Human cytochromes P450 in the metabolism of drugs: new molecular models of enzyme-substrate interactions

Electrochemical transformations catalyzed by cytochrome P450s and peroxidases

Cytochrome P450s (Cyt P450s) and peroxidases are enzymes featuring iron heme cofactors that have wide applicability as biocatalysts in chemical syntheses. Cyt P450s are a family of monooxygenases that oxidize fatty acids, steroids, and xenobiotics, synthesize hormones, and convert drugs and other chemicals to metabolites. Peroxidases are involved in breaking down hydrogen peroxide and can oxidize organic compounds during this process. Both heme-containing enzymes utilize active Fe^IVO intermediates to oxidize reactants. By incorporating these enzymes in stable thin films on electrodes, Cyt P450s and peroxidases can accept electrons from an electrode, albeit by different mechanisms, and catalyze organic transformations in a feasible and cost-effective way. This is an advantageous approach, often called bioelectrocatalysis, compared to their biological pathways in solution that require expensive biochemical reductants such as NADPH or additional enzymes to recycle NADPH for Cyt P450s. Bioelectrocatalysis also serves as an ex situ platform to investigate metabolism of drugs and bio-relevant chemicals. In this paper we review biocatalytic electrochemical reactions using Cyt P450s including C-H activation, S-oxidation, epoxidation, N-hydroxylation, and oxidative N-, and O-dealkylation; as well as reactions catalyzed by peroxidases including synthetically important oxidations of organic compounds. Design aspects of these bioelectrocatalytic reactions are presented and discussed, including enzyme film formation on electrodes, temperature, pH, solvents, and activation of the enzymes. Finally, we discuss challenges and future perspective of these two important bioelectrocatalytic systems.

XenoNet: Inference and Likelihood of Intermediate Metabolite Formation

Drug metabolism is a common cause of adverse drug reactions. Drug molecules can be metabolized into reactive metabolites, which can conjugate to biomolecules, like protein and DNA, in a process termed bioactivation. To mitigate adverse reactions caused by bioactivation, both experimental and computational screening assays are utilized. Experimental assays for assessing the formation of reactive metabolites are low throughput and expensive to perform, so they are often reserved until later stages of the drug development pipeline when the drug candidate pools are already significantly narrowed. In contrast, computational methods are high throughput and cheap to perform to screen thousands to millions of compounds for potentially toxic molecules during the early stages of the drug development pipeline. Commonly used computational methods focus on detecting and structurally characterizing reactive metabolite-biomolecule adducts or predicting sites on a drug molecule that are liable to form reactive metabolites. However, such methods are often only concerned with the structure of the initial drug molecule or of the adduct formed when a biomolecule conjugates to a reactive metabolite. Thus, these methods are likely to miss intermediate metabolites that may lead to subsequent reactive metabolite formation. To address these shortcomings, we create XenoNet, a metabolic network predictor, that can take a pair of a substrate and a target product as input and (1) enumerate pathways, or sequences of intermediate metabolite structures, between the pair, and (2) compute the likelihood of those pathways and intermediate metabolites. We validate XenoNet on a large, chemically diverse data set of 17 054 metabolic networks built from a literature-derived reaction database. Each metabolic network has a defined substrate molecule that has been experimentally observed to undergo metabolism into a defined product metabolite. XenoNet can predict experimentally observed pathways and intermediate metabolites linking the input substrate and product pair with a recall of 88 and 46%, respectively. Using likelihood scoring, XenoNet also achieves a top-one pathway and intermediate metabolite accuracy of 93.6 and 51.9%, respectively. We further validate XenoNet against prior methods for metabolite prediction. XenoNet significantly outperforms all prior methods across multiple metrics. XenoNet is available at https://swami.wustl.edu/xenonet.

