Simultaneous binding mechanism of multiple substrates for multidrug resistance transporter P-glycoprotein

Potency and mechanism of p-glycoprotein chemosensitizers in rainbow trout (Oncorhynchus mykiss) hepatocytes

The membrane efflux transporter P-glycoprotein (P-gp, [ABCB1, MDR1]) exports a wide range of xenobiotic compounds, resulting in a continuous first line of defense against toxicant accumulation at basal expression levels, and contributing to the multixenobiotic resistance (MXR) phenotype at elevated expression levels. Relatively little information exists on P-gp inhibition in fish by chemosensitizers, compounds which lower toxicity thresholds for harmful P-gp substrates in complex mixtures. The effects of four known mammalian chemosensitizers (cyclosporin A [CsA], quinidine, valspodar [PSC833], and verapamil) on the P-gp-mediated transport of rhodamine 123 (R123) and cortisol in primary cultures of rainbow trout (Oncorhynchus mykiss) hepatocytes were examined. Competitive accumulation assays using 25 µM R123 or cortisol and varying concentrations of chemosensitizers (0-500 µM) were used. CsA, quinidine, and verapamil inhibited R123 export (IC50 values ± SE: 132 ± 60, 83.3 ± 27.2, and 43.2 ± 13.6 µM, respectively). CsA and valspodar inhibited cortisol export (IC50 values: 294 ± 106 and 92.2 ± 34.9 µM, respectively). In an ATP depletion assay, hepatocytes incubated with all four chemosensitizers resulted in lower free ATP concentrations, suggesting that they act via competitive inhibition. Chemosensitizers that inhibit MXR transporters are an important class of environmental pollutant, and these results show that rainbow trout transporters are inhibited by similar chemosensitizers (and mostly at similar concentrations) as seen in mammals and other fish species.

Drug resistance in ovarian cancer: from mechanism to clinical trial

Ovarian cancer is the leading cause of gynecological cancer-related death. Drug resistance is the bottleneck in ovarian cancer treatment. The increasing use of novel drugs in clinical practice poses challenges for the treatment of drug-resistant ovarian cancer. Continuing to classify drug resistance according to drug type without understanding the underlying mechanisms is unsuitable for current clinical practice. We reviewed the literature regarding various drug resistance mechanisms in ovarian cancer and found that the main resistance mechanisms are as follows: abnormalities in transmembrane transport, alterations in DNA damage repair, dysregulation of cancer-associated signaling pathways, and epigenetic modifications. DNA methylation, histone modifications and noncoding RNA activity, three key classes of epigenetic modifications, constitute pivotal mechanisms of drug resistance. One drug can have multiple resistance mechanisms. Moreover, common chemotherapies and targeted drugs may have cross (overlapping) resistance mechanisms. MicroRNAs (miRNAs) can interfere with and thus regulate the abovementioned pathways. A subclass of miRNAs, "epi-miRNAs", can modulate epigenetic regulators to impact therapeutic responses. Thus, we also reviewed the regulatory influence of miRNAs on resistance mechanisms. Moreover, we summarized recent phase I/II clinical trials of novel drugs for ovarian cancer based on the abovementioned resistance mechanisms. A multitude of new therapies are under evaluation, and the preliminary results are encouraging. This review provides new insight into the classification of drug resistance mechanisms in ovarian cancer and may facilitate in the successful treatment of resistant ovarian cancer.

Exploring the dynamics of the ABCB1 membrane transporter P-glycoprotein in the presence of ATP and active/non-active compounds through molecular dynamics simulations

