Reversal of multidrug resistance by bis(phenylalkyl)amines and structurally related compounds

Prediction of P-glycoprotein inhibitors with machine learning classification models and 3D-RISM-KH theory based solvation energy descriptors

Development of novel in silico methods for questing novel PgP inhibitors is crucial for the reversal of multi-drug resistance in cancer therapy. Here, we report machine learning based binary classification schemes to identify the PgP inhibitors from non-inhibitors using molecular solvation theory with excellent accuracy and precision. The excess chemical potential and partial molar volume in various solvents are calculated for PgP± (PgP inhibitors and non-inhibitors) compounds with the statistical-mechanical based three-dimensional reference interaction site model with the Kovalenko-Hirata closure approximation (3D-RISM-KH molecular theory of solvation). The statistical importance analysis of descriptors identified the 3D-RISM-KH based descriptors as top molecular descriptors for classification. Among the constructed classification models, the support vector machine predicted the test set of Pgp± compounds with highest accuracy and precision of ~ 97% for test set. The validation of models confirms the robustness of state-of-the-art molecular solvation theory based descriptors in identification of the Pgp± compounds.

Novel Potent ABCB1 Modulator, Phenethylisoquinoline Alkaloid, Reverses Multidrug Resistance in Cancer Cell

ATP-binding cassette (ABC) transporters, which are concerned with the efflux of anticancer drugs from cancer cells, have a pivotal role in multidrug resistance (MDR). In particular, ABCB1 is a well-known ABC transporter that develops MDR in many cancer cells. Some ABCB1 modulators can reverse ABCB1-mediated MDR; however, no modulators with clinical efficacy have been approved. The aim of this study was to identify novel ABCB1 modulators by using high-throughput screening. Of the 5861 compounds stored at Tohoku University, 13 compounds were selected after the primary screening via a fluorescent plate reader-based calcein acetoxymethylester (AM) efflux assay. These 13 compounds were validated in a flow cytometry-based calcein AM efflux assay. Two isoquinoline derivatives were identified as novel ABCB1 inhibitors, one of which was a phenethylisoquinoline alkaloid, (±)-7-benzyloxy-1-(3-benzyloxy-4-methoxyphenethyl)-1,2,3,4-tetrahydro-6-methoxy-2-methylisoquinoline oxalate. The compound, a phenethylisoquinoline alkaloid, was subsequently evaluated in the cytotoxicity assay and shown to significantly enhance the reversal of ABCB1-mediated MDR. In addition, the compound activated the ABCB1-mediated ATP hydrolysis and inhibited the photolabeling of ABCB1 with [¹²⁵I]-iodoarylazidoprazosin. Furthermore, the compound also reversed the resistance to paclitaxel without increasing the toxicity in the ABCB1-overexpressing KB-V1 cell xenograft model. Overall, we concluded that the newly identified phenethylisoquinoline alkaloid reversed ABCB1-mediated MDR through direct interaction with the substrate-binding site of ABCB1. These findings may contribute to the development of more potent and less toxic ABCB1 modulators, which could overcome ABCB1-mediated MDR.

P-glycoprotein interactions of novel psychoactive substances - stimulation of ATP consumption and transport across Caco-2 monolayers

In contrast to drugs for therapeutic use, there are only few data available concerning interactions between P-glycoprotein (P-gp) and drugs of abuse (DOA). In this work, interactions between structurally diverse DOA and P-gp were investigated using different strategies. First, the effect on the P-gp ATPase activity was studied by monitoring of ATP consumption after addition to recombinant, human P-gp. Second, DOA showing an increased ATP consumption were further characterized regarding their transport across filter grown Caco-2- monolayers. Analyses were performed by luminescence and liquid chromatography-mass spectrometry, respectively. Among the nine DOA initially screened, benzedrone, diclofensine, glaucine, JWH-200, MDBC, WIN-55,212-2 showed an increase of ATP consumption in the ATPase stimulation assay. In Caco-2 transport studies, Glaucine, JWH-200, mitragynine, WIN-55,212-2 could moreover be identified as non-transported substrates, but inhibitors of P-gp activity. Thus, drug-drug or drug-food interactions should be very likely for these compounds.

