In Silico drug repurposing pipeline using deep learning and structure based approaches in epilepsy.

Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE

Original Publication: London : Nature Publishing Group, copyright 2011-

Drug Repositioning*/methods ; Epilepsy*/drug therapy ; Epilepsy*/genetics ; Deep Learning* ; Anticonvulsants*/therapeutic use ; Anticonvulsants*/pharmacology ; Anticonvulsants*/chemistry ; Molecular Dynamics Simulation*; Humans ; Computer Simulation

Due to considerable global prevalence and high recurrence rate, the pursuit of effective new medication for epilepsy treatment remains an urgent and significant challenge. Drug repurposing emerges as a cost-effective and efficient strategy to combat this disorder. This study leverages the transformer-based deep learning methods coupled with molecular binding affinity calculation to develop a novel in-silico drug repurposing pipeline for epilepsy. The number of candidate inhibitors against 24 target proteins encoded by gain-of-function genes implicated in epileptogenesis ranged from zero to several hundreds. Our pipeline has repurposed the medications with most anti-epileptic drugs and nearly half psychiatric medications, highlighting the effectiveness of our pipeline. Furthermore, Lomitapide, a cholesterol-lowering drug, first emerged as particularly noteworthy, exhibiting high binding affinity for 10 targets and verified by molecular dynamics simulation and mechanism analysis. These findings provided a novel perspective on therapeutic strategies for other central nervous system disease.
(© 2024. The Author(s).)

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Keywords: BBB (blood–brain barrier) permeability; Deep learning; Docking; Drug repurposing; Epilepsy; Gain-of-function gene

0 (Anticonvulsants)

Date Created: 20240717 Date Completed: 20240717 Latest Revision: 20240802

20240802

PMC11254927

10.1038/s41598-024-67594-6

39020064