Double Delta (Hungary)

A label-free, optical waveguide lightmode spectroscopy based immunosensor was developed for frog (Bombina orientalis) vitellogenin (Vtg) determination in biological samples as a biomarker for exogenous oestrogen compounds. Antibody against Vtg was produced in rabbits immunised with purified lipovitellin (Lpv), a precursor of Vtg, from the homogenised ovary of oriental fire-bellied toads (B. orientalis). The purified protein and Lpv/Vtg-specific serum were applied in both competitive and direct immunoassay formats using optical waveguide lightmode spectroscopy immunosensor. When measuring Vtg in direct manner, the Lpv antibody (1.76 µg mL−1) was immobilised on the sensor surface, and the linear measuring range for Vtg was 0.1–10 µg mL−1. During the competitive measurement, 100 ng mL−1 Lpv was applied for the immobilisation. The linear measuring range for Vtg was 0.5–50 ng mL−1. We studied the relative substrate specificity of the antibody, and it was concluded that the method is suitable for the sensitive and selective determination of Vtg levels in toads. Heart, liver and gonad samples from male animals were spiked with Vtg and were analysed using the newly developed method, and female toads and spawn samples were tested and compared to the calibration curve obtained by the spiked samples.

Human P-glycoprotein (P-gp) is an ATP-binding cassette multidrug transporter that confers resistance to a wide range of chemotherapeutic agents in cancer cells by active efflux of the drugs from cells. P-gp also plays a key role in limiting oral absorption and brain penetration and in facilitating biliary and renal elimination of structurally diverse drugs. Thus, identification of drugs or new molecular entities to be P-gp substrates is of vital importance for predicting the pharmacokinetics, efficacy, safety, or tissue levels of drugs or drug candidates. At present, publicly available, reliable in silico models predicting P-gp substrates are scarce. In this study, a support vector machine (SVM) method was developed to predict P-gp substrates and P-gp-substrate interactions, based on a training data set of 197 known P-gp substrates and non-substrates collected from the literature. We showed that the SVM method had a prediction accuracy of approximately 80% on an independent external validation data set of 32 compounds. A homology model of human P-gp based on the X-ray structure of mouse P-gp as a template has been constructed. We showed that molecular docking to the P-gp structures successfully predicted the geometry of P-gp-ligand complexes. Our SVM prediction and the molecular docking methods have been integrated into a free web server (http://pgp.althotas.com), which allows the users to predict whether a given compound is a P-gp substrate and how it binds to and interacts with P-gp. Utilization of such a web server may prove valuable for both rational drug design and screening.