In silico structure-based screening of versatile P-glycoprotein inhibitors using polynomial empirical scoring functions

P-glycoprotein (P-gp) is an ATP (adenosine triphosphate)-binding cassette transporter that causes multidrug resistance of various chemotherapeutic substances by active efflux from mammalian cells. P-gp plays a pivotal role in limiting drug absorption and distribution in different organs, including the intestines and brain. Thus, the prediction of P-gp–drug interactions is of vital importance in assessing drug pharmacokinetic and pharmacodynamic properties. To find the strongest P-gp blockers, we performed an in silico structure-based screening of P-gp inhibitor library (1,300 molecules) by the gradient optimization method, using polynomial empirical scoring (POLSCORE) functions. We report a strong correlation (r²=0.80, F=16.27, n=6, P<0.0157) of inhibition constants (Ki_exp or pKi_exp; experimental Ki or negative decimal logarithm of Ki_exp) converted from experimental IC₅₀ (half maximal inhibitory concentration) values with POLSCORE-predicted constants (Ki_POLSCORE or pKi_POLSCORE), using a linear regression fitting technique. The hydrophobic interactions between P-gp and selected drug substances were detected as the main forces responsible for the inhibition effect. The results showed that this scoring technique might be useful in the virtual screening and filtering of databases of drug-like compounds at the early stage of drug development processes.

Exploratory Chemistry toward the Identification of a New Class of Multidrug Resistance Reverters Inspired by Pervilleine and Verapamil Models

On the basis of the present knowledge of the substrate recognition site of ABC transporter proteins and inspired by the structures of verapamil and pervilleine A, a new class of Pgp-mediated multidrug resistance (MDR) reverters has been designed and synthesized. The new compounds are flexible molecules carrying one or two basic nitrogen atoms flanked, at properly modulated distance, by two aromatic moieties. Most of the molecules studied possess MDR inhibitory activity on anthracycline-resistant erythroleukemia K 562 cells, showing a potency that is higher than that of the reference compound verapamil and, in a few cases (7, 12, 13,17, 20, 22, 28), is in the high nanomolar range. These compounds may be useful leads to develop new MDR reverting agents. In fact, the chemical structure of the class is fairly simple and can be implemented in a variety of ways that will allow the synthesis of new compounds that might be useful leads for the development of drugs to control Pgp-dependent MDR.

A Naive Bayes Classifier for Prediction of Multidrug Resistance Reversal Activity on the Basis of Atom Typing

Multidrug resistance (MDR), the ability of cancer cells to become simultaneously resistant to different drugs, remains an unsolved challenge in cancer chemotherapy. The use of MDR reversal (MDRR) agents is a promising approach to overcome this problem. For the design and development of such agents, it would be desirable to have a reliable model to estimate the MDRR activity of compounds. Presented here is a naive Bayes classifier to categorize MDRR agents into active and inactive classes, which uses a universal, generic molecular-descriptor system.(1) The naive Bayes classifier was built from a 424 compound training set, selected from 609 druglike compounds in the publicly available "Klopman set". The model correctly predicted MDRR activities for 82.2% of 185 compounds in a testing set. The cumulative probabilities were proven useful for prioritizing the compounds for testing. The impact of attribute dependences on the performance of the classifier was examined. As an unsupervised learner with no tuning parameters, a naive Bayes classifier is capable of providing an objective comparison of the effectiveness of different molecular descriptors. The relative performance of the classifiers constructed from either an atom-type-based molecular descriptor or the long-range functional-class fingerprint descriptors FCFP_6 or FCFP_2 was compared. Employing an atom typing descriptor with the naive Bayes classification, it enables the interpretability of the resulting model, which offers extra information for the rational design of MDRR agents.

Diphenylcyclohexylamine derivatives as new potent multidrug resistance (MDR) modulators

A series of compounds with a diphenylmethyl cyclohexyl skeleton, loosely related to verapamil, has been synthesized and tested as MDR modulators on anthracycline-resistant erythroleukemia K 562 cells. Their residual cardiovascular action (negative inotropic and chronotropic activity as well as vasorelaxant activity) was evaluated on guinea-pig isolated atria preparations and on guinea-pig aortic strip preparations. Most compounds of the series possess a good MDR-reverting activity together with a low cardiovascular action. Among them, compounds 3a1, 7a, and 8a are more potent than verapamil as MDR reverters and lack any cardiovascular action; they can represent useful leads for the development of new safe MDR reversing drugs.

QSAR studies on P-glycoprotein-regulated multidrug resistance and on its reversal by phenothiazines

Multidrug resistance is brought about largely by membrane transport proteins such as P-glycoprotein (P-gp). We have developed a quantitative structure-activity relationship (QSAR) for P-gp-associated ATPase activity for a diverse set of 22 drugs, and found that such activity is related to substrate molecular size and polarity. We have also developed a QSAR for drug efflux from the blood-brain barrier of another diverse set of 22 drugs, and found that such efflux is a function of drug size and polarisability. Thirdly, we have carried out a QSAR analysis of the ability of 157 phenothiazines and related drugs to reverse multidrug resistance. We were unable to obtain a good QSAR for the whole data-set, but when we divided the data-set into sub-sets of closely related structures, a series of good correlations was obtained, most of which incorporated descriptors that model molecular size and polarity/polarisability. In no instance did we find any evidence that hydrogen bonding or hydrophobicity play a part in multidrug resistance or its reversal, despite that fact that several other workers have reported that these effects appear to be important here.

