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Abstract: FR-PO010

In Silico Drug Repurposing of Aquaporin 1

Session Information

Category: Augmented Intelligence, Digital Health, and Data Science

  • 300 Augmented Intelligence, Digital Health, and Data Science


  • Lloyd, Aled Rhys, Swansea University, Swansea, United Kingdom
  • Austin-Muttitt, Karl, Swansea University, Swansea, United Kingdom
  • Mullins, Jonathan G L, Swansea University, Swansea, United Kingdom

Group or Team Name

  • Genome and Structural Bioinformatics Group, Swansea University Medical School.

Drug repurposing is the identification of new therapeutic targets for existing licensed medicinal compounds. We have developed protocols and programs for an in silico high-throughput repurposing screen using structural modelling, docking, and molecular dynamics (MD). Uniquely our approach uses a bespoke interface on Google Colab for graphic processing units (GPU’s) to run the MD simulations. We describe its application to human aquaporin 1 (AQP1).


The library of British National Formulary listed compounds was obtained from NCBI PubChem. I-TASSER was used to generate monomeric structural models and Modeller for assembling oligomers. PLANTS was used for docking simulations. CHARM-GUI and bespoke software were used to prepare membrane-bound systems to run in GROMACS using GPU’s in Google Colab. 20 nanosecond simulations were undertaken (300 Kelvin and 1 bar) to discriminate between binding and non-binding events.


Complete monomeric and tetrameric structural models of human AQP1 were obtained incorporating chains of water molecules traversing the pores. Docking studies of 1002 drug compounds at the cytoplasmic opening of AQP1 identified 200 compounds binding in the pore. 45 compounds exhibited a higher calculated binding energy higher than the known binder furosemide and underwent further testing using MD. The 20 nanosecond MD simulations distinguished the compounds which were not binding and elucidated the dynamics of the binders. A noteworthy finding was that furosemide induced a conformational change in the cytoplasmic chain.


We have developed a robust docking-MD protocol for high throughput repurposing screening. We have demonstrated that shorter simulations than previously published can reliably detect active binding conformations and identify compounds that could interact with human AQP1. Several commonly used medications exhibited stable interactions including furosemide, gabapentin, pregabalin, pravastatin and esmolol.