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Updated: Jun 3, 2025

Sample Preparation using a Lipid Monolayer Method for Electron Crystallographic Studies
Published on: November 20, 2021
In silico drug repurposing at the cytoplasmic surface of human aquaporin 1
Aled R Lloyd1, Karl Austin-Muttitt1, Jonathan G L Mullins1
1Genome and Structural Bioinformatics Group, Faculty of Medicine, Health and Life Science, Swansea University, Swansea, Wales, United Kingdom.
Abstract:
Aquaporin 1 (AQP1) is a key channel for water transport in peritoneal dialysis. Inhibition of AQP1 could therefore impair water transport during peritoneal dialysis. It is not known whether inhibition of AQP1 occurs unintentionally due to off-target interactions of administered medications. A high-throughput virtual screening study has been performed to investigate the possible binding of licensed medications to the water pore of human AQP1. A complete model of human AQP1 based on its canonical sequence was assembled using I-TASSER and MODELLER. The model was refined via the incorporation of pore water molecules from a high-resolution yeast aquaporin structure. Docking studies were conducted for the cytoplasmic domain of the AQP1 monomer against a library of all compounds listed in the British National Formulary (BNF), using the PLANTS software with the ChemPLP scoring function. The stability of the best docked conformations within the intrinsic water pore was assessed via short 15 nanosecond molecular dynamics (MD) simulations using the GROMACS-on-Colab utility. Of the 1512 compounds tested, 1002 docking results were obtained, and 198 of these conformations occupied a position within the intrinsic water pore. 30 compounds with promising docking scores were assessed by MD. The docked conformations for dopamine, gabapentin, pregabalin, and methyldopa were stable in these short MD studies. For furosemide and pravastatin, the MD trajectory suggested a binding mode different to the docking result. A small set of compounds which could impede water transport through human AQP1 have been identified in this computational screening study.
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