The medicinal chemistry of multidrug resistance (MDR) reversing drugs

Multidrug resistance (MDR) is a kind of resistance of cancer cells to multiple classes of chemotherapic drugs that can be structurally and mechanistically unrelated. Classical MDR regards altered membrane transport that results in lower cell concentrations of cytotoxic drug and is related to the over expression of a variety of proteins that act as ATP-dependent extrusion pumps. P-glycoprotein (Pgp) and multidrug resistance protein (MRP1) are the most important and widely studied members of the family that belongs to the ABC superfamily of transporters. It is apparent that, besides their role in cancer cell resistance, these proteins have multiple physiological functions as well, since they are expressed also in many important non-tumoural tissues and are largely present in prokaryotic organisms. A number of drugs have been identified which are able to reverse the effects of Pgp, MRPI and sister proteins, on multidrug resistance. The first MDR modulators discovered and studied in clinical trials were endowed with definite pharmacological actions so that the doses required to overcome MDR were associated with unacceptably high side effects. As a consequence, much attention has been focused on developing more potent and selective modulators with proper potency, selectivity and pharmacokinetics that can be used at lower doses. Several novel MDR reversing agents (also known as chemosensitisers) are currently undergoing clinical evaluation for the treatment of resistant tumours. This review is concerned with the medicinal chemistry of MDR reversers, with particular attention to the drugs that are presently in development.

Progress in understanding the structure-activity relationships of P-glycoprotein

Efflux out of cells by P-glycoprotein (P-gp) represents a serious liability for pharmaceuticals, particularly for anti-cancer drugs. Consequently, identification of compounds as potential substrates is important for understanding their bioavailability. Also, the development of agents which reverse this multi-drug resistance phenotype has received considerable attention. Assays for determining these activities are reviewed. Recent literature and studies into the structure-activity relationships (SAR) of the resulting data are discussed. Multiple binding sites and other complicating factors have prevented the development of a truly general, conclusive SAR either for substrate or inhibitory activities. Consequently, many models have tended to address only very general properties, such as lipophilicity and size. However, progress has been made in the last few years toward more specific SAR suggesting well-defined structural features responsible for both activities. The future of understanding the details of P-gp SAR lies in more specific assays that target specific binding sites and mechanisms of action.

Classification of multidrug-resistance reversal agents using structure-based descriptors and linear discriminant analysis

Linear discriminant analysis is used to generate models to classify multidrug-resistance reversal agents based on activity. Models are generated and evaluated using multidrug-resistance reversal activity values for 609 compounds measured using adriamycin-resistant P388 murine leukemia cells. Structure-based descriptors numerically encode molecular features which are used in model formation. Two types of models are generated: one type to classify compounds as inactive, moderately active, and active (three-class problem) and one type to classify compounds as inactive or active without considering the moderately active class (two-class problem). Two activity distributions are considered, where the separation between inactive and active compounds is different. When the separation between inactive and active classes is small, a model based on nine topological descriptors is developed that produces a classification rate of 83.1% correct for an external prediction set. Larger separation between active and inactive classes raises the prediction set classification rate to 92.0% correct using a model with six topological descriptors. Models are further validated through Monte Carlo experiments in which models are generated after class labels have been scrambled. The classification rates achieved demonstrate that the models developed could serve as a screening mechanism to identify potentially useful MDRR agents from large libraries of compounds.

Reversal of drug resistance in sarcoma-45 by the new calmodulin antagonist--trihydrochloride of [1,2,5-trimethyl-4-phenyl-4-beta-[N-(beta-ethylamino)-N-4'-methoxybe nzy l]-ethylamino] piperidine (AR-2)