The In Silico Drug Discovery Toolbox: Applications in Lead Discovery and Optimization

BACKGROUND

Discovery and development of a new drug is a long lasting and expensive journey that takes around 20 years from starting idea to approval and marketing of new medication. Despite R&D expenditures have been constantly increasing in the last few years, the number of new drugs introduced into market has been steadily declining. This is mainly due to preclinical and clinical safety issues, which still represent about 40% of drug discontinuation. To cope with this issue, a number of in silico techniques are currently being used for an early stage evaluation/prediction of potential safety issues, allowing to increase the drug-discovery success rate and reduce costs associated with the development of a new drug.

METHODS

In the present review, we will analyse the early steps of the drug-discovery pipeline, describing the sequence of steps from disease selection to lead optimization and focusing on the most common in silico tools used to assess attrition risks and build a mitigation plan.

RESULTS

A comprehensive list of widely used in silico tools, databases, and public initiatives that can be effectively implemented and used in the drug discovery pipeline has been provided. A few examples of how these tools can be problem-solving and how they may increase the success rate of a drug discovery and development program have been also provided. Finally, selected examples where the application of in silico tools had effectively contributed to the development of marketed drugs or clinical candidates will be given.

CONCLUSION

The in silico toolbox finds great application in every step of early drug discovery: (i) target identification and validation; (ii) hit identification; (iii) hit-to-lead; and (iv) lead optimization. Each of these steps has been described in details, providing a useful overview on the role played by in silico tools in the decision-making process to speed-up the discovery of new drugs.

Development of an allosteric inhibitor class blocking RNA elongation by the respiratory syncytial virus polymerase complex

Respiratory syncytial virus (RSV) represents a significant health threat to infants and to elderly or immunocompromised individuals. There are currently no vaccines available to prevent RSV infections, and disease management is largely limited to supportive care, making the identification and development of effective antiviral therapeutics against RSV a priority. To identify effective chemical scaffolds for managing RSV disease, we conducted a high-throughput anti-RSV screen of a 57,000-compound library. We identified a hit compound that specifically blocked activity of the RSV RNA-dependent RNA polymerase (RdRp) complex, initially with moderate low-micromolar potency. Mechanistic characterization in an in vitro RSV RdRp assay indicated that representatives of this compound class block elongation of RSV RNA products after initial extension by up to three nucleotides. Synthetic hit-to-lead exploration yielded an informative 3D quantitative structure-activity relationship (3D-QSAR) model and resulted in analogs with more than 20-fold improved potency and selectivity indices (SIs) of >1,000. However, first-generation leads exhibited limited water solubility and poor metabolic stability. A second optimization strategy informed by the 3D-QSAR model combined with in silico pharmacokinetics (PK) predictions yielded an advanced lead, AVG-233, that demonstrated nanomolar activity against both laboratory-adapted RSV strains and clinical RSV isolates. This anti-RSV activity extended to infection of established cell lines and primary human airway cells. PK profiling in mice revealed 34% oral bioavailability of AVG-233 and sustained high drug levels in the circulation after a single oral dose of 20 mg/kg. This promising first-in-class lead warrants further development as an anti-RSV drug.

The effects of dietary and herbal phytochemicals on drug transporters

Membrane transporter proteins (the ABC transporters and SLC transporters) play pivotal roles in drug absorption and disposition, and thus determine their efficacy and safety. Accumulating evidence suggests that the expression and activity of these transporters may be modulated by various phytochemicals (PCs) found in diets rich in plants and herbs. PC absorption and disposition are also subject to the function of membrane transporter and drug metabolizing enzymes. PC-drug interactions may involve multiple major drug transporters (and metabolizing enzymes) in the body, leading to alterations in the pharmacokinetics of substrate drugs, and thus their efficacy and toxicity. This review summarizes the reported in vitro and in vivo interactions between common dietary PCs and the major drug transporters. The oral absorption, distribution into pharmacological sanctuaries and excretion of substrate drugs and PCs are considered, along with their possible interactions with the ABC and SLC transporters which influence these processes.

