<i>In-Silico</i> Screening-Based Discovery of New Natural eEF2K Inhibitors with Neuritogenic Activity

Eukaryotic elongation factor 2 kinase (eEF2K), an atypical Ser/Thr-protein kinase that regulates neuronal protein synthesis homeostasis via an inhibitory phosphorylation of eEF2, has emerged as a promising therapeutic target for several diseases, including Alzheimer's disease (AD). In this study, we employed molecular docking with an in-house natural product library of 4270 compounds, containing 2177 novel compounds and 603 new structural frameworks, to identify eEF2K inhibitors. Following virtual screening, 25 natural products were selected for <i>in-vitro</i> evaluation of eEF2 phosphorylation inhibition as well as protein synthesis promotion. Our findings identified that compounds <b>17</b> and <b>23</b> potently suppress eEF2K activity, increase protein synthesis, and concurrently induce neuritogenesis. Molecular dynamics simulations suggest that <b>17</b> and <b>23</b> may stably bind to the eEF2K protein. Our findings highlighted <b>17</b> and <b>23</b> as new natural eEF2K inhibitors and promising candidates for promoting neural differentiation, providing potential therapeutic leads for the treatment of AD.

Authors

Institutions

Publication Details

Journal
ACS Medicinal Chemistry Letters
Published
2025-03-04
DOI
https://doi.org/10.1021/acsmedchemlett.4c00635
Citations
2
Primary Topic
Click Chemistry and Applications
Type
article
Field-Weighted Citation Impact
1.87

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

In-Silico Screening-Based Discovery of New Natural eEF2K Inhibitors with Neuritogenic Activity

Lijun Hu, Shaobo Wang, Shiqing Zhang, Lei Shi et al.
2 citations
ACS Medicinal Chemistry Letters
Click Chemistry and Applications
1.87
article

In-Silico Screening-Based Discovery of New Natural eEF2K Inhibitors with Neuritogenic Activity

Lijun Hu, Shaobo Wang, Shiqing Zhang, Lei Shi, Wen‐Cai Ye, Lingling Guo, Ying Wang, Xinyu Wang, Xiaoqi Zhang, Xiao‐Jun Huang, Xiaoxia Chen
article en
2 citations

Abstract

Eukaryotic elongation factor 2 kinase (eEF2K), an atypical Ser/Thr-protein kinase that regulates neuronal protein synthesis homeostasis via an inhibitory phosphorylation of eEF2, has emerged as a promising therapeutic target for several diseases, including Alzheimer's disease (AD). In this study, we employed molecular docking with an in-house natural product library of 4270 compounds, containing 2177 novel compounds and 603 new structural frameworks, to identify eEF2K inhibitors. Following virtual screening, 25 natural products were selected for <i>in-vitro</i> evaluation of eEF2 phosphorylation inhibition as well as protein synthesis promotion. Our findings identified that compounds <b>17</b> and <b>23</b> potently suppress eEF2K activity, increase protein synthesis, and concurrently induce neuritogenesis. Molecular dynamics simulations suggest that <b>17</b> and <b>23</b> may stably bind to the eEF2K protein. Our findings highlighted <b>17</b> and <b>23</b> as new natural eEF2K inhibitors and promising candidates for promoting neural differentiation, providing potential therapeutic leads for the treatment of AD.

ACS Medicinal Chemistry LettersVol. 16(3)
Jinan University (CN)
National Natural Science Foundation of China, Jinan University, Guangzhou Municipal Science and Technology Project, National Key Research and Development Program of China, Science and Technology Planning Project of Guangdong Province, Basic and Applied Basic Research Foundation of Guangdong Province
Clean water and sanitation
Openalex Percentile: Top 17%
Click Chemistry and Applications
1.87
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.