Computer-assisted discovery and evaluation of potential ribosomal protein S6 kinase beta 2 inhibitors.

Molecular dynamics simulation Protein model prediction Ribosomal protein S6 kinase beta 2 Virtual screening mTOR signaling pathway

Journal

Computers in biology and medicine
ISSN: 1879-0534
Titre abrégé: Comput Biol Med
Pays: United States
ID NLM: 1250250

Informations de publication

Date de publication:
06 Mar 2024
Historique:
received: 23 11 2023
revised: 11 02 2024
accepted: 19 02 2024
medline: 15 3 2024
pubmed: 15 3 2024
entrez: 14 3 2024
Statut: aheadofprint

Résumé

S6K2 is an important protein in mTOR signaling pathway and cancer. To identify potential S6K2 inhibitors for mTOR pathway treatment, a virtual screening of 1,575,957 active molecules was performed using PLANET, AutoDock GPU, and AutoDock Vina, with their classification abilities compared. The MM/PB(GB)SA method was used to identify four compounds with the strongest binding energies. These compounds were further investigated using molecular dynamics (MD) simulations to understand the properties of the S6K2/ligand complex. Due to a lack of available 3D structures of S6K2, OmegaFold served as a reliable 3D predictive model with higher evaluation scores in SAVES v6.0 than AlphaFold, AlphaFold2, and RoseTTAFold2. The 150 ns MD simulation revealed that the S6K2 structure in aqueous solvation experienced compression during conformational relaxation and encountered potential energy traps of about 19.6 kJ mol

Identifiants

pubmed: 38484695
pii: S0010-4825(24)00288-9
doi: 10.1016/j.compbiomed.2024.108204
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

108204

Informations de copyright

Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Fangyi Yu (F)

Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310009, China.

Xiaochuan Wu (X)

Institute of Pharmaceutics, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.

WeiSong Chen (W)

Department of Respiratory Medicine, Jinhua Municipal Central Hospital, Jinhua, Zhejiang, 321000, China.

Fugui Yan (F)

Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310009, China.

Wen Li (W)

Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310009, China. Electronic address: liwen@zju.edu.cn.

Classifications MeSH