Abstract: Triple-negative breast cancer (TNBC) has poor clinical prognosis. Lack of TNBC-specific biomarkers prevents active clinical intervention. We reasoned that TNBC must have its specific signature due to the lack of three key receptors to distinguish TNBC from other types of breast cancer. We also reasoned that coupling methylation and gene expression as a single unit may increase the specificity for the detected TNBC signatures. We further reasoned that choosing the proper controls may be critical to increasing the sensitivity to identify TNBC-specific signatures. Furthermore, we also considered that specific drugs could target the detected TNBC-specific signatures. We developed a system to identify potential TNBC signatures. It consisted of (1) coupling methylation and expression changes in TNBC to identify the methylation-regulated signature genes for TNBC; (2) using TPBC (triple-positive breast cancer) as the control to detect TNBC-specific signature genes; (3) searching in the drug database to identify those targeting TNBC signature genes. Using this system, we identified 114 genes with both altered methylation and expression, and 356 existing drugs targeting 10 of the 114 genes. Through docking and molecular dynamics simulation, we determined the structural basis between sapropterin, a drug used in the treatment of tetrahydrobiopterin deficiency, and PTGS2, a TNBC signature gene involved in the conversion of arachidonic acid to prostaglandins. Our study reveals the existence of rich TNBC-specific signatures, and many can be drug target and biomarker candidates for clinical applications.

Abstract: Gemcitabine is an anticancer drug used to treat a wide range of solid tumors and is a first line treatment for pancreatic cancer. Our group has previously developed novel conjugates of gemcitabine with cell-penetrating peptides (CPP), and here we report some preliminary data regarding the pharmacokinetics of gemcitabine, two gemcitabine-CPP conjugates and respective CPP gathered from GastroPlus, and analyze these results considering our previous evaluation of gemcitabine release and conjugates' bioactivity. Additionally, seeking to shed some light on the relation between the penetration ability of CPP and their physicochemical properties, chemical descriptors for the 20 natural amino acids were calculated, a new principal property scale (z-scale) was created and CPP prediction models were developed, establishing quantitative structure-activity relationships (QSAR). The z-scores of the peptides conjugated with gemcitabine are presented and analyzed with the aforementioned data.

Abstract: SUMMARY: Limited efficacy and intolerable safety limit therapeutic development and identification of potential liabilities earlier in development could significantly improve this process. Computational approaches which aggregate data from multiple sources and consider the drug's pathways effects could add to identification of these liabilities earlier. Such computational methods must be accessible to a variety of users beyond computational scientists, especially regulators and industry scientists, in order to impact the therapeutic development process. We have previously developed and published PathFX, an algorithm for identifying drug networks and phenotypes for understanding drug associations to safety and efficacy. Here we present a streamlined and easy-to-use PathFX web application that allows users to search for drug networks and associated phenotypes. We have also added visualization, and phenotype clustering to improve functionality and interpretability of PathFXweb. AVAILABILITY AND IMPLEMENTATION: https://www.pathfxweb.net/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Abstract: BACKGROUND: Enzyme-mediated biotransformation of pharmacological agents is a crucial step in xenobiotic detoxification and drug disposition. Herein, we investigated the metabolism and physicochemical properties of the top 200 most prescribed drugs (established) as well as drugs approved by the US Food and Drug Administration (FDA) between 2005 and 2016 (newly approved). OBJECTIVE: Our objective was to capture the changing trends in the routes of administration, physicochemical properties, and prodrug medications, as well as the contributions of drug-metabolizing enzymes and transporters to drug clearance. METHODS: The University of Washington Drug Interaction Database (DIDB((R))) as well as other online resources (e.g., CenterWatch.com, Drugs.com, DrugBank.ca, and PubChem.ncbi.nlm.nih.gov) was used to collect and stratify the dataset required for exploring the above-mentioned trends. RESULTS: Analyses revealed that ~ 90% of all drugs in the established and newly approved drug lists were administered systemically (oral or intravenous). Meanwhile, the portion of biologics (molecular weight > 1 kDa) was 15 times greater in the newly approved list than established drugs. Additionally, there was a 4.5-fold increase in the number of compounds with a high calculated partition coefficient (cLogP > 3) and a high total polar surface area (> 75 A(2)) in the newly approved drug vs. the established category. Further, prodrugs in established or newly approved lists were found to be converted to active compounds via hydrolysis, demethylases, and kinases. The contribution of cytochrome P450 (CYP) 3A4, as the major biotransformation pathway, has increased from 40% in the established drug list to 64% in the newly approved drug list. Moreover, the role of CYP1A2, CYP2C19, and CYP2D6 were decreased as major metabolizing enzymes among the newly approved medications. Among non-CYP major metabolizers, the contribution of alcohol dehydrogenases/aldehyde dehydrogenases (ADH/ALDH) and sulfotransferases decreased in the newly approved drugs compared with the established list. Furthermore, the highest contribution among uptake and efflux transporters was found for Organic Anion Transporting Polypeptide 1B1 (OATP1B1) and P-glycoprotein (P-gp), respectively. CONCLUSIONS: The higher portion of biologics in the newly approved drugs compared with the established list confirmed the growing demands for protein- and antibody-based therapies. Moreover, the larger number of hydrophilic drugs found in the newly approved list suggests that the probability of toxicity is likely to decrease. With regard to CYP-mediated major metabolism, CYP3A5 showed an increased involvement owing to the identification of unique probe substrates to differentiate CYP3As. Furthermore, the contribution of OATP1B1 and P-gp did not show a significant shift in the newly approved drugs as compared to the established list because of their broad substrate specificity.

