Subtle Structural Differences Trigger Inhibitory Activity of Propafenone Analogues at the Two Polyspecific ABC Transporters: P-Glycoprotein (P-gp) and Breast Cancer Resistance Protein (BCRP)

Ligand- and Structure-based Approaches for Transmembrane Transporter Modeling

The study of transporter proteins is key to understanding the mechanism behind multidrug resistance and drug-drug interactions causing severe side effects. While ATP-binding transporters are well-studied, solute carriers illustrate an understudied family with a high number of orphan proteins. To study these transporters, in silico methods can be used to shed light on the basic molecular machinery by studying protein-ligand interactions. Nowadays, computational methods are an integral part of the drug discovery and development process. In this short review, computational approaches, such as machine learning, are discussed, which try to tackle interactions between transport proteins and certain compounds to locate target proteins. Furthermore, a few cases of selected members of the ATP binding transporter and solute carrier family are covered, which are of high interest in clinical drug interaction studies, especially for regulatory agencies. The strengths and limitations of ligand-based and structure-based methods are discussed to highlight their applicability for different studies. Furthermore, the combination of multiple approaches can improve the information obtained to find crucial amino acids that explain important interactions of protein-ligand complexes in more detail. This allows the design of drug candidates with increased activity towards a target protein, which further helps to support future synthetic efforts.

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.

Chemical molecular-based approach to overcome multidrug resistance in cancer by targeting P-glycoprotein (P-gp)

Multidrug resistance (MDR) remains one of the major impediments for efficacious cancer chemotherapy. Increased efflux of multiple chemotherapeutic drugs by transmembrane ATP-binding cassette (ABC) transporter superfamily is considered one of the primary causes for cancer MDR, in which the role of P-glycoprotein (P-gp/ABCB1) has been most well-established. The clinical co-administration of P-gp drug efflux inhibitors, in combination with anticancer drugs which are P-gp transport substrates, was considered to be a treatment modality to surmount MDR in anticancer therapy by blocking P-gp-mediated multidrug efflux. Extensive attempts have been carried out to screen for sets of nontoxic, selective, and efficacious P-gp efflux inhibitors. In this review, we highlight the recent achievements in drug design, characterization, structure-activity relationship (SAR) studies, and mechanisms of action of the newly synthetic, potent small molecules P-gp inhibitors in the past 5 years. The development of P-gp inhibitors will increase our knowledge of the mechanisms and functions of P-gp-mediated drug efflux which will benefit drug discovery and clinical cancer therapeutics where P-gp transporter overexpression has been implicated in MDR.

P. Cardoso D, U. Ferreira MJ. Overcoming Multidrug Resistance: Flavonoid and Terpenoid Nitrogen-Containing Derivatives as ABC Transporter Modulators

Multidrug resistance (MDR) in cancer is one of the main limitations for chemotherapy success. Numerous mechanisms are behind the MDR phenomenon wherein the overexpression of the ATP-binding cassette (ABC) transporter proteins P-glycoprotein (P-gp), breast cancer resistance protein (BCRP) and multidrug resistance protein 1 (MRP1) is highlighted as a prime factor. Natural product-derived compounds are being addressed as promising ABC transporter modulators to tackle MDR. Flavonoids and terpenoids have been extensively explored in this field as mono or dual modulators of these efflux pumps. Nitrogen-bearing moieties on these scaffolds were proved to influence the modulation of ABC transporters efflux function. This review highlights the potential of semisynthetic nitrogen-containing flavonoid and terpenoid derivatives as candidates for the design of effective MDR reversers. A brief introduction concerning the major role of efflux pumps in multidrug resistance, the potential of natural product-derived compounds in MDR reversal, namely natural flavonoid and terpenoids, and the effect of the introduction of nitrogen-containing groups are provided. The main modifications that have been performed during last few years to generate flavonoid and terpenoid derivatives, bearing nitrogen moieties, such as aliphatic, aromatic and heterocycle amine, amide, and related functional groups, as well as their P-gp, MRP1 and BCRP inhibitory activities are reviewed and discussed.

Benzophenone Sulfonamide Derivatives as Interacting Partners and Inhibitors of Human P-glycoprotein

BACKGROUND

Human P-glycoprotein (P-gp) is a transmembrane protein that belongs to the ATPBinding Cassette (ABC) transporters family. Physiologically, it exports toxins out of the cell, however, its overexpression leads to the phenomena of Multidrug-Resistance (MDR) by exporting a diverse range of compounds, which are structurally and chemically different from each other, thus creating a hurdle in the treatment of various diseases including cancer. The current study was designed to screen benzophenone sulfonamide derivatives as a class of inhibitors and potential anticancer agents for P-gp.

