A network-based target overlap score for characterizing drug combinations: High correlation with cancer clinical trial results

Drug combinations are highly efficient in systemic treatment of complex multigene diseases such as cancer, diabetes, arthritis and hypertension. Most currently used combinations were found in empirical ways, which limits the speed of discovery for new and more effective combinations. Therefore, there is a substantial need for efficient and fast computational methods. Here, we present a principle that is based on the assumption that perturbations generated by multiple pharmaceutical agents propagate through an interaction network and can cause unexpected amplification at targets not immediately affected by the original drugs. In order to capture this phenomenon, we introduce a novel Target Overlap Score (TOS) that is defined for two pharmaceutical agents as the number of jointly perturbed targets divided by the number of all targets potentially affected by the two agents. We show that this measure is correlated with the known effects of beneficial and deleterious drug combinations taken from the DCDB, TTD and Drugs.com databases. We demonstrate the utility of TOS by correlating the score to the outcome of recent clinical trials evaluating trastuzumab, an effective anticancer agent utilized in combination with anthracycline- and taxane-based systemic chemotherapy in HER2-receptor (erb-b2 receptor tyrosine kinase 2) positive breast cancer. © 2015 Ligeti et al

In vitro antileishmanial and antischistosomal activities of anemonin isolated from the fresh leaves of Ranunculus multifidus forsk

Leishmaniasis and schistosomiasis are neglected tropical diseases (NTDs) infecting the world's poorest populations. Effectiveness of the current antileishmanial and antischistosomal therapies are significantly declining, which calls for an urgent need of new effective and safe drugs. In Ethiopia fresh leaves of Ranunculus multifidus Forsk. are traditionally used for the treatment of various ailments including leishmaniasis and eradication of intestinal worms. In the current study, anemonin isolated from the fresh leaves of R. multifidus was assessed for its in vitro antileishmanial and antischistosomal activities. Anemonin was isolated from the hydro-distilled extract of the leaves of R. multifidus. Antileishmanial activity was assessed on clinical isolates of the promastigote and amastigote forms of Leishmania aethiopica and L. donovani clinical isolates. Resazurin reduction assay was used to determine antipromastigote activity, while macrophages were employed for antiamastigote and cytotoxicity assays. Antischistosomal assays were performed against adult Schistosoma mansoni and newly transformed schistosomules (NTS). Anemonin displayed significant antileishmanial activity with IC50 values of 1.33 nM and 1.58 nM against promastigotes and 1.24 nM and 1.91 nM against amastigotes of L. aethiopica and L. donovani, respectively. It also showed moderate activity against adult S. mansoni and NTS (49% activity against adult S. mansoni at 10 microM and 41% activity against NTS at 1 microM). The results obtained in this investigation indicate that anemonin has the potential to be used as a template for designing novel antileishmanial and antischistosomal pharmacophores

Anthelmintic activity and cytotoxic effects of compounds isolated from the fruits of Ozoroa insignis del. (Anacardiaceae)

Ozoroa insignis Del. is an ethnobotanical plant widely used in traditional medicine for various ailments, including schistosomiasis, tapeworm, and hookworm infections. From the so far not investigated fruits of Ozoroa insignis, the anthelmintic principles could be isolated through bioassay-guided isolation using Caenorhabditis elegans and identified by NMR spectroscopic analysis and mass spectrometric studies. Isolated 6-[8(Z)-pentadecenyl] anacardic (1), 6-[10(Z)-heptadecenyl] anacardic acid (2), and 3-[7(Z)-pentadecenyl] phenol (3) were evaluated against the 5 parasitic organisms Schistosoma mansoni (adult and newly transformed schistosomula), Strongyloides ratti, Heligmosomoides polygyrus, Necator americanus, and Ancylostoma ceylanicum, which mainly infect humans and other mammals. Compounds 1-3 showed good activity against Schistosoma mansoni, with compound 1 showing the best activity against newly transformed schistosomula with 50% activity at 1microM. The isolated compounds were also evaluated for their cytotoxic properties against PC-3 (human prostate adenocarcinoma) and HT-29 (human colorectal adenocarcinoma) cell lines, whereby compounds 2 and 3 showed antiproliferative activity in both cancer cell lines, while compound 1 exhibited antiproliferative activity only on PC-3 cells. With an IC50 value of 43.2 microM, compound 3 was found to be the most active of the 3 investigated compounds

Sucrose in the concentrated solution or the supercooled “state” : a review of caramelisation reactions and physical behaviour