P-glycoprotein (Pgp) is a member of the ATP-binding cassette family of transporters that confers multidrug resistance to cancer cells and is actively involved in the pharmacokinetics and toxicokinetics of a big variety of drugs. Extensive studies have provided insights into the binding of many compounds, but the precise mechanism of translocation across the membrane remains unknown; in this context, the major challenge has been to understand the basis for its polyspecificity. In this study, molecular dynamics (MD) simulations of human P-gp (hP-gp) in an explicit membrane-and-water environment were performed to investigate the dynamic behavior of the transporter in the presence of different compounds (active and inactive) in the binding pocket and ATP molecules within the nucleotide binding domains (NBDs). The complexes studied involve four compounds: cyclosporin A (CSA), amiodarone (AMI), pamidronate (APD), and valproic acid (VPA). While CSA and AMI are known to interact with P-gp, APD and VPA do not. The results highlighted how the presence of ATP notably contributed to increased flexibility of key residues in NBD1 of active systems, indicating potential conformational changes activating the translocation mechanism. MD simulations reveal how these domains adapt and respond to the presence of different substrates, as well as the influence of ATP binding on their flexibility. Furthermore, distinctive behavior was observed in the presence of active and inactive compounds, particularly in the arrangement of ATP between NBDs, supporting the proposed nucleotide sandwich dimer mechanism for ATP binding. This study provides comprehensive insights into P-gp behavior with various ligands and ATP, offering implications for drug development, toxicity assessment and demonstrating the validity of the results derived from the MD simulations.

Effects of the chemosensitizer verapamil on P-glycoprotein substrate efflux in rainbow trout hepatocytes

The ATP-dependent membrane transporter P-glycoprotein (P-gp) is associated with resistance to a wide variety of chemical substrates, as well as the multi-drug resistance (MDR) phenotype in mammals. Less is known regarding P-gp's function and relevance in teleosts; this study expanded the range of known substrates and the inhibitory effects of a model chemosensitizer verapamil. The P-gp-mediated uptake and efflux dynamics of 5 known mammalian substrates (berberine, cortisol, doxorubicin, rhodamine 123 [R123], and vinorelbine) were examined in isolated rainbow trout (Oncorhynchus mykiss) hepatocytes with and without co-exposure to varying doses of verapamil. Initial substrate uptake rates (pmol/106 cells/min) varied widely and were in order: berberine (482 ± 94) > R123 (364 ± 67) > doxorubicin (158 ± 41) > cortisol (20.3 ± 5.9) > vinorelbine (15.3 ± 3.5). Initial efflux rates (pmol/106 cells/min) were highest in berberine (464 ± 110) > doxorubicin (341 ± 57) > R123 (106 ± 33) > cortisol (26.6 ± 6.1) > vinorelbine (9.0 ± 2.4). Transport of vinorelbine and R123 is verapamil sensitive, but verapamil had no effect on transport of berberine, cortisol, or doxorubicin. Cortisol and doxorubicin showed evidence of high P-gp affinity, thus displacing verapamil from their shared P-gp binding site. Cortisol, doxorubicin, R123, and vinorelbine transport by rainbow trout P-gp was confirmed, while berberine could not be confirmed or excluded as a substrate. Binding sites and affinities were similar between mammalian and trout P-gp for doxorubicin, R123, and vinorelbine, while fish P-gp had a higher affinity for cortisol than mammalian P-gp. This study demonstrated that the range of substrates, as well as binding sites and affinities, of fish P-gp are well-aligned with those in mammals.

Computational and artificial intelligence-based approaches for drug metabolism and transport prediction

Drug metabolism and transport, orchestrated by drug-metabolizing enzymes (DMEs) and drug transporters (DTs), are implicated in drug-drug interactions (DDIs) and adverse drug reactions (ADRs). Reliable and precise predictions of DDIs and ADRs are critical in the early stages of drug development to reduce the rate of drug candidate failure. A variety of experimental and computational technologies have been developed to predict DDIs and ADRs. Recent artificial intelligence (AI) approaches offer new opportunities for better predicting and understanding the complex processes related to drug metabolism and transport. We summarize the role of major DMEs and DTs, and provide an overview of current progress in computational approaches for the prediction of drug metabolism, transport, and DDIs, with an emphasis on AI including machine learning (ML) and deep learning (DL) modeling.