SOMP: web server for in silico prediction of sites of metabolism for drug-like compounds

A new freely available web server site of metabolism predictor to predict the sites of metabolism (SOM) based on the structural formula of chemicals has been developed. It is based on the analyses of 'structure-SOM' relationships using a Bayesian approach and labelled multilevel neighbourhoods of atoms descriptors to represent the structures of over 1000 metabolized xenobiotics. The server allows predicting SOMs that are catalysed by 1A2, 2C9, 2C19, 2D6 and 3A4 isoforms of cytochrome P450 and enzymes of the UDP-glucuronosyltransferase family. The average invariant accuracy of prediction that was calculated for the training sets (using leave-one-out cross-validation) and evaluation sets is 0.9 and 0.95, respectively.

AVAILABILITY AND IMPLEMENTATION

Freely available on the web at http://www.way2drug.com/SOMP.

Computational identification and binding analysis of orphan human cytochrome P450 4X1 enzyme with substrates

Background

Cytochrome P450s (CYPs) are important heme-containing proteins, well known for their monooxygenase reaction. The human cytochrome P450 4X1 (CYP4X1) is categorized as “orphan” CYP because of its unknown function. In recent studies it is found that this enzyme is expressed in neurovascular functions of the brain. Also, various studies have found the expression and activity of orphan human cytochrome P450 4X1 in cancer. It is found to be a potential drug target for cancer therapy. However, three-dimensional structure, the active site topology and substrate specificity of CYP4X1 remain unclear.

Methods

In the present study, the three-dimensional structure of orphan human cytochrome P450 4X1 was generated by homology modeling using Modeller 9v8. The generated structure was accessed for geometrical errors and energy stability using PROCHECK, VERFIY 3D and PROSA. A molecular docking analysis was carried out against substrates arachidonic acid and anandamide and the docked substrates were predicted for drug-likeness, ADME-Tox parameters and biological spectrum activity.

Results

The three-dimensional model of orphan human cytochrome P450 4X1 was generated and assessed with various structural validation programmes. Docking of orphan human cytochrome P450 4X1 with arachidonic acid revealed that TYR 112, ALA 126, ILE 222, ILE 223, THR 312, LEU 315, ALA 316, ASP 319, THR 320, PHE 491 and ILE 492 residues were actively participating in the interaction, while docking of CYP4X1 with anandamide showed that TYR 112, GLN 114, PRO 118, ALA 126, ILE 222, ILE 223, SER 251, LEU 315, ALA 316 and PHE 491 key residues were involved in strong interaction.

Conclusion

From this study, several key residues were identified to be responsible for the binding of arachidonic acid and anandamide with orphan human cytochrome P450 4X1. Both substrates obeyed Lipinski rule of five in drug-likeness test and biological spectrum prediction showed anticarcinogenic activity. Compared to anandamide, arachidonic acid showed strong interaction with cytochrome P450 4X1 and also less health effect in certain human system in ADME-Tox prediction. These findings provide useful information on the biological role and structure-based drug design of orphan human cytochrome P450 4X1.

Metabolism site prediction based on xenobiotic structural formulas and PASS prediction algorithm

A new ligand-based method for the prediction of sites of metabolism (SOMs) for xenobiotics has been developed on the basis of the LMNA (labeled multilevel neighborhoods of atom) descriptors and the PASS (prediction of activity spectra for substances) algorithm and applied to predict the SOMs of the 1A2, 2C9, 2C19, 2D6, and 3A4 isoforms of cytochrome P450. An average IAP (invariant accuracy of prediction) of SOMs calculated by the leave-one-out cross-validation procedure was 0.89 for the developed method. The external validation was made with evaluation sets containing data on biotransformations for 57 cardiovascular drugs. An average IAP of regioselectivity for evaluation sets was 0.83. It was shown that the proposed method exceeds accuracy of SOM prediction by RS-Predictor for CYP 1A2, 2D6, 2C9, 2C19, and 3A4 and is comparable to or better than SMARTCyp for CYP 2C9 and 2D6.