METHODS

A total number of 15 compounds were evaluated. These compounds were screened in daunorubicin efflux inhibition assays using CCRF-CEM Vcr1000 cell line that overexpressed human P-gp. Cytotoxicity assay was also performed for active compounds 11, 14, and 13. These scaffolds were then docked in the homology model of human P-gp using mouse P-gp as a template (PDB ID: 4MIM) and the recently published Cryo Electron Microscopy (CEM) structure of human mouse chimeric P-gp to find their interactions with specified residues in the binding pocket. Analysis was performed using Labview VI and Graph pad prism version 5.0.

RESULTS

Results revealed the potency of all these compounds in low nanomolar range whereas, compound 14 was found to be most active with IC50 value of 18.35nM±4.90 followed by 11 and 13 having IC50 values of 30.66nM±5.49 and 46.12nM±3.06, respectively. Moreover, IC50 values calculated for 14, 11 and 13 in cytotoxicity assay were found to be 22.97μM±0.026, 583.1μM±0.027 and 117.8μM±0.062, respectively. Docking results showed the interaction of these scaffolds in transmembrane helices (TM) where Tyr307, Tyr310, Tyr953, Met986 and Gln946 were found to be the major interaction partners, thus they might play a significant role in the transport of these scaffolds.

CONCLUSION

Benzophenone sulfonamide derivatives showed IC50 values in low nanomolar range comparable to the standard inhibitor Verapamil, therefore they can be good inhibitors of P-gp and can serve as anticancer agents. Also, they have shown interactions in the transmembrane region sharing the same binding region of verapamil and zosuquidar.

Propafenone analogue with additional H-bond acceptor group shows increased inhibitory activity on P-glycoprotein

P-glycoprotein (P-gp) is an ATP-dependent efflux pump that has a marked impact on the absorption, distribution, and excretion of therapeutic drugs. As P-gp inhibition can result in drug-drug interactions and altered drug bioavailability, identifying molecular properties that are linked to inhibition is of great interest in drug development. In this study, we combined chemical synthesis, in vitro testing, quantitative structure-activity relationship analysis, and docking studies to investigate the role of hydrogen bond (H-bond) donor/acceptor properties in transporter-ligand interaction. In a previous work, it has been shown that propafenone analogs with a 4-hydroxy-4-piperidine moiety exhibit a generally 10-fold higher P-gp inhibitory activity than expected based on their lipophilicity. Here, we specifically expanded the data set by introducing substituents at position 4 of the 4-phenylpiperidine moiety to assess the importance of H-bond donor/acceptor features in this region. The results suggest that indeed an H-bond acceptor, such as hydroxy and methoxy, increases the affinity by forming a H-bond with Tyr310.

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.

Structural insights and influence of V599 mutations on the overall dynamics of BRAF protein against its kinase domains

Mutations in the BRAF gene are well known for their oncogenic effects. Point mutations in V599 are particularly oncogenic and are considered important for therapeutic purposes. Along with wild type, other V599 mutated BRAF variants viz. V599E, V599D and V599R are reported and crystals of the former two with inhibitor (BAY43-9006) are further detailed. Both wild-type and mutated BRAF forms show similar interaction patterns with BAY43-9006, but the 599th residue did not show any involvement in the interactions. Upon BAY43-9006 binding, kinase domains of both forms were found adopting essentially identical conformations. However, BAY43-9006 shows a varied activity profile in the case of the wild and V599E variant of the BRAF protein. Furthermore, MMGBSA binding energy results for all four BRAF variants, further revealed the importance of the 599th residue. In-depth analysis viz. molecular dynamics, residue correlation studies and residue interaction network (RIN) analyses were conducted, providing a deep insight into the 599th residue and its impact on the overall dynamics of BRAF protein. Our findings reveal that the mutated residue at the 599th position not only changed the BAY43-9006-BRAF binding behaviour but also produced a massive impact on the overall dynamic behaviour of the protein. The insights obtained herein could be of great relevance for designing new BRAF inhibitors aimed at getting ideal activity against all BRAF forms.

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.

The structure of the human ABC transporter ABCG2 reveals a novel mechanism for drug extrusion

The human ABC transporter ABCG2 (Breast Cancer Resistance Protein, BCRP) is implicated in anticancer resistance, in detoxification across barriers and linked to gout. Here, we generate a novel atomic model of ABCG2 using the crystal structure of ABCG5/G8. Extensive mutagenesis verifies the structure, disclosing hitherto unrecognized essential residues and domains in the homodimeric ABCG2 transporter. The elbow helix, the first intracellular loop (ICL1) and the nucleotide-binding domain (NBD) constitute pivotal elements of the architecture building the transmission interface that borders a central cavity which acts as a drug trap. The transmission interface is stabilized by salt-bridge interactions between the elbow helix and ICL1, as well as within ICL1, which is essential to control the conformational switch of ABCG2 to the outward-open drug-releasing conformation. Importantly, we propose that ICL1 operates like a molecular spring that holds the NBD dimer close to the membrane, thereby enabling efficient coupling of ATP hydrolysis during the catalytic cycle. These novel mechanistic data open new opportunities to therapeutically target ABCG2 in the context of related diseases.

