Structure-Based Identification of Natural Compounds as Potential RET-Kinase Inhibitors for Therapeutic Targeting of Neurodegenerative Diseases

BACKGROUND: Tyrosine-protein kinase receptor Ret (RET), a proto-oncogene, is considered as an attractive drug target for cancer and neurodegenerative diseases, including Alzheimer's disease (AD).

OBJECTIVE: We aimed to identify potential inhibitors of RET kinase among natural compounds present in the ZINC database.

METHODS: A multistep structure-based virtual screening approach was used to identify potential RET kinase inhibitors based on their binding affinities, docking scores, and interactions with the biologically important residues of RET kinase. To further validate the potential of these compounds as therapeutic leads, molecular dynamics (MD) simulations for 100 ns were carried out and subsequently evaluated the stability, conformational changes, and interaction mechanism of RET in-complex with the elucidated compounds.

RESULTS: Two natural compounds, ZINC02092851 and ZINC02726682, demonstrated high affinity, specificity for the ATP-binding pocket of RET and drug-likeness properties. The MD simulation outputs indicated that the binding of both compounds stabilizes the RET structure and leads to fewer conformational changes.

CONCLUSIONS: The findings suggest that ZINC02092851 and ZINC02726682 may be potential inhibitors for RET, offering valuable leads for drug development against RET-associated diseases. Our study provides a promising avenue for developing new therapeutic strategies against complex diseases, including AD. Identifying natural compounds with high affinity and specificity for RET provides a valuable starting point for developing novel drugs that could help combat these debilitating diseases.

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:95

Enthalten in:

Journal of Alzheimer's disease : JAD - 95(2023), 4 vom: 09., Seite 1519-1533

Sprache:

Englisch

Beteiligte Personen:

Hasan, Gulam Mustafa [VerfasserIn]
Shamsi, Anas [VerfasserIn]
Sohal, Sukhwinder Singh [VerfasserIn]
Alam, Manzar [VerfasserIn]
Hassan, Md Imtaiyaz [VerfasserIn]

Links:

Volltext

Themen:

Alzheimer’s disease
Computer-aided drug design
Journal Article
Molecular dynamics simulations
Natural compounds
Proto-oncogene tyrosine-protein kinase receptor Ret
Virtual screening

Anmerkungen:

Date Revised 16.10.2023

published: Print

Citation Status Publisher

doi:

10.3233/JAD-230698

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM362157723