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Updated: Jul 11, 2025

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
Published on: June 20, 2025
Predicting molecular docking of per- and polyfluoroalkyl substances to blood protein using generative artificial
Dhan Lord B Fortela1,2, Ashley P Mikolajczyk1,2, Miranda R Carnes1
1Department of Chemical Engineering, University of Louisiana, Lafayette, LA 70504, USA.
Abstract:
This study computationally evaluates the molecular docking affinity of various perfluoroalkyl and polyfluoroalkyl substances (PFAs) towards blood proteins using a generative machine-learning algorithm, DiffDock, specialized in protein-ligand blind-docking learning and prediction. Concerns about the chemical pathways and accumulation of PFAs in the environment and eventually in the human body has been rising due to empirical findings that levels of PFAs in human blood has been rising. DiffDock may offer a fast approach in determining the fate and potential molecular pathways of PFAs in human body.
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