Identification of potential inhibitors against Alzheimer-related proteins in Cordyceps militaris ethanol extract: experimental evidence and computational analyses

Abstract Laboratory experiments were carried out to identify the chemical composition of Cordyceps militaris and reveal the first evidence of their Alzheimer-related potential. Liquid chromatography–mass spectrometry analysis identified 21 bioactive compounds in the ethanol extract (1–21). High-performance liquid chromatography quantified the content of cordycepin (0.32%). Bioassays revealed the overall anti-Alzheimer potential of the extract against acetylcholinesterase ($ IC_{50} $ = 115.9 ± 11.16 µg $ mL^{−1} $). Multi-platform computations were utilized to predict the biological inhibitory effects of its phytochemical components against Alzheimer-related protein structures: acetylcholinesterase (PDB-4EY7) and β-amyloid protein (PDB-2LMN). In particular, 7 is considered as a most effective inhibitor predicted by its chemical stability in dipole-based environments (ground state − 467.26302 a.u.; dipole moment 11.598 Debye), inhibitory effectiveness (%$\overline{\mathrm{DS} }%$ − 13.6 kcal $ mol^{−1} $), polarized compatibility (polarizability 25.8 $ Å^{3} $; logP − 1.01), and brain penetrability (logBB − 0.244; logPS − 3.047). Besides, 3 is promising as a brain-penetrating agent (logBB − 0.257; logPS − 2.400). The results preliminarily suggest further experimental attempts to verify the pro-cognitive effects of l(−)-carnitine (7)..

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:13

Enthalten in:

3 Biotech - 13(2023), 9 vom: 04. Aug.

Sprache:

Englisch

Beteiligte Personen:

Thai, Nguyen Minh [VerfasserIn]
Dat, Ton That Huu [VerfasserIn]
Hai, Nguyen Thi Thanh [VerfasserIn]
Bui, Thanh Q. [VerfasserIn]
Phu, Nguyen Vinh [VerfasserIn]
Quy, Phan Tu [VerfasserIn]
Triet, Nguyen Thanh [VerfasserIn]
Pham, Duy Toan [VerfasserIn]
De Tran, Van [VerfasserIn]
Nhung, Nguyen Thi Ai [VerfasserIn]

Links:

Volltext [lizenzpflichtig]

Themen:

ADMET
Anti-Alzheimer
Density functional theory
Molecular docking simulation
QSARIS

Anmerkungen:

© King Abdulaziz City for Science and Technology 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

doi:

10.1007/s13205-023-03714-9

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

SPR052644472