Abstract: The peptidergic system is the most abundant network of ligand-receptor-mediated signaling in humans. However, the physiological roles remain elusive for numerous peptides and more than 100 G protein-coupled receptors (GPCRs). Here we report the pairing of cognate peptides and receptors. Integrating comparative genomics across 313 species and bioinformatics on all protein sequences and structures of human class A GPCRs, we identify universal characteristics that uncover additional potential peptidergic signaling systems. Using three orthogonal biochemical assays, we pair 17 proposed endogenous ligands with five orphan GPCRs that are associated with diseases, including genetic, neoplastic, nervous and reproductive system disorders. We also identify additional peptides for nine receptors with recognized ligands and pathophysiological roles. This integrated computational and multifaceted experimental approach expands the peptide-GPCR network and opens the way for studies to elucidate the roles of these signaling systems in human physiology and disease. VIDEO ABSTRACT.

Abstract: In the process of drug discovery and disease treatment, drug repositioning is broadly studied to identify biological targets for existing drugs. Many methods have been proposed for drug-target interaction prediction by taking into account different kinds of data sources. However, most of the existing methods only use one side information for drugs or targets to predict new targets for drugs. Some recent works have improved the prediction accuracy by jointly considering multiple representations of drugs and targets. In this work, the authors propose a drug-target prediction approach by matrix completion with multi-view side information (MCM) of drugs and proteins from both structural view and chemical view. Different from existing studies for drug-target prediction, they predict drug-target interaction by directly completing the interaction matrix between them. The experimental results show that the MCM method could obtain significantly higher accuracies than the comparison methods. They finally report new drug-target interactions for 26 FDA-approved drugs, and biologically discuss these targets using existing references.

Abstract: Drug distribution is a necessary component of models to predict human pharmacokinetics. A new membrane-based tissue-plasma partition coefficient (K p) method (K p,mem) to predict unbound tissue to plasma partition coefficients (K pu) was developed using in vitro membrane partitioning [fraction unbound in microsomes (f um)], plasma protein binding, and log P The resulting K p values were used in a physiologically based pharmacokinetic (PBPK) model to predict the steady-state volume of distribution (V ss) and concentration-time (C-t) profiles for 19 drugs. These results were compared with K p predictions using a standard method [the differential phospholipid K p prediction method (K p,dPL)], which differentiates between acidic and neutral phospholipids. The K p,mem method was parameterized using published rat K pu data and tissue lipid composition. The K pu values were well predicted with R (2) = 0.8. When used in a PBPK model, the V ss predictions were within 2-fold error for 12 of 19 drugs for K p,mem versus 11 of 19 for Kp,dPL With one outlier removed for K p,mem and two for K p,dPL, the V ss predictions for R (2) were 0.80 and 0.79 for the K p,mem and K p,dPL methods, respectively. The C-t profiles were also predicted and compared. Overall, the K p,mem method predicted the V ss and C-t profiles equally or better than the K p,dPL method. An advantage of using f um to parameterize membrane partitioning is that f um data are used for clearance prediction and are, therefore, generated early in the discovery/development process. Also, the method provides a mechanistically sound basis for membrane partitioning and permeability for further improving PBPK models. SIGNIFICANCE STATEMENT: A new method to predict tissue-plasma partition coefficients was developed. The method provides a more mechanistic basis to model membrane partitioning.

