

The herbal materials were procured from Fu Qin Pharmacy in Xinjiang and identified as Sophora alopecuroides L. by Professor Yuan Chunping of Shanghai University of Engineering Science. The MCF-7/ADR cell line and culture medium were obtained from Kanglang Bio (Shanghai, China). Methanol, ethanol, chloroform, acetonitrile, and the CCK-8 kit were purchased from McLean Reagent (Shanghai Macklin Biochemical Co., Ltd., Shanghai, China). Adriamycin hydrochloride, verapamil hydrochloride, DAPI, AO/PI, and the Hoechst 33342 staining solution and Calcein-AM/PI were purchased from Titan Bio (Shanghai Titan Scientific Co., Ltd., Shanghai, China).
High-resolution mass spectrometry was obtained from an AB Sciex TripleTOF 5600+ (AB Sciex LLC, Framingham, MA, USA). High-performance liquid chromatography (HPLC) was performed using an Agilent 1260 from Agilent Technologies (China) Co., Ltd. (Shenzhen, China). Ultrapure water was obtained using a UPT-II-20T ultrapure water meter from Sichuan Uppu Ultrapure Technology Co. (Chengdu, China).

4.2. Identification of the Active Fractions of Sophora alopecuroides L. Against Multidrug Resistance in Breast Cancer

The drug-resistant fractions were analyzed by mass spectrometry. A Triple TOF 5600+ (AB SCIEX) was used to analyze the fractions. Analytical parameters: UPLC: LC30 system (Shimadzu, Japan); column: Supersil ODS2 (2.1 mm × 100 mm, 1.8 μm); temperature: 30 °C; injection volume: 3 μL; flow rate: 0.3 mL/min; Mobile phase A: Water; Mobile phase B: Acetonitrile; Gradient elution; Positive and negative ion modes; ESI source: CUR: 30.0 psi; GS1 spray gas: 50.0 psi; GS2 gas: 50.0 psi; ISVF voltage: 55,000 V; Ion source temperature: 550.0 °C; DP level: +80 eV, CE 10 eV, acquisition range: 100–1000, 50–1000; CE: +40 ± 20 eV. The mass spectrometry peak data were analyzed to identify the chemical constituents in the optimal fraction for reversal. The data were then organized as a source for compounds in the BioConfidence B.09.00 (Agilent Technologies, Santa Clara, CA, USA; https://www.agilent.com/en/products/software/masshunter-bioconfirm, accessed on 20 June 2024) analysis [33,34].

4.3. Confirmation of an Anti-Breast Cancer Resistant Active Compound Group in Sophora alopecuroides L.

The TCMSP (https://www.tcmsp-e.com/tcmsp.php, accessed on 20 June 2024) and Herb (http://herb.ac.cn/v2, accessed on 20 June 2024) databases were screened for potential active ingredients with OB ≥ 30% and DL ≥ 0.18. Compounds that did not meet the screening criteria were evaluated for ADME properties using SwissADME (https://www.swissadme.ch/, accessed on 20 June 2024). Those meetings with ≥ 2 drug-like YES criteria were selected. Target information was then extracted, and the results were further analyzed using OMIM (https://www.omim.org/, accessed on 20 June 2024) and GeneCards (https://www.genecards.org/, accessed on 20 June 2024). Finally, Cytoscape (http://www.cytoscape.org/, accessed on 20 June 2024) and its component-target-disease network were used to identify Sophora alopecuroides L. active compound group (SACG) resistant to breast cancer [34].

4.4. Network Pharmacology Analysis of SACG Against Breast Cancer Multidrug Resistance

4.4.1. Prediction of Potential Targets for SACG Combination Therapy for Multidrug Resistance in Breast Cancer

Target information from TCMSP and Herb was obtained for the set of acquired compounds. The targets were combined, deduplicated, and corrected on UniProt (https://www.uniprot.org/, accessed on 21 June 2024) and converted to official human gene symbols. Using “breast cancer multidrug resistance” as the keyword, we excluded duplicates and false-positive genes to obtain multidrug resistance-related breast cancer targets from OMIM and GeneCards. Cross-targeted genes (SACG-breast cancer multidrug resistance target) were collected as potential targets with the online tool Venny (https://bioinfogp.cnb.csic.es/tools/venny/, accessed on 21 June 2024).