Protein expression profiling of nuclear membrane protein reveals potential biomarker of human hepatocellular carcinoma

Background

Complex molecular events lead to development and progression of liver cirrhosis to HCC. Differentially expressed nuclear membrane associated proteins are responsible for the functional and structural alteration during the progression from cirrhosis to carcinoma. Although alterations/ post translational modifications in protein expression have been extensively quantified, complementary analysis of nuclear membrane proteome changes have been limited. Deciphering the molecular mechanism that differentiate between normal and disease state may lead to identification of biomarkers for carcinoma.

Results

Many proteins displayed differential expression when nuclear membrane proteome of hepatocellular carcinoma (HCC), fibrotic liver, and HepG2 cell line were assessed using 2-DE and ESI-Q-TOF MS/MS. From the down regulated set in HCC, we have identified for the first time a 15 KDa cytochrome b5A (CYB5A), ATP synthase subunit delta (ATPD) and Hemoglobin subunit beta (HBB) with 11, 5 and 22 peptide matches respectively. Furthermore, nitrosylation studies with S-nitrosocysteine followed by immunoblotting with anti SNO-cysteine demonstrated a novel and biologically relevant post translational modification of thiols of CYB5A in HCC specimens only. Immunofluorescence images demonstrated increased protein S-nitrosylation signals in the tumor cells and fibrotic region of HCC tissues. The two other nuclear membrane proteins which were only found to be nitrosylated in case of HCC were up regulated ATP synthase subunit beta (ATPB) and down regulated HBB. The decrease in expression of CYB5A in HCC suggests their possible role in disease progression. Further insight of the functional association of the identified proteins was obtained through KEGG/ REACTOME pathway analysis databases. String 8.3 interaction network shows strong interactions with proteins at high confidence score, which is helpful in characterization of functional abnormalities that may be a causative factor of liver pathology.

Conclusion

These findings may have broader implications for understanding the mechanism of development of carcinoma. However, large scale studies will be required for further verification of their critical role in development and progression of HCC.

The effects of flavonoids on the ABC transporters: consequences for the pharmacokinetics of substrate drugs

INTRODUCTION

The flavonoids are a large group of dietary plant compounds with suggested health benefits. There is accumulating evidence that many of these flavonoids can interact with the major drug transporters (and metabolizing enzymes) in the body, leading to alterations in the pharmacokinetics of substrate drugs, and thus their efficacy and toxicity.

AREAS COVERED

This review summarizes and updates the reported in vitro and in vivo interactions between common dietary flavonoids and the major drug-effluxing ABC transporters; these include P-glycoprotein, breast cancer resistance protein and multidrug resistance proteins 1 and 2. In contrast to previous reviews, the ADME of flavonoids are considered, along with their glycosides and Phase II conjugates. The authors also consider their possible interactions with the ABC transporters in the oral absorption, distribution into pharmacological sanctuaries and excretion of substrate drugs. Electronic databases, including PubMed, Scopus and Google Scholar were searched to identify appropriate in vitro and in vivo ABC transporter-flavonoid interactions, particularly within the last 10 years.

EXPERT OPINION

Caution is advised when taking flavonoid-containing supplements or herbal remedies concurrently with drugs. Further clinical studies are warranted to explore the impact of flavonoids and their metabolites on the pharmacokinetics, efficacy and toxicity of drugs.

In vivo-in vitro-in silico pharmacokinetic modelling in drug development: current status and future directions

Although clinical drug trials are indispensable in providing an appropriate background for dosage recommendations, they can provide mechanistic pharmacokinetic information only indirectly with the help of certain biomarkers for pathological, physiological and pharmacological determinants. Thus, to provide such mechanistic information of clinical value, various in vitro and in silico tests and approaches are increasingly employed in drug discovery and development. Integration of the results of these primarily preclinical studies has been made possible by various computational models, such as in vitro-in vivo extrapolation of hepatic clearance or physiologically based pharmacokinetic modelling. In this article, the current status of these modelling approaches is surveyed and some examples are given, highlighting advantages and disadvantages in applying them at various phases of drug development. A new paradigm of model-based drug development is briefly described, and the importance of the approach of integrating all of the information coming from different investigations at all levels--be it in vivo, in vitro or in silico--is emphasized.

