Increased lipid peroxidation, apoptosis and selective cytotoxicity in colon cancer cell line LoVo and its doxorubicin-resistant subline LoVo/Dx in the presence of newly synthesized phenothiazine derivatives

Cancer cells often develop the resistance to pro-apoptotic signaling that makes them invulnerable to conventional treatment. Therapeutic strategies that make cancer cells enter the path of apoptosis are desirable due to the avoidance of inflammatory reaction that usually accompanies necrosis. In the present study phenothiazines (fluphenazine and four recently synthesized derivatives) were investigated in order to identify compounds with a potent anticancer activity. Since phenothiazines are known as multidrug resistance modulators the sensitive human colorectal adenocarcinoma cell line (LoVo) and its doxorubicin-resistant, ABCB1 overexpressing, subline (LoVo/Dx) have been employed as a model system. In studied cancer cells cytotoxic effect of the phenothiazine derivatives was accompanied by apoptosis and autophagy induction as well as by the increase of cellular lipid peroxidation and intracellular reactive oxygen species generation. Molecular modelling revealed that reactivity of phenothazines (manifested by their low energy gap) but not lipophilicity was positively correlated with their anticancer potency, pro-oxidant properties and apoptosis induction ability. Additionally, some of the studied compounds turned out to be more potent cytotoxic and pro-apoptotic agents in doxorubicin-resistant (LoVo/Dx) cells than in sensitive ones (LoVo). The hypothesis was assumed that studied phenothiazine derivatives induced apoptotic cell death by increasing the production of reactive oxygen species.

Methylene blue activates the PMCA activity and cross-interacts with amyloid β-peptide, blocking Aβ-mediated PMCA inhibition

The phenothiazine methylene blue (MB) is attracting increasing attention because it seems to have beneficial effects in the pathogenesis of Alzheimer's disease (AD). Among other factors, the presence of neuritic plaques of amyloid-β peptide (Aβ) aggregates, neurofibrilar tangles of tau and perturbation of cytosolic Ca²⁺ are important players of the disease. It has been proposed that MB decreases the formation of neuritic plaques due to Aβ aggregation. However, the molecular mechanism underlying this effect is far from clear. In this work, we show that MB stimulates the Ca²⁺-ATPase activity of the plasma membrane Ca²⁺-ATPase (PMCA) in human tissues from AD-affected brain and age-matched controls and also from pig brain and cell cultures. In addition, MB prevents and even blocks the inhibitory effect of Aβ on PMCA activity. Functional analysis with mutants and fluorescence experiments strongly suggest that MB binds to PMCA, at the C-terminal tail, in a site located close to the last transmembrane helix and also that MB binds to the peptide. Besides, Aβ increases PMCA affinity for MB. These results point out a novel molecular basis of MB action on Aβ and PMCA as mediator of its beneficial effect on AD.

Chemical structure of phenothiazines and their biological activity

Phenothiazines belong to the oldest, synthetic antipsychotic drugs, which do not have their precursor in the world of natural compounds. Apart from their fundamental neuroleptic action connected with the dopaminergic receptors blockade, phenothiazine derivatives also exert diverse biological activities, which account for their cancer chemopreventive-effect, as: calmodulin- and protein kinase C inhibitory-actions, anti-proliferative effect, inhibition of P-glycoprotein transport function and reversion of multidrug resistance. According to literature data on relations between chemical structure of phenothiazines and their biological effects, the main directions for further chemical modifications have been established. They are provided and discussed in this review paper.

Communications on quantum similarity, part 3: a geometric-quantum similarity molecular superposition algorithm

This work describes a new procedure to obtain optimal molecular superposition based on quantum similarity (QS): the geometric-quantum similarity molecular superposition (GQSMS) algorithm. It has been inspired by the QS Aufbau principle, already described in a previous work, to build up coherently quantum similarity matrices (QSMs). The cornerstone of the present superposition technique relies upon the fact that quantum similarity integrals (QSIs), defined using a GTO basis set, depend on the squared intermolecular atomic distances. The resulting QSM structure, constructed under the GQSMS algorithm, becomes not only optimal in terms of its QSI elements but can also be arranged to produce a positive definite matrix global structure. Kruskal minimum spanning trees are also discussed as a device to order molecular sets described in turn by means of QSM. Besides the main subject of this work, focused on MS and QS, other practical considerations are also included in this study: essentially the use of elementary Jacobi rotations as QSM refinement tools and inward functions as QSM scaling methods.