4.4.2. SACG-Breast Cancer Resistance Target PPI Network

The data were uploaded to STRING (https://cn.string-db.org/, accessed on 20 June 2024), and the settings were adjusted to focus on human interactions to create a network of protein interactions (PPI). The interactions had a highest confidence score > 0.90, and the data were analyzed using Cytoscape 3.10.2 (Cytoscape Consortium, La Jolla, CA, USA; https://cytoscape.org/, accessed on 20 June 2024). Proteins are represented by the network’s nodes, and the edges represent the protein–protein interactions. The most connected nodes in the network were examined using CentiScaPe 2.2. The most critical overlapping genes were considered core/hub genes.

4.4.3. GO&KEGG Enrichment Analysis of SACG-Breast Cancer Drug-Resistant Targets

DAVID Bioinformatics analysis platform (https://davidbioinformatics.nih.gov/, accessed on 20 June 2024) was utilized to conduct Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Functional annotation clustering analysis was performed using the DAVID tool (https://davidbioinformatics.nih.gov/gene2gene_new.jsp, accessed on 20 June 2024). Subsequently, the results were visualized using the bioinformatics platform (https://www.bioinformatics.com.cn/, accessed on 20 June 2024). p values (p < 0.05) were used to screen acquired data for subsequent manipulation. DAVID integrates tools to annotate bioprocesses and pathway analysis. All genes were used as backgrounds, and the data was timely. A p < 0.05 threshold was used to identify key pathways [35].

4.4.4. Construction of a “Component-Target-Disease” Network

A “component-target-disease” network was generated using Cytoscape 3.10.2 to illustrate relationships between compounds, genes, pathways, and diseases. The Analyzer plugin was used to analyze the network [20].

4.5. Molecular Docking Experiments

The 2D structures of the potentially active compounds in Sophora alopecuroides L. SACG were downloaded from PubChem (https://pubchem.ncbi.nlm.nih.gov/, accessed on 26 June 2024), and the target proteins were obtained from PDB (https://pubchem.ncbi.nlm.nih.gov/, accessed on 26 June 2024). In AutoDock4, the protein files were set up as active compounds: water removal, hydrogen addition, and protein designation as receptors. Water and small-molecule ligands were removed from the protein structure using PyMOL2 (Schrödinger, LLC, New York, NY, USA). The data were loaded into AutoDockTools (Scripps Research Institute, La Jolla, CA, USA) for pretreatment and dehydration reaction. Molecular docking was conducted using the AutoDock Vina (Oleg Trott & Thomas E. Ferrin, University of California, San Diego, CA, USA) software [21].

4.6. Pharmacodynamic Validation of Optimal Active Fractions of Sophora alopecuroides L. Against Breast Cancer Resistance

Logarithmic-phase cells were prepared for single-cell suspension, counted, and inoculated (2 × 105 cells/well) into a 96-well plate. The plates were homogenized and pre-cultured at 37 °C in a 5% CO2 incubator for 24 h.
Drug formulation: The drug concentration that inhibited MCF-7/ADR cells by ≤10% after the administration of fraction 30 alone was determined. Verapamil hydrochloride (VRP) was co-administered with ADR at the same concentration. The ADR concentration was determined by a gradient of 0, 0.5, 1, 5, 10, 20, 40, 80 μM, and 160 μM. A blank group, a control group, and an experimental group were set up. Each group had three replicate wells to control experimental error and improve data reliability.
Add 10% CCK-8 solution after 48 h of drug treatment and incubate in dark conditions for 45 min. The OD450 value of each well was measured, and the cell survival rate was calculated. IC50 values for ADR with and without SaL-30 and VRP were derived with GraphPad Prism 9.0 (San Diego, CA, USA; https://www.graphpad.com, accessed on 20 June 2024) [36].
A single compound control group was also established to assess the combined reversal of MCF-7/ADR cells. This was done by testing the concentration of single compounds, such as picloram, oxidized picloram, chrysoidine, locustine, and oxidized locustine, administered in combination with ADR.
The synergy index was also calculated from the IC50 values of SaL-30 alone and in combination with ADR administration. The Combination Index (CI) quantitatively assesses the effect of a drug combo. It is derived from comparing single-drug cell growth inhibition rates to those of the combo. The calculation of the Combination Index (CI) is derived from the following equation:
CI = DA/IC50,A + DB/IC50,B.
In Equation (1), “DA/DB” is defined as the concentration of the combination drug, and “IC50,X” is the concentration of the single drug at which 50% inhibition is achieved.
The cells were stained with Hoechst 33342 (0.5–10 μg/mL) and Calcein-AM (2 μM) with PI (5 μM), incubated at 37 °C for 15–30 min away from light. The observation of apoptosis was conducted through the utilization of fluorescence microscopy [37].