In silico toxicology - non-testing methods

In silico toxicology in its broadest sense means “anything that we can do with a computer in toxicology.” Many different types of in silico methods have been developed to characterize and predict toxic outcomes in humans and environment. The term non-testing methods denote grouping approaches, structure–activity relationship, and expert systems. These methods are already used for regulatory purposes and it is anticipated that their role will be much more prominent in the near future. This Perspective will delineate the basic principles of non-testing methods and evaluate their role in current and future risk assessment of chemical compounds.

From known knowns to known unknowns: predicting in vivo drug metabolites

'It is better to be useful than perfect'. This review attempts to critically cover and assess the currently available approaches and tools to answer the crucial question: Is it possible (and if it is, to what extent is it possible) to predict in vivo metabolites and their abundances on the basis of in vitro and preclinical animal studies? In preclinical drug development, it is possible to produce metabolite patterns from a candidate drug by virtual means (i.e., in silico models), but these are not yet validated. However, they may be useful to cover the potential range of metabolites. In vitro metabolite patterns and apparent relative abundances are produced by various in vitro systems employing tissue preparations (mainly liver) and in most cases using liquid chromatography-mass spectrometry analytical techniques for tentative identification. The pattern of the metabolites produced depends on the enzyme source; the most comprehensive source of drug-metabolizing enzymes is cultured human hepatocytes, followed by liver homogenate fortified with appropriate cofactors. For specific purposes, such as the identification of metabolizing enzyme(s), recombinant enzymes can be used. Metabolite data from animal in vitro and in vivo experiments, despite known species differences, may help pinpoint metabolites that are not apparently produced in in vitro human systems, or suggest alternative experimental approaches. The range of metabolites detected provides clues regarding the enzymes attacking the molecule under study. We also discuss established approaches to identify the major enzymes. The last question, regarding reliability and robustness of metabolite extrapolations from in vitro to in vivo, both qualitatively and quantitatively, cannot be easily answered. There are a number of examples in the literature suggesting that extrapolations are generally useful, but there are only a few systematic and comprehensive studies to validate in vitro-in vivo extrapolations. In conclusion, extrapolation from preclinical metabolite data to the in vivo situation is certainly useful, but it is not known to what extent.

Alternative (non-animal) methods for cosmetics testing: current status and future prospects-2010

The 7th amendment to the EU Cosmetics Directive prohibits to put animal-tested cosmetics on the market in Europe after 2013. In that context, the European Commission invited stakeholder bodies (industry, non-governmental organisations, EU Member States, and the Commission's Scientific Committee on Consumer Safety) to identify scientific experts in five toxicological areas, i.e. toxicokinetics, repeated dose toxicity, carcinogenicity, skin sensitisation, and reproductive toxicity for which the Directive foresees that the 2013 deadline could be further extended in case alternative and validated methods would not be available in time. The selected experts were asked to analyse the status and prospects of alternative methods and to provide a scientifically sound estimate of the time necessary to achieve full replacement of animal testing. In summary, the experts confirmed that it will take at least another 7-9 years for the replacement of the current in vivo animal tests used for the safety assessment of cosmetic ingredients for skin sensitisation. However, the experts were also of the opinion that alternative methods may be able to give hazard information, i.e. to differentiate between sensitisers and non-sensitisers, ahead of 2017. This would, however, not provide the complete picture of what is a safe exposure because the relative potency of a sensitiser would not be known. For toxicokinetics, the timeframe was 5-7 years to develop the models still lacking to predict lung absorption and renal/biliary excretion, and even longer to integrate the methods to fully replace the animal toxicokinetic models. For the systemic toxicological endpoints of repeated dose toxicity, carcinogenicity and reproductive toxicity, the time horizon for full replacement could not be estimated.