Sucrose is probably one of the most studied molecules by food scientists, since it plays an important role as an ingredient or preserving agent in many formulations and technological processes. When sucrose is present in a product with a concentration near or greater than the saturation point—i.e. in the supercooled state—it possesses high potentialities for the food industry in areas as different as pastry industry, dairy and frozen desserts or films and coatings production. This paper presents a review on critical issues and research on highly concentrated sucrose solutions—mainly, on sucrose thermal degradation and relaxation behaviour in such solutions. The reviewed works allow identifying several issues with great potential for contributing to significant advances in Food Science and Technology.Authors are grateful for the valuable discussions with Teresa S. Brandao and Rosiane Lopes da Cunha during this research. Author M. A. C. Quintas acknowledges the financial support of her research by FCT grant SFRH/BPD/41715/2007

Pharmacokinetics of cytisine after single intravenous and oral administration in rabbits

The aim of this study is to develop a sensitive HPLC method for the quantitative determination of cytisine in serum and to characterize the pharmacokinetic behaviour of cytisine after oral and intravenous administration in rabbits. The pharmacokinetic behaviour of cytisine is studied in male and female New Zealand rabbits after oral and intravenous administration. Cytisine is administered orally (dose of 5 mg/kg b.w.) under fasting condition (12 hours) and intravenously (dose 1 mg/kg b.w.) in the marginal ear vein. Cytisine serum concentrations are measured using a highly selective and sensitive validated HPLC method with UV detection. Linearity of the method is in the range 12–2 400 µg/L; accuracy and precision are both within ± 10%, and the limit of detection is 4 µg/L. Selectivity and stability are also validated. Basic pharmacokinetic parameters of cytisine after single oral and intravenous administration are calculated using TOPFIT software. Pharmacokinetic analysis suggests a rapid but incomplete absorption of cytisine after oral administration

Predicting enzyme targets for cancer drugs by profiling human Metabolic reactions in NCI-60 cell lines

<p>Abstract</p> <p>Background</p> <p>Drugs can influence the whole metabolic system by targeting enzymes which catalyze metabolic reactions. The existence of interactions between drugs and metabolic reactions suggests a potential way to discover drug targets.</p> <p>Results</p> <p>In this paper, we present a computational method to predict new targets for approved anti-cancer drugs by exploring drug-reaction interactions. We construct a Drug-Reaction Network to provide a global view of drug-reaction interactions and drug-pathway interactions. The recent reconstruction of the human metabolic network and development of flux analysis approaches make it possible to predict each metabolic reaction's cell line-specific flux state based on the cell line-specific gene expressions. We first profile each reaction by its flux states in NCI-60 cancer cell lines, and then propose a kernel k-nearest neighbor model to predict related metabolic reactions and enzyme targets for approved cancer drugs. We also integrate the target structure data with reaction flux profiles to predict drug targets and the area under curves can reach 0.92.</p> <p>Conclusions</p> <p>The cross validations using the methods with and without metabolic network indicate that the former method is significantly better than the latter. Further experiments show the synergism of reaction flux profiles and target structure for drug target prediction. It also implies the significant contribution of metabolic network to predict drug targets. Finally, we apply our method to predict new reactions and possible enzyme targets for cancer drugs.</p

Impedance Responses Reveal β2-Adrenergic Receptor Signaling Pluridimensionality and Allow Classification of Ligands with Distinct Signaling Profiles

The discovery that drugs targeting a single G protein-coupled receptor (GPCR) can differentially modulate distinct subsets of the receptor signaling repertoire has created a challenge for drug discovery at these important therapeutic targets. Here, we demonstrate that a single label-free assay based on cellular impedance provides a real-time integration of multiple signaling events engaged upon GPCR activation. Stimulation of the β2-adrenergic receptor (β2AR) in living cells with the prototypical agonist isoproterenol generated a complex, multi-featured impedance response over time. Selective pharmacological inhibition of specific arms of the β2AR signaling network revealed the differential contribution of Gs-, Gi- and Gβγ-dependent signaling events, including activation of the canonical cAMP and ERK1/2 pathways, to specific components of the impedance response. Further dissection revealed the essential role of intracellular Ca2+ in the impedance response and led to the discovery of a novel β2AR-promoted Ca2+ mobilization event. Recognizing that impedance responses provide an integrative assessment of ligand activity, we screened a collection of β-adrenergic ligands to determine if differences in the signaling repertoire engaged by compounds would lead to distinct impedance signatures. An unsupervised clustering analysis of the impedance responses revealed the existence of 5 distinct compound classes, revealing a richer signaling texture than previously recognized for this receptor. Taken together, these data indicate that the pluridimensionality of GPCR signaling can be captured using integrative approaches to provide a comprehensive readout of drug activity