Predicting drug-induced liver injury: The importance of data curation

Drug-induced liver injury (DILI) is a major issue for both patients and pharmaceutical industry due to insufficient means of prevention/prediction. In the current work we present a 2-class classification model for DILI, generated with Random Forest and 2D molecular descriptors on a dataset of 966 compounds. In addition, predicted transporter inhibition profiles were also included into the models. The initially compiled dataset of 1773 compounds was reduced via a 2-step approach to 966 compounds, resulting in a significant increase (p-value < 0.05) in model performance. The models have been validated via 10-fold cross-validation and against three external test sets of 921, 341 and 96 compounds, respectively. The final model showed an accuracy of 64% (AUC 68%) for 10-fold cross-validation (average of 50 iterations) and comparable values for two test sets (AUC 59%, 71% and 66%, respectively). In the study we also examined whether the predictions of our in-house transporter inhibition models for BSEP, BCRP, P-glycoprotein, and OATP1B1 and 1B3 contributed in improvement of the DILI mode. Finally, the model was implemented with open-source 2D RDKit descriptors in order to be provided to the community as a Python script.

Predicting Drug-Induced Cholestasis with the Help of Hepatic Transporters-An in Silico Modeling Approach

Cholestasis represents one out of three types of drug induced liver injury (DILI), which comprises a major challenge in drug development. In this study we applied a two-class classification scheme based on k-nearest neighbors in order to predict cholestasis, using a set of 93 two-dimensional (2D) physicochemical descriptors and predictions of selected hepatic transporters' inhibition (BSEP, BCRP, P-gp, OATP1B1, and OATP1B3). In order to assess the potential contribution of transporter inhibition, we compared whether the inclusion of the transporters' inhibition predictions contributes to a significant increase in model performance in comparison to the plain use of the 93 2D physicochemical descriptors. Our findings were in agreement with literature findings, indicating a contribution not only from BSEP inhibition but a rather synergistic effect deriving from the whole set of transporters. The final optimal model was validated via both 10-fold cross validation and external validation. It performs quite satisfactorily resulting in 0.686 ± 0.013 for accuracy and 0.722 ± 0.014 for area under the receiver operating characteristic curve (AUC) for 10-fold cross-validation (mean ± standard deviation from 50 iterations).

Virtual Screening of DrugBank Reveals Two Drugs as New BCRP Inhibitors

The breast cancer resistance protein (BCRP) is an ABC transporter playing a crucial role in the pharmacokinetics of drugs. The early identification of substrates and inhibitors of this efflux transporter can help to prevent or foresee drug-drug interactions. In this work, we built a ligand-based in silico classification model to predict the inhibitory potential of drugs toward BCRP. The model was applied as a virtual screening technique to identify potential inhibitors among the small-molecules subset of DrugBank. Ten compounds were selected and tested for their capacity to inhibit mitoxantrone efflux in BCRP-expressing PLB985 cells. Results identified cisapride (IC₅₀ = 0.4 µM) and roflumilast (IC₅₀ = 0.9 µM) as two new BCRP inhibitors. The in silico strategy proved useful to prefilter potential drug-drug interaction perpetrators among a database of small molecules and can reduce the amount of compounds to test.

Subtle Structural Differences Trigger Inhibitory Activity of Propafenone Analogues at the Two Polyspecific ABC Transporters: P-Glycoprotein (P-gp) and Breast Cancer Resistance Protein (BCRP)

The transmembrane ABC transporters P‐glycoprotein (P‐gp) and breast cancer resistance protein (BCRP) are widely recognized for their role in cancer multidrug resistance and absorption and distribution of compounds. Furthermore, they are linked to drug–drug interactions and toxicity. Nevertheless, due to their polyspecificity, a molecular understanding of the ligand‐transporter interaction, which allows designing of both selective and dual inhibitors, is still in its infancy. This study comprises a combined approach of synthesis, in silico prediction, and in vitro testing to identify molecular features triggering transporter selectivity. Synthesis and testing of a series of 15 propafenone analogues with varied rigidity and basicity of substituents provide first trends for selective and dual inhibitors. Results indicate that both the flexibility of the substituent at the nitrogen atom, as well as the basicity of the nitrogen atom, trigger transporter selectivity. Furthermore, inhibitory activity of compounds at P‐gp seems to be much more influenced by logP than those at BCRP. Exploiting these differences further should thus allow designing specific inhibitors for these two polyspecific ABC‐transporters.