Comparison of in vitro metabolism of ticlopidine by human cytochrome P450 2B6 and rabbit cytochrome P450 2B4

A recent X-ray crystal structure of a rabbit cytochrome P450 2B4 (CYP2B4)-ticlopidine complex indicated that the compound could be modeled with either the thiophene or chlorophenyl group oriented toward the heme prosthetic group. Subsequent NMR relaxation and molecular docking studies suggested that orientation with the chlorophenyl ring closer to the heme was the preferred one. To evaluate the predictive value of these findings, the oxidation of ticlopidine by reconstituted CYP2B4 was studied and compared with CYP2B6, in which the thiophene portion of the molecule likely orients toward the heme. In vitro incubation of ticlopidine with both enzymes yielded the same set of metabolites: 7-hydroxyticlopidine (M1), 2-oxoticlopidine (M2), 5-(2-chlorobenzyl)thieno[3,2-c]pyridin-5-ium metabolite (M3), 5-(2-chlorobenzyl)thieno[3,2-c]pyridin-5-ium metabolite (M4), ticlopidine N-oxide (M5), and ticlopidine S-oxide dimer, a dimerization product of ticlopidine S-oxide (M6). The rates of metabolite formation deviated markedly from linearity with time, consistent with the known inactivation of CYP2B6 by ticlopidine. Fitting to a first-order equation yielded similar rate constants (k(obs)) for both enzymes. However, the amplitude (R(max)) of M1 and M6 formation was 4 to 5 times higher for CYP2B6 than CYP2B4, indicating a greater residence time of ticlopidine with its thiophene ring closer to heme in CYP2B6. In contrast, CYP2B4 formed M4 and M5 in more abundance than CYP2B6, indicating an alternate orientation. Overall, the results suggest that the preferential orientation of ticlopidine in the active site of CYP2B4 predicted by X-ray crystallography and NMR studies is unproductive and that ticlopidine likely reorients within CYP2B4 to a more productive mode.

The SMARTCyp cytochrome P450 metabolism prediction server

SUMMARY

The SMARTCyp server is the first web application for site of metabolism prediction of cytochrome P450-mediated drug metabolism.

AVAILABILITY

The SMARTCyp server is freely available for use on the web at www.farma.ku.dk/smartcyp where the SMARTCyp Java program and source code is also available for download.

CONTACT

smartcyp@farma.ku.dk; lo@farma.ku.dk

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Human CYPs involved in drug metabolism: structures, substrates and binding affinities

IMPORTANCE OF THE FIELD

There is current interest in the CYPs primarily due to their important role in the Phase I metabolism of foreign compounds, including pharmaceuticals, agrochemicals and environmental pollutants, to which mankind is exposed.

AREAS COVERED IN THIS REVIEW

The roles of the human CYPs are introduced in the context of using structural modelling and quantitative structure-activity relationships for rationalizing substrate binding, selectivity and rates of metabolism, particularly for drugs in current clinical use. The importance of compound lipophilicity in both substrate binding and metabolic rate is emphasised, together with the employment of an automated docking method (AutoDock) for estimating binding energy and likely route of metabolism for drug substrates.

WHAT THE READER WILL GAIN

The location of key interacting groups on both substrate and enzyme tends to define the preferred outcome of CYP-mediated drug metabolism in the majority of cases investigated thus far. This enables one to draw up a simple model of the important features present in the binding sites of CYPs which relate to substrate selectivity and likely positions of metabolism.

TAKE HOME MESSAGE

For the major CYPs involved in human drug metabolism, it would appear that there is a relatively well-defined key distance, in terms of number of intervening atoms, between the main sites of binding and CYP-mediated metabolism.

Drug interactions

Drugs for allergy are often taken in combination with other drugs, either to treat allergy or other conditions. In common with many pharmaceuticals, most such drugs are subject to metabolism by P450 enzymes and to transmembrane transport. This gives rise to considerable potential for drug-drug interactions, to which must be added consideration of drug-diet interactions. The potential for metabolism-based drug interactions is increasingly being taken into account during drug development, using a variety of in silico and in vitro approaches. Prediction of transporter-based interactions is not as advanced. The clinical importance of a drug interaction will depend upon a number of factors, and it is important to address concerns quantitatively, taking into account the therapeutic index of the compound.

