Xingyu Chen

Supervisor: Anna Weinzinger, University of Vienna

Co-Supervisor: Thierry Langer, University of Vienna


Title of the project: In silico investigations of KATP-channels.

Finishing date: 11/2019


Research topic of the student: In my thesis, I study Cantú syndrome, a rare genetic disorder, which affects a small number of patients who suffer from multiple symptoms including hypertrichosis, lymphedema, distinctive facial features and cardiac abnormalities. Cantú syndrome is caused by dominant gain-of-function mutations in the ATP - dependent potassium channel formed by inward rectification potassium channel Kir6.1 and sulfonylurea receptors SUR2. There is currently no treatment for the Cantú syndrome available.

My research is focused on finding selective KATP channel blockers using in silicomethods. In my research, I used molecular dynamic simulation to firstly gain the structural and dynamical insights into the mechanisms of the Kir6.x channels and Cantú-related mutants (Cooper et al., 2017). Currently, combining with other computational methods, docking and pharmacophore modelling, I investigate the binding mode of Kir6 channel blockers. Using µs long MD simulations I have identified the binding site of rosiglitazone, a drug that as a side-effect blocks Kir6 channels. Later on, I developed a dynamic, structure based pharmacophore model and searched in DrugBank for novel potential Kir6.1 inhibitors. Functional tests in the lab of our international collaborator Marcel van der Heyden revealed already several promising novel inhibitors. The long-term vision of this project is to develop novel therapies for Cantú syndrome.


Lab Rotation (2 weeks): Host: Thierry Langer, Dept. of Pharmaceutical Chemistry, University of Vienna. Subject: Dynamic pharmacophore models based on rosiglitazone binding to Kir6.1 channel;  2017

Place after Graduation: PostDoc in the Group of Thomas Simonson, BIOS Research Group, BIO Computing and Structure, Biology Dept., École Polytechnique, Palaiseau, France.

 Abstract of the PhD thesis

 Alumni brochure contribution by Xingyu Chen