Drug Discovery and Repurposing Inhibits a Major Gut Pathogen-Derived Oncogenic Toxin.

Objective: The human intestinal microbiome plays an important role in inflammatory bowel disease (IBD) and colorectal cancer (CRC) development. One of the first discovered bacterial mediators involves Bacteroides fragilis toxin (BFT, also named as fragilysin), a metalloprotease encoded by enterotoxigenic Bacteroides fragilis (ETBF) that causes barrier disruption and inflammation of the colon, leads to tumorigenesis in susceptible mice, and is enriched in the mucosa of IBD and CRC patients. Thus, targeted inhibition of BFT may benefit ETBF carrying patients. Design: By applying two complementary in silico drug design techniques, drug repositioning and molecular docking, we predicted potential BFT inhibitory compounds. Top candidates were tested in vitro on the CRC epithelial cell line HT29/c1 for their potential to inhibit key aspects of BFT activity, being epithelial morphology changes, E-cadherin cleavage (a marker for barrier function) and increased IL-8 secretion. Results: The primary bile acid and existing drug chenodeoxycholic acid (CDCA), currently used for treating gallstones, cerebrotendinous xanthomatosis, and constipation, was found to significantly inhibit all evaluated cell responses to BFT exposure. The inhibition of BFT resulted from a direct interaction between CDCA and BFT, as confirmed by an increase in the melting temperature of the BFT protein in the presence of CDCA. Conclusion: Together, our results show the potential of in silico drug discovery to combat harmful human and microbiome-derived proteins and more specifically suggests a potential for retargeting CDCA to inhibit the pro-oncogenic toxin BFT.

Highlights from the ISCB Student Council Symposia in 2016.

This editorial provides a brief overview of the 12th International Society for Computational Biology (ISCB) Student Council Symposium and the 4th European Student Council Symposium held in Florida, USA and The Hague, Netherlands, respectively. Further, the role of the ISCB Student Council in promoting education and networking in the field of computational biology is also highlighted.

Highlights from the Third International Society for Computational Biology (ISCB) European Student Council Symposium 2014.

In this meeting report, we give an overview of the talks, presentations and posters presented at the third European Symposium of the International Society for Computational Biology (ISCB) Student Council. The event was organized as a satellite meeting of the 13th European Conference for Computational Biology (ECCB) and took place in Strasbourg, France on September 6th, 2014.

In silico identification and in vitro validation of potential cholestatic compounds through 3D ligand-based pharmacophore modeling of BSEP inhibitors.

Drug-induced cholestasis is a frequently observed side effect of drugs and is often caused by an unexpected interaction with the bile salt export pump (BSEP/ABCB11). BSEP is the key membrane transporter responsible for the transport of bile acids from hepatocytes into bile. Here, we developed a pharmacophore model that describes the molecular features of compounds associated with BSEP inhibitory activity. To generate input and validation data sets, in vitro experiments with membrane vesicles overexpressing human BSEP were used to assess the effect of compounds (50 µM) on BSEP-mediated (3)H-taurocholic acid transport. The model contains two hydrogen bond acceptor/anionic features, two hydrogen bond acceptor vector features, four hydrophobic/aromatic features, and exclusion volumes. The pharmacophore was validated against a set of 59 compounds, including registered drugs. The model recognized 9 out of 12 inhibitors (75%), which could not be identified based on general parameters, such as molecular weight or SlogP, alone. Finally, the model was used to screen a virtual compound database. A number of compounds found via virtual screening were tested and displayed statistically significant BSEP inhibition, ranging from 13 ± 1% to 67 ± 7% of control (P < 0.05). In conclusion, we developed and validated a pharmacophore model that describes molecular features found in BSEP inhibitors. The model may be used as an in silico screening tool to identify potentially harmful drug candidates at an early stage in drug development.