Prof. Gerhard Ecker

Predicting drug-transporter interaction.
In the light of our contribution to the SFB35 ( we developed ligand- and structure-based models for ligands of the neurotransmitter transporters SERT, DAT, and NET as well as for the GABA transporters GAT1-4. In this project we aim at focusing on the molecular basis of ligand-transporter selectivity (both for SERT/DAT/NET and for GAT1-4) as well as to expand our studies to the L-Type amino acid transporter 1 (LAT-1). LAT-1 is a major nutrient transporter protein that is responsible for the transport of large neutral, aromatic or branched amino acids from extracellular fluids into the cells. LAT-1 plays an important role in cancer development as well as in mediating drug and nutrient delivery across the blood-brain barrier, making it a key drug target for development of novel anti-cancer agents. We will utilize an integrated approach of pharmacoinformatics and experimental validation to characterize and develop new potent ligands that inhibit LAT-1. Starting with ligand and structure based in silico approaches, the top ranked hit compounds obtained by virtual screening will be optimized by synthesizing and testing small compound libraries. All in silico models will be implemented in the Vienna Transporter Informatics Workspace. This project will be pursued in strong collaboration with the groups of Marko Mihovilovic, Gaia Novarino, and Harald Sitte.

The molecular basis of GABA-subtype Selectivity.
GABAA receptors constitute the major inhibitory neurotransmitter receptors in the brain. In our previous work, we established a protocol to elucidate the binding mode of benzodiazepines, proposed a new modulatory binding site on the α+/β- interface of GABAA receptors, and performed SAR and QSAR studies on a set of piperine analogs. The very recent X-ray structure of a GABAA receptor will allow to extend these studies on a set of new homology models. Furthermore, the labs of Mihovilovic and Maulide will synthesize new compound series (pyrazoloindolones, valerenic acid analogs), with new scaffolds, which will enlarge the chemical space of the ligands available for in silico model building and complement the large compound collection available in the Ernst lab. Specifically this thesis topic will focus on the selectivity profiling of selected compound series on GABAA receptor subtypes. The molecular basis of subtype selectivity will be elaborated by combining ligand-and structure-based design studies following our experimental data guided docking protocol. Briefly, SAR- and QSAR-studies will identify small sets of compounds which show distinct activity cliffs. Those will be used for docking into homology models, followed by common scaffold clustering and pose evaluation. Final binding hypotheses will be validated by synthesis of new compounds and/or studies of diagnostic mutations. This project will be pursued in strong collaboration with the groups of Margot Ernst, Marko Mihovilovic, and Steffen Hering.