4.7. Data Analysis Methods

The statistical analysis and graphing were conducted using GraphPad Prism 9.0, while Adobe Illustrator (version 29.8.1, Adobe Inc., San Jose, CA, USA) was employed for image layout. The data are expressed as the mean ± standard error of the mean (mean ± SEM). The validity of the findings was ensured by setting a statistically significant threshold at p < 0.05, and comparisons between groups were conducted using one-way ANOVA.

5. Conclusions

The chloroform site of Sophora alopecuroides L. has been demonstrated to reverse breast cancer drug resistance through a combination of actions on multiple targets. The low dose and high activity of the substance in question offer a novel strategy for its use with traditional chemotherapeutic drugs, which is expected to be an ideal synergist.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/molecules31040660/s1, Figure S1: Results of Extraction and Preliminary Separation of Sophora alopecuroides L. Figure S2: Screening results of the chloroform fraction of Sophora alopecuroides for reversing drug resistance in breast cancer cells MCF-7/ADR; Figure S3: Active component mass spectrometry total ion flow chromatogram; Figure S4: Screening of compounds in active fractions by network pharmacology; Figure S5: Cytotoxicity of SaL-30 on MCF-7/ADR cells; Table S1: IC50 values of fractions with reversal drug resistance activity; Table S2: Mass spectrometry compound analysis of fraction SaL-30; Table S3: A comparison table of the main components in active ingredient mass spectrometry; Table S4: List of SACG; Table S5: Network pharmacology databases; Table S6: Software for molecular docking; Table S7: Molecular docking target PDB ID and grid parameters.

Author Contributions

Conceptualization, R.X. and X.Y.; methodology, X.Y.; software, C.X., Y.L. and Q.Z.; validation, R.X., F.S., D.S. and H.C.; formal analysis, R.X.; investigation, H.C.; resources, X.Y.; data curation, R.X.; writing—original draft preparation, R.X.; writing—review and editing, X.Y. and R.X.; visualization, R.X.; supervision, Q.Z.; project administration, X.Y.; funding acquisition, X.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the National Natural Science Foundation of China (Grant No. 81973453) and the Science & Technology Commission of Shanghai Municipality (Grant No. 20DZ2255900).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Materials. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
SACGThe active compound group of Sophora alopecuroides L.
MDRMultidrug resistance
TCMTraditional Chinese Medicine
SaL-30Chloroform fraction 30 of Sophora alopecuroides
VRPVerapamil
ADRAdriamycin
MTMatrine
OMTOxymatrine
SRISophoridine
OSdOxysophoridine
ScpSophocarpine
OspOxysophocarpine
CtsCytisine
NMCN-methylcytisine
FMNFormononetin
GlyGlycitein
KaKaempferide
DOF2-(3,4-dihydroxyphenyl)-5,7-dihydroxy-6,8-dimethoxychromen-4-one
KrnKurarinone
GOGene Ontology
BPBiological Process
CCCell Components
MFMolecular Function
KEGGKyoto Encyclopedia of Genes and Genomes

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