The Important Role of Transporter Structures in Drug Disposition, Efficacy, and Toxicity

The ATP-binding cassette (ABC) and solute carrier (SLC) transporters are critical determinants of drug disposition, clinical efficacy, and toxicity as they specifically mediate the influx and efflux of various substrates and drugs. ABC transporters can modulate the pharmacokinetics of many drugs via mediating the translocation of drugs across biologic membranes. SLC transporters are important drug targets involved in the uptake of a broad range of compounds across the membrane. However, high-resolution experimental structures have been reported for a very limited number of transporters, which limits the study of their physiologic functions. In this review, we collected structural information on ABC and SLC transporters and described the application of computational methods in structure prediction. Taking P-glycoprotein (ABCB1) and serotonin transporter (SLC6A4) as examples, we assessed the pivotal role of structure in transport mechanisms, details of ligand-receptor interactions, drug selectivity, the molecular mechanisms of drug-drug interactions, and differences caused by genetic polymorphisms. The data collected contributes toward safer and more effective pharmacological treatments. SIGNIFICANCE STATEMENT: The experimental structure of ATP-binding cassette and solute carrier transporters was collected, and the application of computational methods in structure prediction was described. P-glycoprotein and serotonin transporter were used as examples to reveal the pivotal role of structure in transport mechanisms, drug selectivity, the molecular mechanisms of drug-drug interactions, and differences caused by genetic polymorphisms.

Dendrobium candidum quality detection in both food and medicine agricultural product: Policy, status, and prospective

Dendrobium candidum (DC) is an agricultural product for both food and medicine. It has a variety of beneficial effects on the human body with antioxidant, anti-inflammatory, antitumor, enhancing immune function, and other pharmacological activities. Due to less natural distribution, harsh growth conditions, slow growth, low reproduction rate, and excessive logging, wild DC has been seriously damaged and listed as an endangered herbal medicine variety in China. At present, the quality of DC was uneven in the market, so it is very necessary to detect its quality. This article summarized the methods of DC quality detection with traditional and rapid nondestructive, and it also expounded the correlation between DC quality factor and endophytes, which provides a theoretical basis for a variety of rapid detection methods in macromolecules. At last, this article put forward a variety of rapid nondestructive detection methods based on the emission spectrum. In view of the complexity of molecular structure, the quality correlation established by spectral analysis was greatly affected by varieties and environment. We discussed the possibility of DC quality detection based on the molecular dynamic calculation and simulation mechanism. Also, a multimodal fusion method was proposed to detect the quality. The literature review suggests that it is very necessary to understand the structure performance relationship, kinetic properties, and reaction characteristics of chemical substances at the molecular level by means of molecular chemical calculation and simulation, to detect a certain substance more accurately. At the same time, several modes are combined to form complementarity, eliminate ambiguity, and uncertainty and fuse the information of multiple modes to obtain more accurate judgment results.

Recent Advances on P-Glycoprotein (ABCB1) Transporter Modelling with In Silico Methods

ABC transporters play a critical role in both drug bioavailability and toxicity, and with the discovery of the P-glycoprotein (P-gp), this became even more evident, as it plays an important role in preventing intracellular accumulation of toxic compounds. Over the past 30 years, intensive studies have been conducted to find new therapeutic molecules to reverse the phenomenon of multidrug resistance (MDR) ), that research has found is often associated with overexpression of P-gp, the most extensively studied drug efflux transporter; in MDR, therapeutic drugs are prevented from reaching their targets due to active efflux from the cell. The development of P-gp inhibitors is recognized as a good way to reverse this type of MDR, which has been the subject of extensive studies over the past few decades. Despite the progress made, no effective P-gp inhibitors to reverse multidrug resistance are yet on the market, mainly because of their toxic effects. Computational studies can accelerate this process, and in silico models such as QSAR models that predict the activity of compounds associated with P-gp (or analogous transporters) are of great value in the early stages of drug development, along with molecular modelling methods, which provide a way to explain how these molecules interact with the ABC transporter. This review highlights recent advances in computational P-gp research, spanning the last five years to 2022. Particular attention is given to the use of machine-learning approaches, drug-transporter interactions, and recent discoveries of potential P-gp inhibitors that could act as modulators of multidrug resistance.

