Comparative Analysis of Virtual Screening Approaches in the Search for Novel EphA2 Receptor Antagonists

Towards an Enrichment Optimization Algorithm (EOA)-based Target Specific Docking Functions for Virtual Screening

Docking-based virtual screening (VS) is a common starting point in many drug discovery projects. While ligand-based approaches may sometimes provide better results, the advantage of docking lies in its ability to provide reliable ligand binding modes and approximated binding free energies, two factors that are important for hit selection and optimization. Most docking programs were developed to be as general as possible and consequently their performances on specific targets may be sub-optimal. With this in mind, in this work we present a method for the development of target-specific scoring functions using our recently reported Enrichment Optimization Algorithm (EOA). EOA derives QSAR models in the form of multiple linear regression (MLR) equations by optimizing an enrichment-like metric. Since EOA requires target-specific active and inactive (or decoy) compounds, we retrieved such data for six targets from the DUD-E database, and used them to re-derive the weights associated with the components that make up GOLD's ChemPLP scoring function yielding target-specific, modified functions. We then used the original ChemPLP function in small-scale VS experiments on the six targets and subsequently rescored the resulting poses with the modified functions. In addition, we used the modified functions for compounds re-docking. We found that in many although not all cases, either rescoring the original ChemPLP poses or repeating the entire docking process with the modified functions, yielded better results in terms of AUC and EF_1% , two metrics, common for the evaluation of VS performances. While work on additional datasets and docking tools is clearly required, we propose that the results obtained thus far hint to the potential benefits in using EOA-based optimization for the derivation of target-specific functions in the context of virtual screening. To this end, we discuss the downsides of the methods and how it could be improved.

MicroRNA-26b Enhances the Radiosensitivity of Hepatocellular Carcinoma Cells by Targeting EphA2

Sensitizing hepatocellular carcinoma (HCC) cells to irradiation is important to achieve satisfactory therapeutic effect with low-dose radiotherapy. Erythropoietin-producing hepatocellular carcinoma A2 (EphA2) is a member of the Eph receptor family that constitutes the largest family of tyrosine kinase receptors. EphA2 overexpression is one of the poor prognostic factors in many progressive cancers. Importantly, EphA2 is a potential target of microRNA-26b (miR-26b), and miR-26b expression is down-regulated in several types of cancer. In this study, we measured the expression levels of miR-26b and EphA2 protein in seven human HCC cell lines by quantitative PCR and western blot analysis, respectively. Overall, lower miR-26b expression levels tended to be associated with higher EphA2 levels in HCC cell lines. Among the cell lines examined, 97H HCC cells expressed the lowest level of miR-26b and highest level of EphA2 protein. Thus, using 97H HCC cells, EphA2 mRNA was verified as the target of miR-26b by the luciferase reporter assay. Accordingly, a synthetic miR-26b, miR-26b mimics, was used to mimic the function of endogenous miR-26b. In 97H HCC cells transfected with miR-26b mimics or short-hairpin RNA targeting EphA2 mRNA, expression of EphA2 protein was reduced, which was associated with significantly lower proliferation rate and invasion ability and with higher apoptosis rate in response to low-dose irradiation, compared to control cells. In contrast, 97H HCC cells over-expressing EphA2 showed higher proliferation rate and invasion ability and lower apoptosis rate upon irradiation. These data suggest that miR-26b enhances the radiosensitivity of 97H HCC cells by targeting EphA2 protein.