Predicting molecular docking of per- and polyfluoroalkyl substances to blood protein using generative artificial intelligence algorithm DiffDock

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...

Full description

Saved in:

Bibliographic Details
Published in:	BioTechniques Vol. 76; no. 1; pp. 14 - 26
Main Authors:	B Fortela, Dhan Lord, Mikolajczyk, Ashley P, Carnes, Miranda R, Sharp, Wayne, Revellame, Emmanuel, Hernandez, Rafael, Holmes, William E, Zappi, Mark E
Format:	Journal Article
Language:	English
Published:	England Future Science Ltd 01.01.2024 Taylor & Francis Group
Subjects:	Algorithms Artificial Intelligence Blood Proteins Fluorocarbons generative artificial intelligence human health Humans molecular docking Molecular Docking Simulation per- and polyfluoroalkyl substances target-based screening molecular docking per- and polyfluoroalkyl substances blood proteins generative artificial intelligence human health target-based screening
ISSN:	0736-6205, 1940-9818, 1940-9818
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!