Prediction of potential drug targets based on simple sequence properties

<p>Abstract</p> <p>Background</p> <p>During the past decades, research and development in drug discovery have attracted much attention and efforts. However, only 324 drug targets are known for clinical drugs up to now. Identifying potential drug targets is the first step in the process of modern drug discovery for developing novel therapeutic agents. Therefore, the identification and validation of new and effective drug targets are of great value for drug discovery in both academia and pharmaceutical industry. If a protein can be predicted in advance for its potential application as a drug target, the drug discovery process targeting this protein will be greatly speeded up. In the current study, based on the properties of known drug targets, we have developed a sequence-based drug target prediction method for fast identification of novel drug targets.</p> <p>Results</p> <p>Based on simple physicochemical properties extracted from protein sequences of known drug targets, several support vector machine models have been constructed in this study. The best model can distinguish currently known drug targets from non drug targets at an accuracy of 84%. Using this model, potential protein drug targets of human origin from Swiss-Prot were predicted, some of which have already attracted much attention as potential drug targets in pharmaceutical research.</p> <p>Conclusion</p> <p>We have developed a drug target prediction method based solely on protein sequence information without the knowledge of family/domain annotation, or the protein 3D structure. This method can be applied in novel drug target identification and validation, as well as genome scale drug target predictions.</p

Predicting Inactive Conformations of Protein Kinases Using Active Structures: Conformational Selection of Type-II Inhibitors

Protein kinases have been found to possess two characteristic conformations in their activation-loops: the active DFG-in conformation and the inactive DFG-out conformation. Recently, it has been very interesting to develop type-II inhibitors which target the DFG-out conformation and are more specific than the type-I inhibitors binding to the active DFG-in conformation. However, solving crystal structures of kinases with the DFG-out conformation remains a challenge, and this seriously hampers the application of the structure-based approaches in development of novel type-II inhibitors. To overcome this limitation, here we present a computational approach for predicting the DFG-out inactive conformation using the DFG-in active structures, and develop related conformational selection protocols for the uses of the predicted DFG-out models in the binding pose prediction and virtual screening of type-II ligands. With the DFG-out models, we predicted the binding poses for known type-II inhibitors, and the results were found in good agreement with the X-ray crystal structures. We also tested the abilities of the DFG-out models to recognize their specific type-II inhibitors by screening a database of small molecules. The AUC (area under curve) results indicated that the predicted DFG-out models were selective toward their specific type-II inhibitors. Therefore, the computational approach and protocols presented in this study are very promising for the structure-based design and screening of novel type-II kinase inhibitors

Novel insight into the reaction of nitro, nitroso and hydroxylamino benzothiazinones and of benzoxacinones with Mycobacterium tuberculosis DprE1

Abstract Nitro-substituted 1,3-benzothiazinones (nitro-BTZs) are mechanism-based covalent inhibitors of Mycobacterium tuberculosis decaprenylphosphoryl-β-D-ribose-2′-oxidase (DprE1) with strong antimycobacterial properties. We prepared a number of oxidized and reduced forms of nitro-BTZs to probe the mechanism of inactivation of the enzyme and to identify opportunities for further chemistry. The kinetics of inactivation of DprE1 was examined using an enzymatic assay that monitored reaction progress up to 100 min, permitting compound ranking according to k inact/K i values. The side-chain at the 2-position and heteroatom identity at the 1-position of the BTZs were found to be important for inhibitory activity. We obtained crystal structures with several compounds covalently bound. The data suggest that steps upstream from the covalent end-points are likely the key determinants of potency and reactivity. The results of protein mass spectrometry using a 7-chloro-nitro-BTZ suggest that nucleophilic reactions at the 7-position do not operate and support a previously proposed mechanism in which BTZ activation by a reduced flavin intermediate is required. Unexpectedly, a hydroxylamino-BTZ showed time-dependent inhibition and mass spectrometry corroborated that this hydroxylamino-BTZ is a mechanism-based suicide inhibitor of DprE1. With this BTZ derivative, we propose a new covalent mechanism of inhibition of DprE1 that takes advantage of the oxidation cycle of the enzyme