Identity-Based Encryption from Lattices Using Approximate Trapdoors - GREYC amacc Access content directly
Conference Papers Year : 2023

Identity-Based Encryption from Lattices Using Approximate Trapdoors

Abstract

Unlabelled - Alzheimer's disease (AD) is a leading cause of dementia in elderly patients. The pathophysiology of AD includes various pathways, such as the degradation of acetylcholine, amyloid-beta deposition, neurofibrillary tangle formation, and neuroinflammation. Many studies showed that targeting acetylcholinesterase enzyme (AChE) to improve acetylcholine can be an effective option to treat AD. In the current work, we employed a 3D QSAR-based approach to generate a pharmacophore to screen a chemical library of compounds that may inhibit AChE. Data from experimental studies were collected and used for the generation of pharmacophores. More than 1 million compounds were screened, and further drug-like properties were determined via ADMET studies. Techniques like molecular docking and molecular dynamics simulation were performed to analyze the binding of novel AChE inhibitors. A novel AChE inhibitor ligand-1 was identified as best with a docking score of -13.560 kcal/mol with RMSD of 1.71 Å during a 100 ns MD run. Further biological studies can give an insight into the potential of ligand-1 as a therapeutic agent for AD. Supplementary information - The online version contains supplementary material available at 10.1007/s40203-024-00189-1.
Fichier principal
Vignette du fichier
Identity-Based_Encryption_from_Lattices_Using_Approximate_Trapdoors.pdf (662.34 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-04163136 , version 1 (17-07-2023)

Licence

Attribution

Identifiers

Cite

Malika Izabachène, Lucas Prabel, Adeline Roux-Langlois. Identity-Based Encryption from Lattices Using Approximate Trapdoors. ACISP 2023 - 28th Australasian Conference on Information Security and Privacy, Jul 2023, Brisbane, Australia. pp.270-290, ⟨10.1007/978-3-031-35486-1_13⟩. ⟨hal-04163136⟩
58 View
97 Download

Altmetric

Share

Gmail Facebook X LinkedIn More