Abstract: An environmental risk assessment is presented for mycophenolic acid (MPA), an immunosuppressive pharmaceutical used for prevention of organ rejection, and its prodrug mycophenolate mofetil (MPM). Mycophenolic acid will not significantly adsorb to activated sludge. In activated sludge, (14) C-MPA attained >80% degradation, supporting an older environmental fate test with the same compound. Based on n-octanol/water distribution coefficient (log DOW ) values of 2.28, 0.48, and =-1.54 at pH 5, 7, and 9, respectively, MPA is not expected to bioaccumulate. Sales amounts of MPA+MPM in Europe were used to derive predicted environmental concentrations (PECs) in surface waters; PECs were refined by including expected biodegradation in sewage treatment, average drinking water use, and average dilution of the effluents in the receiving waters per country. In addition, the exposure to pharmaceuticals in the environment (ePiE) model was run for 4 European catchments. The PECs were complemented with 110 measured environmental concentrations (MECs), ranging from below the limit of quantitation (<0.001 microg/L) to 0.656 microg/L. Predicted no-effect concentrations (PNECs) were derived from chronic tests with cyanobacteria, green algae, daphnids, and fish. The comparison of PECs and MECs with the PNECs resulted in a differentiated environmental risk assessment in which the risk ratio of PEC/PNEC or MEC/PNEC was <1 in most cases (mostly >90%), meaning no significant risk, but a potential risk to aquatic organisms in generally <10% of instances. Because this assessment reveals a partial risk, the following questions must be asked: How much risk is acceptable? and Through which measures can this risk be reduced? These questions are all the more important in view of limited alternatives for MPM and MPA and the serious consequences of not using them. Environ Toxicol Chem 2019;38:2259-2278. (c) 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Abstract: BACKGROUND AND OBJECTIVES: Lack of information on the pharmacokinetics of the active moiety of Cannabis or the metabolites of delta-9-tetrahydrocannabinol (THC) does not seem to be discouraging medical or recreational use. Cytochrome P450 (CYP) 2C9, the primary enzyme responsible for THC metabolism, has two single nucleotide polymorphisms-Arg144Cys (*2) and Ile359Leu (*3). In the Caucasian population, allelic frequency is between 0.08 and 0.14 for CYP2C9*2 and between 0.04 and 0.16 for CYP2C9*3. In vitro data suggest that metabolic capacity for the variants CYP2C9*2 and CYP2C9*3 is about one-third compared to wild-type CYP2C9. Previous work has suggested exposure to the terminal metabolite is genetically determined. We therefore sought to characterize the pharmacokinetics of THC and its major metabolites 11-hydroxy-delta-9-tetrahydrocannabinol (THC-OH) and 11-nor-9-carboxy-delta-9-tetrahydrocannabinol (THC-COOH) in healthy volunteers with known CYP2C9 status by non-compartmental analysis (NCA), compartmental modeling (CM) and minimal physiologically based pharmacokinetic (mPBPK) modeling. METHODS: Blood samples drawn for THC, THC-OH and THC-COOH after a single intravenous (IV) bolus of 0.1 mg/kg (0.32 muM/kg) THC were analyzed using a validated LC-MS/MS method. NCA generated initial estimates and CM and the mPBPK model were then fit to plasma concentration data using non-linear mixed-effects modeling. Blood samples from orally dosed (10, 25 and 50 mg) THC brownies were added to validate the model. RESULTS: THC can be described as a high hepatic extraction ratio drug with blood flow-dependent metabolism not restricted by protein binding. THC hepatic clearance is dependent on the CYP2C9 genetic variant in the population. High extraction drugs display route-dependent metabolism. When administered via the IV or inhalation routes, induction or inhibition of CYP2C9 should be non-contributory as the elimination of THC is dependent only on liver blood flow. THC-OH is also a high extraction ratio drug, but its hepatic clearance is significantly impacted by the hepatic diffusional barrier that impedes its access to hepatic CYP2C9. THC-COOH is glucuronidated and renally cleared; subjects homozygous for CYP2C9*3 have reduced exposure to this metabolite as a result of the polymorphism reducing THC production, the hepatic diffusional barrier impeding egress from the hepatocyte, and increased renal clearance. CONCLUSION: It has recently been reported that the terminal metabolite THC-COOH is active, implying the exposure difference in individuals homozygous for CYP2C9*3 may become therapeutically relevant. Defining the metabolism of THC in humans is important, as it is increasingly being used as a drug to treat various diseases and its recreational use is also rising. We have used NCA, CM, and mPBPK modeling of THC and its metabolites to partially disentangle the complexity of cannabis disposition in humans.

Abstract: Actinobacteria in the Tsukamurella genus are aerobic, high-GC, Gram-positive mycolata, considered as opportunistic pathogens and isolated from various environmental sources, including sites contaminated with oil, urban or industrial waste and pesticides. Although studies look into xenobiotic biotransformation by Tsukamurella isolates, the relevant enzymes remain uncharacterized. We investigated the arylamine N-acetyltransferase (NAT) enzyme family, known for its role in the xenobiotic metabolism of prokaryotes and eukaryotes. Xenobiotic sensitivity of Tsukamurella paurometabola type strain DSM 20162(T) was assessed, followed by cloning, recombinant expression and functional characterization of its single NAT homolog (TSUPD)NAT1. The bacterium appeared quite robust against chloroanilines, but more sensitive to 4-anisidine and 2-aminophenol. However, metabolic activity was not evident towards those compounds, presumably due to mechanisms protecting cells from xenobiotic entry. Of the pharmaceutical arylhydrazines tested, hydralazine was toxic, but the bacterium was less sensitive to isoniazid, a drug targeting mycolic acid biosynthesis in mycobacteria. Although (TSUPD)NAT1 protein has an atypical Cys-His-Glu (instead of the expected Cys-His-Asp) catalytic triad, it is enzymatically active, suggesting that this deviation is likely due to evolutionary adaptation potentially serving a different function. The protein was indeed found to use malonyl-CoA, instead of the archetypal acetyl-CoA, as its preferred donor substrate. Malonyl-CoA is important for microbial biosynthesis of fatty acids (including mycolic acids) and polyketide chains, and the corresponding enzymatic systems have common evolutionary histories, also linked to xenobiotic metabolism. This study adds to accummulating evidence suggesting broad phylogenetic and functional divergence of microbial NAT enzymes that goes beyond xenobiotic metabolism and merits investigation.