The anti-drug resistance effect of three derivatives (AR-1, AR-2 and AR-3) of [1,2,5-trimethyl-4-phenyl-4-beta-(N,N-disubstituted-ethylamino)] piperidines, that were evaluated as calcium and calmodulin antagonists, was studied on doxorubicin (ADM) and vincristine (VCR) resistant Sarcoma-45 inoculated rats. Treatment with ADM (5 mg/kg) or VCR (3 mg/kg) alone, as well as with AR-1, AR-2 or AR-3 (50 mg/kg) alone, had no effect on tumor growth. However, AR-2 in dose 50 mg/kg (calmodulin antagonist), but not AR-1 and AR-3 (calcium channel blocker), administered with ADM (5 mg/kg) or VCR (3 mg/kg), significantly suppressed tumor growth 80% and 70%, respectively. Two rats treated with ADM/AR-2 and one treated with VCR/AR-2 were cured. 170 kDa protein was purified from sarcoma-45 tumor cells to apparent homogeneity by successive steps of phosphocellulose, DEAE-cellulose, and AR-2-coupled sepharose chromatography. The protein proved to be immunopositive with the P-glycoprotein-specific monoclonal antibody. It is concluded that the effect of AR-2 can be explained by both hydrophobic and electrostatic interaction with a protein target (170 kDa P-glycoprotein) in resistant sarcoma-45 tumor cell's membrane.

Analysis of the tangled relationships between P-glycoprotein-mediated multidrug resistance and the lipid phase of the cell membrane

P-glycoprotein (Pgp), the so-called multidrug transporter, is a plasma membrane glycoprotein often involved in the resistance of cancer cells towards multiple anticancer agents in the multidrug-resistant (MDR) phenotype. It has long been recognized that the lipid phase of the plasma membrane plays an important role with respect to multidrug resistance and Pgp because: the compounds involved in the MDR phenotype are hydrophobic and diffuse passively through the membrane; Pgp domains involved in drug binding are located within the putative transmembrane segments; Pgp activity is highly sensitive to its lipid environment; and Pgp may be involved in lipid trafficking and metabolism. Unraveling the different roles played by the membrane lipid phase in MDR is relevant, not only to the evaluation of the precise role of Pgp, but also to the understanding of the mechanism of action and function of Pgp. With this aim, I review the data from different fields (cancer research, medicinal chemistry, membrane biophysics, pharmaceutical research) concerning drug-membrane, as well as Pgp-membrane, interactions. It is emphasized that the lipid phase of the membrane cannot be overlooked while investigating the MDR phenotype. Taking into account these aspects should be useful in the search of ways to obviate MDR and could also be relevant to the study of other multidrug transporters.

Design, synthesis, and in vitro activity of catamphiphilic reverters of multidrug resistance: discovery of a selective, highly efficacious chemosensitizer with potency in the nanomolar range

On the basis of the results obtained in previous research, three series of compounds (A-C), derived from verapamil, were designed and synthesized to obtain drugs able to revert multidrug resistance (MDR), an acquired resistance that frequently impairs cancer chemotherapy. The ability of the obtained compounds to revert MDR was evaluated on anthracycline-resistant erythroleukemia K 562 cells, measuring the uptake of THP-adriamycin (pirarubicin) by continuous spectrofluorometric monitoring of the decrease of the fluorescence signal of the anthracycline at 590 nm (lambdaex = 480 nm), after incubation with cells. Cardiovascular activity, which is responsible for unwanted side effects, was also evaluated. The results obtained show that many of the compounds studied are potent reverters of MDR and are endowed with reduced cardiovascular activity. One of the compounds (7, MM36) presents a pharmacological profile (unprecedented nanomolar potency, high reversal of MDR, low cardiovascular activity) that makes it a promising drug candidate to treat MDR and a useful tool for studying P-glycoprotein.

P-glycoprotein-mediated multidrug resistance: experimental and clinical strategies for its reversal

The study of the cellular, biochemical, and molecular biology and pharmacology of MDR has provided one of the most active and exciting areas within cancer research and one that holds great promise for translation into clinical benefit. While convincing evidence for the functional role of P-gp in mediating clinical drug resistance in humans remains elusive, studies of the clinical expression of P-gp and trials of chemosensitizers with cancer chemotherapy suggest "resistance modification" strategies may be effective in some tumors with intrinsic or acquired drug resistance. However, even if P-gp-associated MDR proves to be a relevant and reversible cause of clinical drug resistance, numerous problems remain to be solved before effective clinical chemosensitization may be achieved. Such factors as absorption, distribution, and metabolism; the effect of chemosensitizers on chemotherapeutic drug clearance; toxicity to normal tissues expressing P-gp; and the most efficacious modulator regimens all remain to be defined in vivo. Clearly, the identification of more specific, potent, and less clinically toxic chemosensitizers for clinical use remains critical to the possible success of this approach. Nonetheless, the finding that a number of pharmacological agents can antagonize a well-characterized form of experimental drug resistance provides promise for potential clinical applications. Further study of chemosensitizers in humans and the rational design of novel chemosensitizers with improved activity should define the importance of MDR in clinically resistant cancer.