Abstract: SA-OR056
Computational Analysis of Inhibitor Binding in SGLT2 Variants
Session Information
- Kidney Disease with Diabetes: Translational Science Breakthroughs
November 08, 2025 | Location: Room 372A, Convention Center
Abstract Time: 04:40 PM - 04:50 PM
Category: Diabetic Kidney Disease
- 701 Diabetic Kidney Disease: Basic
Authors
- Lloyd, Aled Rhys, Swansea University, Swansea, Wales, United Kingdom
- Austin-Muttitt, Karl, Swansea University, Swansea, Wales, United Kingdom
- Mullins, Jonathan G L, Swansea University, Swansea, Wales, United Kingdom
Group or Team Name
- Genome & Structural Bioinformatics Group.
Background
Genetic polymorphisms of SGLT2 near the binding site could affect SGLT2 inhibitor binding. Information on the binding of flozin compounds with single nucleotide polymorphisms (SNPs) is sparse. We investigated the binding pattern of SNPs near the inhibitor binding site of SGLT2 using structural bioinformatics approaches.
Methods
Wild type (WT) and variant structural models of the SGLT2-MAP17 complex were created using a combination D-I-TASSER and homology modelling. These models underwent a 5 nanosecond molecular dynamics (MD) relaxation simulation with a reference ligand using the GROMACS-on-Colab utility prior to membrane-bound docking studies using PLANTS PLP software. Variant and WT docked conformations were compared using DockRMSD. The stability of variant docking results with a DockRMSD below 3Å was assessed using three MD simulations of 10 nanoseconds duration.
Results
Eleven SNPs affecting residues within 5Å of the position of empagliflozin in a reference structure were identified on the UniProt database. The docking results obtained for the variants E99Δ, E99G and T87A were substantially different to wild type docked conformations with all SGLT2 inhibitors investigated. The binding of dapagliflozin and empagliflozin was different to the WT with E99FS, while the binding of dapagliflozin and canagliflozin were different to the wild type in the F98L and Q457H models. The behaviour 10 variant-ligand combinations were assessed using MD, however only S286L with dapagliflozin proved to be unstable.
Conclusion
SGLT2 SNPs where inhibitor binding could be different to the WT have been identified in this computational study. There is a paucity of clinical data on both the frequency of SGLT2 variants and the effectiveness of SGLT2 inhibitors in variants. Given the extensive use of SGLT2i in the fields of diabetes, nephrology and cardiology the suggestion that these drugs may be less effective in some individuals warrants investigation.
SGLT2-MAP17 complex with empagliflozin (green) from PDB 7VSI. Key residues for binding are highlighted in orange.