Abstract by Julian Philipp Storm

The sodium-coupled neutral amino acid transporters 1 and 3 (SNAT1 and SNAT3) of the Solute Carrier (SLC)38 family mediate transport of neutral amino acids across cellular membranes. SNAT1 and SNAT3 are classified into different transport systems, namely system A (SNAT1) and system N (SNAT3), which are distinguished by substrate profiles and differences in transport-ion coupling. Their preferred substrate is glutamine, the most abundant amino acid in human plasma and a pivotal metabolite for diverse cellular processes, including the synthesis of neurotransmitters, lipids, nucleotides, and proteins. Many tumors develop glutamine addiction to sustain elevated metabolism and rapid proliferation. Consequently, cancer cells rely on glutamine transport pathways, and SNAT1 and SNAT3 are reported to be upregulated in several cancers. Inhibition of SNATs could therefore reduce glutamine supply to tumor cells, providing a pharmacological approach. However, targeting these transporters is challenging due to a lack of high-resolution structural data and a limited understanding of their transport mechanisms.

In this thesis, we solved high-resolution cryogenic electron microscopy (cryo-EM) structures of SNAT1 in glutamine-bound, substrate-analogue-bound, and substrate-free states, and of SNAT3 in a glutamine-bound state. We complemented the structural work with functional characterization, including mutational mapping of the binding pocket using glutamine uptake and electrophysiology, thereby identifying key residues involved in substrate coordination and mechanistic differences between system A and system N transport. In the second part of the thesis, we used this structural and functional framework to build a structure-guided drug discovery pipeline targeting SNAT1. Using machine-learning-based virtual screening of ultra-large chemical spaces, re-docking into hydration-state-dependent SNAT1 grids, and clustering of prioritized hits by chemical similarity and protein–ligand interaction fingerprints, we identified and selected a chemically diverse set of candidate compounds for experimental validation. Together, this work provides a structural framework for understanding system A versus system N coupling and enables structure-guided inhibitor discovery.