Synthesis and biochemical characterization of new phenothiazines and related drugs as MDR reversal agents

Chemotherapy is one of the most important methods in the treatment of cancer. However, development of drug resistance during chemotherapy is the leading cause of treatment failure and decreased survival in cancer patients. Multidrug resistance (MDR) is one of the extensively studied forms of drug resistance for more than 30 years. The members of ATP-binding cassette protein family are responsible for multidrug resistance with P-glycoprotein as most representative transporter. To overcome multidrug resistance, pharmacological modulation of the transporters by efflux pump inhibitors seem to be the first choice, but preclinical studies did not lead to clinical applications. Therefore, a systematical research for pharmacophor structures is a promising strategy to increase the efficacy of those drugs still influencing multidrug resistance. In this study a range of phenothiazine derivatives was synthesizied with systematical variation of three molecule domains. The biochemical determination of multidrug resistance reversal activity was achieved with the crystalviolet assay on LLC-PK1/MDR1 cells. The results will be discussed considering of hypotheses in the literature directed to new structure-acitivity relationships to overcome drug resistance in the future.

Membrane effects of the antitumor drugs doxorubicin and thaliblastine: comparison to multidrug resistance modulators verapamil and trans-flupentixol

The interactions of the antitumor drugs doxorubicin and thaliblastine with model membranes composed of neutral (phosphatidylcholine) and negatively charged (phosphatidylserine) phospholipids were studied by differential scanning calorimetry and nuclear magnetic resonance. The membrane activities of doxorubicin and thaliblastine were compared to those of the powerful multidrug resistance (MDR) modulators trans-flupentixol and verapamil. The results point out to the potential role of the drug-membrane interactions for the effects of doxorubicin and thaliblastine in resistant tumor cells. They direct also to the artificial membranes as a suitable tool for screening of compounds with potential ability to modulate MDR.

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.

QSAR and 3D-QSAR of phenothiazine type multidrug resistance modulators in P388/ADR cells

A series of 25 phenothiazines and structurally related compounds was investigated by QSAR (quantitative structure activity relationship) and 3D-QSAR methods with respect to their MDR (multidrug resistance) reversing activity in P388/ADR- murine leukemia cell line resistant to ADR (adriamycin). The objective was to outline structural properties important for the investigated activity. Different measures for MDR reversal were used and compared. Two 3D-QSAR approaches were applied-CoMFA (comparative molecular field analysis) and CoMSIA (comparative molecular similarity indices analysis). Both, neutral and protonated forms of the compounds were investigated. Molecular models with good predictive power were derived using a hydrophobic field alone and a combination of steric, hydrophobic, and hydrogen bond acceptor fields of the compounds. In the combined models highest contribution of the hydrogen bond acceptor field was noticed. Thus, the dominant role of the hydrophobic and hydrogen bond acceptor fields for MDR reversing activity of the investigated compounds was demonstrated. The structural regions responsible for the differences in anti-MDR activity were analyzed in respect to their hydrophobic, hydrogen bond acceptor and steric nature. The results may direct design of new phenothiazines and related compounds as MDR modulators.