Comprehensive characterization of cytochrome P450 isozyme selectivity across chemical libraries

The cytochrome P450 (CYP) gene family catalyzes drug metabolism and bioactivation and is therefore relevant to drug development. We determined potency values for 17,143 compounds against five recombinant CYP isozymes (1A2, 2C9, 2C19, 2D6 and 3A4) using an in vitro bioluminescent assay. The compounds included libraries of US Food and Drug Administration (FDA)-approved drugs and screening libraries. We observed cross-library isozyme inhibition (30-78%) with important differences between libraries. Whereas only 7% of the typical screening library was inactive against all five isozymes, 33% of FDA-approved drugs were inactive, reflecting the optimized pharmacological properties of the latter. Our results suggest that low CYP 2C isozyme activity is a common property of drugs, whereas other isozymes, such as CYP 2D6, show little discrimination between drugs and unoptimized compounds found in screening libraries. We also identified chemical substructures that differentiated between the five isozymes. The pharmacological compendium described here should further the understanding of CYP isozymes.

Improving the oral bioavailability of beneficial polyphenols through designed synergies

A substantial and growing consumer demand exists for plant-based functional foods that improve general health and wellbeing. Amongst consumed phytochemicals, the polyphenolic compounds tend to be the most bioactive. Many commonly consumed polyphenols have been shown to have specific and potent health-promoting activities when assessed by high-throughput in vitro assays and when administered to experimental animals by injection. However, very few have been shown to have any beneficial effects in animals or man when orally consumed, because of the poor bioavailability exhibited by most polyphenols following the ingestion. Consumed polyphenols, like most pharmaceuticals, are regarded as xenobiotics by the body and must overcome many barriers, including extensive enzymatic and chemical modification during digestion and absorption, to reach their site(s) of action. This is especially true for polyphenols targeting the brain, which is protected by the tightly regulated blood-brain barrier. Interestingly, many polyphenols are also known to specifically modify some of the metabolic and transport processes that govern bioavailability. Therefore, the opportunity exists to increase the bioactivity of beneficial polyphenols by designing specific synergistic interactions with polyphenols that improve their oral bioavailability. This hypothesis and review paper will discuss some of the endogenous systems that limit the bioavailability of ingested polyphenols to the body and the brain, and the means by which bioavailability may be improved by specifically designing synergies between orally consumed polyphenols.

Proteomic expression signature distinguishes cancerous and nonmalignant tissues in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is an aggressive liver cancer but clinically validated biomarkers that can predict natural history of malignant progression are lacking. The present study explored the proteome-wide patterns of HCC to identify biomarker signature that could distinguish cancerous and nonmalignant liver tissues. A retrospective cohort of 80 HBV-associated HCC was included and both the tumor and adjacent nontumor tissues were subjected to proteome-wide expression profiling by 2-DE method. The subjects were randomly divided into the training (n = 55) and validation (n = 25) subsets, and the data analyzed by classification-and-regression tree algorithm. Protein markers were characterized by MALDI-ToF/MS and confirmed by immunohistochemistry, Western blotting and qPCR assays. Proteomic expression signature composed of six biomarkers (haptoglobin, cytochrome b5, progesterone receptor membrane component 1, heat shock 27 kDa protein 1, lysosomal proteinase cathepsin B, keratin I) was developed as a classifier model for predicting HCC. We further evaluated the model using both leave-one-out procedure and independent validation, and the overall sensitivity and specificity for HCC both are 92.5%, respectively. Clinical correlation analysis revealed that these biomarkers were significantly associated with serum AFP, total protein levels and the Ishak's score. The described model using biomarker signatures could accurately distinguish HCC from nonmalignant tissues, which may also provide hints on how normal hepatocytes are transformed to malignant state during tumor progression.