Discovery of alkoxyl biphenyl derivatives bearing dibenzo[c,e]azepine scaffold as potential dual inhibitors of P-glycoprotein and breast cancer resistance protein

Design and evaluation of dibenzoazepine-tetrahydroisoquinoline hybrids as potential P-glycoprotein inhibitors against multidrug resistant K562/A02 cells

Multidrug resistance (MDR) caused by P-glycoprotein (P-gp) is a main barrier to the success of cancer chemotherapies. In this study, fourteen novel dibenzoazepine-tetrahydroisoquinoline hybrids were prepared as potential P-gp inhibitors to surmount MDR caused by P-gp. Amongst them, 8a displayed the most potent inhibition effect on P-gp, thus effectively reversing P-gp-mediated drug resistance with a reversal fold (RF) value of 93.17 in K562/A02 cells. Excitingly, the EC₅₀ value of 8a on MDR reversing effect was 48.74 nM, which was nearly two thousand-fold lower than its IC₅₀ value (95.94 μM) for intrinsic cytotoxicity on K562/A02 cells. Further investigation showed that 8a exerted the MDR reversal effect through impairing P-gp function rather than affecting its expression. Molecular docking and CETSA results illustrated that 8a possessed a relatively high affinity for P-gp, thus effectively improving the stability of P-gp. Furthermore, 8a exhibited a much poorer inhibitory effect on CYP3A4 activity than CYP3A4 inhibitor ketoconazole, thus might not cause unfavorable drug-drug interactions. These data together suggested that 8a may be a promising lead to design P-gp inhibitors, and warranted further investigation on overcoming P-gp-mediated MDR.

A curated binary pattern multitarget dataset of focused ATP-binding cassette transporter inhibitors

Multitarget datasets that correlate bioactivity landscapes of small-molecules toward different related or unrelated pharmacological targets are crucial for novel drug design and discovery. ATP-binding cassette (ABC) transporters are critical membrane-bound transport proteins that impact drug and metabolite distribution in human disease as well as disease diagnosis and therapy. Molecular-structural patterns are of the highest importance for the drug discovery process as demonstrated by the novel drug discovery tool ‘computer-aided pattern analysis’ (‘C@PA’). Here, we report a multitarget dataset of 1,167 ABC transporter inhibitors analyzed for 604 molecular substructures in a statistical binary pattern distribution scheme. This binary pattern multitarget dataset (ABC_BPMDS) can be utilized for various areas. These areas include the intended design of (i) polypharmacological agents, (ii) highly potent and selective ABC transporter-targeting agents, but also (iii) agents that avoid clearance by the focused ABC transporters [e.g., at the blood-brain barrier (BBB)]. The information provided will not only facilitate novel drug prediction and discovery of ABC transporter-targeting agents, but also drug design in general in terms of pharmacokinetics and pharmacodynamics.

Measurement(s)	Influx • Efflux • Tracer • Transport velocity
Technology Type(s)	Fluorometry • Radioactivity • Plate reader • Flow cytometer • Tracer distribution
Factor Type(s)	half-maximal inhibition concentration
Sample Characteristic - Organism	Homo sapiens
Sample Characteristic - Environment	cell culture
Sample Characteristic - Location	Kingdom of Norway • Germany • Australia • Latvia

Development of Simple and Accurate in Silico Ligand-Based Models for Predicting ABCG2 Inhibition

The ATP binding cassette transporter ABCG2 is a physiologically important drug transporter that has a central role in determining the ADMET (absorption, distribution, metabolism, elimination, and toxicity) profile of therapeutics, and contributes to multidrug resistance. Thus, development of predictive in silico models for the identification of ABCG2 inhibitors is of great interest in the early stage of drug discovery. In this work, by exploiting a large public dataset, a number of ligand-based classification models were developed using partial least squares-discriminant analysis (PLS-DA) with molecular interaction field- and fingerprint-based structural description methods, regarding physicochemical and fragmental properties related to ABCG2 inhibition. An in-house dataset compiled from recently experimental studies was used to rigorously validated the model performance. The key molecular properties and fragments favored to inhibitor binding were discussed in detail, which was further explored by docking simulations. A highly informative chemical property was identified as the principal determinant of ABCG2 inhibition, which was utilized to derive a simple rule that had a strong capability for differentiating inhibitors from non-inhibitors. Furthermore, the incorporation of the rule into the best PLS-DA model significantly improved the classification performance, particularly achieving a high prediction accuracy on the independent in-house set. The integrative model is simple and accurate, which could be applied to the evaluation of drug-transporter interactions in drug development. Also, the dominant molecular features derived from the models may help medicinal chemists in the molecular design of novel inhibitors to circumvent ABCG2-mediated drug resistance.

