Prediction of Drug-Target Interactions and Drug Repositioning via Network-Based Inference

Drug-target interaction (DTI) is the basis of drug discovery and design. It is time consuming and costly to determine DTI experimentally. Hence, it is necessary to develop computational methods for the prediction of potential DTI. Based on complex network theory, three supervised inference methods were developed here to predict DTI and used for drug repositioning, namely drug-based similarity inference (DBSI), target-based similarity inference (TBSI) and network-based inference (NBI). Among them, NBI performed best on four benchmark data sets. Then a drug-target network was created with NBI based on 12,483 FDA-approved and experimental drug-target binary links, and some new DTIs were further predicted. In vitro assays confirmed that five old drugs, namely montelukast, diclofenac, simvastatin, ketoconazole, and itraconazole, showed polypharmacological features on estrogen receptors or dipeptidyl peptidase-IV with half maximal inhibitory or effective concentration ranged from 0.2 to 10 µM. Moreover, simvastatin and ketoconazole showed potent antiproliferative activities on human MDA-MB-231 breast cancer cell line in MTT assays. The results indicated that these methods could be powerful tools in prediction of DTIs and drug repositioning

The Prolyl Isomerase Pin1 Acts Synergistically with CDK2 to Regulate the Basal Activity of Estrogen Receptor α in Breast Cancer

In hormone receptor-positive breast cancers, most tumors in the early stages of development depend on the activity of the estrogen receptor and its ligand, estradiol. Anti-estrogens, such as tamoxifen, have been used as the first line of therapy for over three decades due to the fact that they elicit cell cycle arrest. Unfortunately, after an initial period, most cells become resistant to hormonal therapy. Peptidylprolyl isomerase 1 (Pin1), a protein overexpressed in many tumor types including breast, has been demonstrated to modulate ERalpha activity and is involved in resistance to hormonal therapy. Here we show a new mechanism through which CDK2 drives an ERalpha-Pin1 interaction under hormone- and growth factor-free conditions. The PI3K/AKT pathway is necessary to activate CDK2, which phosphorylates ERalphaSer294, and mediates the binding between Pin1 and ERalpha. Site-directed mutagenesis demonstrated that ERalphaSer294 is essential for Pin1-ERalpha interaction and modulates ERalpha phosphorylation on Ser118 and Ser167, dimerization and activity. These results open up new drug treatment opportunities for breast cancer patients who are resistant to anti-estrogen therapy. © 2013 Lucchetti et al

Identifying salt stress-responsive transcripts from Roselle (Hibiscus sabdariffa L.) roots by differential display

No previous study has been reported on the salt-modulated gene(s) of roselle (Hibiscus sabdariffa L.). Identifying the potentially novel transcripts responsible for salt stress tolerance in roselle will increase knowledge of the molecular mechanism underlying salt stress responses. In this study, differential display reverse transcriptase PCR (DDRT-PCR) was used to compare the overall differences in gene expression between salt-stressed and control plants. A total of 81 primer combinations were used and false positive clones were rejected during a screening and quality control assay. The remaining nine cDNA transcript fragments were extracted from the gel, reamplified, cloned and sequenced. A homology search revealed that four transcripts showed significant homology with known genes. Out of five transcripts, real-time PCR demonstrated that four exhibited high expression in salt-stressed root tissues relative to the control and one transcript was down-regulated. These transcripts may be useful for improving tolerance in salt stress-sensitive plants.Keywords: Roselle, Hibiscus Sabdariffa L., differential display, salt-stress, differentially expressed transcripts, signal transduction.African Journal of Biotechnology, Vol 13(53) 4775-478