Essential oil of Ligusticum chuanxiong Hort. Regulated P-gp protein and tight junction protein to change pharmacokinetic parameters of temozolomide in blood, brain and tumor

ETHNOPHARMACOLOGICAL RELEVANCE

The existence of the blood-brain barrier/blood tumor barrier (BBB/BTB) severely restricts the effectiveness of anti-tumor drugs, thus glioma is still an incurable disease with a high fatality rate. Chuanxiong (Ligusticum chuanxiong Hort., Umbelliferae) was used as a messenger drug to increase the distribution of drugs in brain tissue, and its application in Chinese herbal formula for treating glioma was also the highest.

AIM OF THE STUDY

Our previous researches showed that essential oil (EO) of chuanxiong could promote temozolomide (TMZ) entry into glioma cells in vitro and enhance TMZ-induced anticancer efficiency in vivo, and therefore, the aim of this study was to investigate whether EO could increase the concentration accumulation of TMZ in brain or tumor of C6 glioma rats and the related mechanisms.

MATERIALS AND METHODS

The pharmacokinetics were conducted in C6 glioma rats by administering either TMZ alone or combined with EO through oral routes. TMZ concentration in blood, brain and tumor was detected using liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) and then pharmacokinetic parameters were calculated. The changed expressions of P-gp protein, tight junction occludin, claudin-5 and zonula occludens-1 (ZO-1) in brain of glioma rats were studied by Western blot to clarify the mechanism. Finally, the chemical composition of EO was analyzed by gas chromatography-massspectrometry (GC-MS).

RESULTS

The results showed that EO significantly affected the pharmacokinetic parameters such as T_max, C_max and CL (p < 0.01), but did not significantly change the AUC_(0→∞) of TMZ in blood (p > 0.05). However, EO markedly improved the AUC_(0→∞)of TMZ in brain and tumor (p < 0.01). The calculate drug targeting index was greater than 1, indicating that EO could promote the distribution of TMZ to the brain and tumor. Western blot analysis showed that EO significantly inhibited the expression of P-gp, tight junction protein claudin-5, occludin and ZO-1. And meanwhile, the expressions of P-gp, claudin-5 and occludin also markedly down-regulated in EO-TMZ co-administration treatment. GC-MS analysis of the TIC component of EO was (E)-Ligustilide (36.93%), Terpinolene (7.245%), gamma-terpinene (7.225%) etc. CONCLUSION: EO could promote the distribution of TMZ in the brain and tumor of C6 glioma rats, which may attribute to down-regulate the expression of P-gp, claudin-5 and occludin.

Structure-Function Relationships in the Human P-Glycoprotein (ABCB1): Insights from Molecular Dynamics Simulations

P-Glycoprotein (P-gp) is a transmembrane protein belonging to the ATP binding cassette superfamily of transporters, and it is a xenobiotic efflux pump that limits intracellular drug accumulation by pumping compounds out of cells. P-gp contributes to a reduction in toxicity, and has broad substrate specificity. It is involved in the failure of many cancer and antiviral chemotherapies due to the phenomenon of multidrug resistance (MDR), in which the membrane transporter removes chemotherapeutic drugs from target cells. Understanding the details of the ligand–P-gp interaction is therefore critical for the development of drugs that can overcome the MDR phenomenon, for the early identification of P-gp substrates that will help us to obtain a more effective prediction of toxicity, and for the subsequent outdesign of substrate properties if needed. In this work, a series of molecular dynamics (MD) simulations of human P-gp (hP-gp) in an explicit membrane-and-water environment were performed to investigate the effects of binding different compounds on the conformational dynamics of P-gp. The results revealed significant differences in the behaviour of P-gp in the presence of active and non-active compounds within the binding pocket, as different patterns of movement were identified that could be correlated with conformational changes leading to the activation of the translocation mechanism. The predicted ligand–P-gp interactions are in good agreement with the available experimental data, as well as the estimation of the binding-free energies of the studied complexes, demonstrating the validity of the results derived from the MD simulations.