ADMET evaluation in drug discovery. 20. Prediction of breast cancer resistance protein inhibition through machine learning

Breast cancer resistance protein (BCRP/ABCG2), an ATP-binding cassette (ABC) efflux transporter, plays a critical role in multi-drug resistance (MDR) to anti-cancer drugs and drug–drug interactions. The prediction of BCRP inhibition can facilitate evaluating potential drug resistance and drug–drug interactions in early stage of drug discovery. Here we reported a structurally diverse dataset consisting of 1098 BCRP inhibitors and 1701 non-inhibitors. Analysis of various physicochemical properties illustrates that BCRP inhibitors are more hydrophobic and aromatic than non-inhibitors. We then developed a series of quantitative structure–activity relationship (QSAR) models to discriminate between BCRP inhibitors and non-inhibitors. The optimal feature subset was determined by a wrapper feature selection method named rfSA (simulated annealing algorithm coupled with random forest), and the classification models were established by using seven machine learning approaches based on the optimal feature subset, including a deep learning method, two ensemble learning methods, and four classical machine learning methods. The statistical results demonstrated that three methods, including support vector machine (SVM), deep neural networks (DNN) and extreme gradient boosting (XGBoost), outperformed the others, and the SVM classifier yielded the best predictions (MCC = 0.812 and AUC = 0.958 for the test set). Then, a perturbation-based model-agnostic method was used to interpret our models and analyze the representative features for different models. The application domain analysis demonstrated the prediction reliability of our models. Moreover, the important structural fragments related to BCRP inhibition were identified by the information gain (IG) method along with the frequency analysis. In conclusion, we believe that the classification models developed in this study can be regarded as simple and accurate tools to distinguish BCRP inhibitors from non-inhibitors in drug design and discovery pipelines.

Recent advances in the search of BCRP- and dual P-gp/BCRP-based multidrug resistance modulators

The development of multidrug resistance (MDR) is one of the major challenges to the success of chemotherapy treatment of cancer. This phenomenon is often associated with the overexpression of the ATP-binding cassette (ABC) transporters P-gp (P-glycoprotein, ABCB1), multidrug resistance-associated protein 1, ABCC1 and breast cancer resistance protein, ABCG2 (BCRP). These transporters are constitutively expressed in many tissues playing relevant protective roles by the regulation of the permeability of biological membranes, but they are also overexpressed in malignant tissues. P-gp is the first efflux transporter discovered to be involved in cancer drug resistance, and over the years, inhibitors of this pump have been disclosed to administer them in combination with chemotherapeutic agents. Three generations of inhibitors of P-gp have been examined in preclinical and clinical studies; however, these trials have largely failed to demonstrate that coadministration of pump inhibitors elicits an improvement in therapeutic efficacy of antitumor agents, although some of the latest compounds show better results. Therefore, new and innovative strategies, such as the fallback to natural products and the discover of dual activity ligands emerged as new perspectives. BCRP is the most recently ABC protein identified to be involved in multidrug resistance. It is overexpressed in several haematological and solid tumours together with P-gp, threatening the therapeutic effectiveness of different chemotherapeutic drugs. The chemistry of recently described BCRP inhibitors and dual P-gp/BCRP inhibitors, as well as their preliminary pharmacological evaluation are discussed, and the most recent advances concerning these kinds of MDR modulators are reviewed.

4b,5,6,9-Tetrahydro-7H-dibenzo[c,e]pyrrolo[1,2-a]azepin-7-one

A simple approach to synthesize 4b,5,6,9-tetrahydro-7H-dibenzo[c,e]pyrrolo[1,2-a]azepin- 7-one has been developed, based on a three-step transformation of 2-(2-bromophenyl)cyclopropane-1,1-diester. The key stage in this method is an intramolecular cross-coupling of 1-(2-bromobenzyl)-5-(2-bromophenyl)pyrrolidin-2-one under continuous flow conditions in an H-Сube-Pro using commercially available supported Pd catalysts.

Assessment of a bifendate derivative bearing a 6,7-dihydro-dibenzo[c,e]azepine scaffold as a potential anti-metastatic agent

Multidrug resistance (MDR) and metastasis are major causes of mortality in patients with cancer. We recently reported a bifendate derivative bearing a dibenzo[c,e]azepine scaffold (4i) as a P-gp and BCRP-medicated MDR reversal agent. As a continuation of the previous research, its ability to inhibit cancer metastasis was investigated in MDA-MB-231 cells in the present work. Wound-healing and chamber migration assays showed that 4i could significantly attenuate the migration of MDA-MB-231 cells. Additionally, 4i obviously suppressed the invasive activity of MDA-MB-231 cells, thus displaying potential anti-metastasis activity. Preliminary mechanism studies indicated that the anti-metastasis activity of 4i was associated with the inhibitory effect on the activity and expression of MMP-2 and MMP-9. These results, together with the previous findings, suggest that compound 4i could be a promising lead for the development of novel anti-cancer agents with anti-MDR and metastatic activities.