New phenothiazine-type multidrug resistance modifiers: anti-MDR activity versus membrane perturbing potency

The phenothiazine multidrug resistance (MDR) modulators are chemically diversified but share the common feature to be hydrophobic cationic molecules. Molecular mechanisms of their action may involve interactions with either P-glycoprotein or membrane lipid matrix. In the present work we study the anti-MDR and biophysical membrane effects of new phenothiazine derivatives differing in the type of group substituting phenothiazine ring at position 2 (H-, Cl-, CF(3)-) and in the side chain group (NHCO(2)CH(3) or NHSO(2)CH(3)). Within each phenothiazine subset we found that anti-MDR activity (determined by P-glycoprotein inhibition assessed by flow cytometry) correlates with the theoretically calculated hydrophobicity value (logP) and experimental parameters (determined by calorimetry and fluorescence spectroscopy) of lipid bilayers. It is concluded that the biological and biophysical activity of phenothiazine derivatives depends more on the type of ring substitution than on the nature of the side chain group.

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 predicting human ADME parameters in silico

Understanding the development of a scientific approach is a valuable exercise in gauging the potential directions the process could take in the future. The relatively short history of applying computational methods to absorption, distribution, metabolism and excretion (ADME) can be split into defined periods. The first began in the 1960s and continued through the 1970s with the work of Corwin Hansch et al. Their models utilized small sets of in vivo ADME data. The second era from the 1980s through 1990s witnessed the widespread incorporation of in vitro approaches as surrogates of in vivo ADME studies. These approaches fostered the initiation and increase in interpretable computational ADME models available in the literature. The third era is the present were there are many literature data sets derived from in vitro data for absorption, drug-drug interactions (DDI), drug transporters and efflux pumps [P-glycoprotein (P-gp), MRP], intrinsic clearance and brain penetration, which can theoretically be used to predict the situation in vivo in humans. Combinatorial synthesis, high throughput screening and computational approaches have emerged as a result of continual pressure on pharmaceutical companies to accelerate drug discovery while decreasing drug development costs. The goal has become to reduce the drop-out rate of drug candidates in the latter, most expensive stages of drug development. This is accomplished by increasing the failure rate of candidate compounds in the preclinical stages and increasing the speed of nomination of likely clinical candidates. The industry now understands the reasons for clinical failure other than efficacy are mainly related to pharmacokinetics and toxicity. The late 1990s saw significant company investment in ADME and drug safety departments to assess properties such as metabolic stability, cytochrome P-450 inhibition, absorption and genotoxicity earlier in the drug discovery paradigm. The next logical step in this process is the evaluation of higher throughput data to determine if computational (in silico) models can be constructed and validated from it. Such models would allow an exponential increase in the number of compounds screened virtually for ADME parameters. A number of researchers have started to utilize in silico, in vitro and in vivo approaches in parallel to address intestinal permeability and cytochrome P-450-mediated DDI. This review will assess how computational approaches for ADME parameters have evolved and how they are likely to progress.

Molecular field Topology analysis method in QSAR studies of organic compounds

A new method of QSAR analysis for organic compounds, molecular field topology analysis (MFTA), is considered that involves the topological superposition of the training set structures and the construction of a molecular supergraph (MSG). This enables the creation of the uniform descriptor vectors based on the local physicochemical parameters (atom and bond properties) of the molecules. The application of this technique is illustrated by a number of examples, and its features are discussed. The MFTA is especially suitable for solving the problems where the analysis of three-dimensional structure is either unnecessary or complicated.

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.

Molecular modeling of phenothiazines and related drugs as multidrug resistance modifiers: a comparative molecular field analysis study

A set of 40 phenothiazines, thioxanthenes, and structurally related drugs with multidrug resistance modulating activity in tumor cells in vitro were selected from literature data and subjected to three-dimensional quantitative structure-activity relationship study using comparative molecular field analysis (CoMFA). More than 350 CoMFA models were derived and evaluated using steric, electrostatic, and hydrophobic fields alone and in combination. Four alignment strategies based on selected atom pairs or field fit alignment were compared. Several training and test sets were analyzed for both neutral and protonated drug forms separately. Each chemical class was trained and tested individually, and finally the classes were combined together into integrated models. All models obtained were statistically significant and most of them highly predictive. All fields contributed to MDR reversing activity, and hydrophobic fields improved the correlative and predictive power of the models in all cases. The results point to the role of hydrophobicity as a space-directed molecular property to explain differences in anti-MDR activity of the drugs studied.