9-Deazapurines as Broad-Spectrum Inhibitors of the ABC Transport Proteins P-Glycoprotein, Multidrug Resistance-Associated Protein 1, and Breast Cancer Resistance Protein

P-Glycoprotein (P-gp, ABCB1), multidrug resistance-associated protein 1 (MRP1, ABCC1), and breast cancer resistance protein (BCRP, ABCG2) are the three major ABC transport proteins conferring resistance to many structurally diverse anticancer agents, leading to the phenomenon called multidrug resistance (MDR). Much effort has been put into the development of clinically useful compounds to reverse MDR. Broad-spectrum inhibitors of ABC transport proteins can be of great use in cancers that simultaneously coexpress two or three transporters. In this work, we continued our effort to generate new, potent, nontoxic, and multiply effective inhibitors of the three major ABC transporters. The best compound was active in a very low micromolar concentration range against all three transporters and restored sensitivity toward daunorubicin (P-gp and MRP1) and SN-38 (BCRP) in A2780/ADR (P-gp), H69AR (MRP1), and MDCK II BCRP (BCRP) cells. Additionally, the compound is a noncompetitive inhibitor of daunorubicin (MRP1), calcein AM (P-gp), and pheophorbide A (BCRP) transport.

Indole-fused azepines and analogues as anticancer lead molecules: Privileged findings and future directions

The search for new lead compounds of simple structure, displaying highest quality anti-tumor potency with new mechanisms of action and least adverse effects is the major intention of cancer drug discovery now a days. For the time being, indole-fused azepines emerged as a simple class of compounds prolifically designed with strong pharmacological significances in particular of cancer protecting ability. In the recent years from the efforts of our research group, indole-fused heteroazepines, a simple structural class achieved by fusion of indole with oxygen, sulphur and nitrogen containing heteroazepine rings, have known for its superior outcomes in cancer treatment. Surprisingly, the chemistry and biology of these unique families with an amazing role in cancer drug discovery has remained broadly unexplored. This short review is consequently an endeavor to highlight the preliminary ideas over this structural class and to draw the medical attention towards future development of indole-fused azepines and analogues for their promising function in cancer drug discovery.

ABCG2/BCRP: Specific and Nonspecific Modulators

Multidrug resistance (MDR) in cancer cells is the development of resistance to a variety of structurally and functionally nonrelated anticancer drugs. This phenomenon has become a major obstacle to cancer chemotherapy seriously affecting the clinical outcome. MDR is associated with increased drug efflux from cells mediated by an energy-dependent mechanism involving the ATP-binding cassette (ABC) transporters, mainly P-glycoprotein (ABCB1), the MDR-associated protein-1 (ABCC1), and the breast cancer resistance protein (ABCG2). The first two transporters have been widely studied already and reviews summarized the results. The ABCG2 protein has been a subject of intense study since its discovery as its overexpression has been detected in resistant cell lines in numerous types of human cancers. To date, a long list of modulators of ABCG2 exists and continues to increase. However, little is known about the clinical consequences of ABCG2 modulation. This makes the design of novel, potent, and nontoxic inhibitors of this efflux protein a major challenge to reverse MDR and thereby increase the success of chemotherapy. The aim of the present review is to describe and highlight specific and nonspecific modulators of ABCG2 reported to date based on the selectivity of the compounds, as many of them are effective against one or more ABC transport proteins.

Synthesis and ABCG2 inhibitory evaluation of 5-N-acetylardeemin derivatives

An efficient and versatile synthesis of 5-N-acetylardeemin (1a) and sixteen 2-, 3- and 13-substituted derivatives 1b-q was achieved through Ugi three-component reaction of 3,3a,8,8a-tetrahydropyrrolo[2,3-b]indole and cyclization/epimerization. Their inhibitory activity on the drug efflux of breast cancer resistance protein (ABCG2) was evaluated by flow cytometric analysis of accumulation of Hoechst 33342 stain in Flp-In-293/ABCG2 cells. Most of the derivatives exhibited a stronger ABCG2 inhibitory effect compared with natural product 1a. The derivative 1m with a 4-tolyl substituent at the C-13 position exhibited the most potent ABCG2 inhibition. This preliminary structure-activity relationship study indicates that an electron-rich aryl moiety as the 13-substituent is key to increasing the inhibitory activity.