Yubo Li

Yubo Li


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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25 October 2024 in Journal of Ethnopharmacology
Verified
Journal Article
Closed access
PLPan Long
Pan Long
CGChao Guo
Chao Guo
TWTing Wen
Ting Wen
TLTao Luo
Tao Luo
LYLing Yang
Ling Yang
MHMengshan He
Mengshan He

27 May 2025 in International Immunopharmacology
Verified
Journal Article
Closed access
XWXudong Wen
Xudong Wen
FHFei Han
Fei Han
HZHengdi Zhang
Hengdi Zhang
TLTao Luo
Tao Luo
JJJun Jiang
Jun Jiang
PLPan Long
Pan Long

14 October 2026 in Frontiers in Physiology
Verified
Journal Article
Open access
PDF file
DLDefang Liu
Defang Liu
JYJiao Yan
Jiao Yan
TLTing Luo
Ting Luo
YGYu Guo
Yu Guo
YLYubo Li
Yubo Li
LYLing Yang
Ling Yang
Introduction: High-altitude (HA) illness threatens health after acute high-altitude exposure, but its molecular mechanisms and effective interventions remain unclear. Drug–food homologous (DFH) substances have potential for HA illness intervention, yet their active components and targets are unknown. Methods: Datasets related to HA illness, as well as 106 DFH substances and their corresponding chemical components, were obtained in this study. Differentially expressed genes were identified, and active components were screened according to the criteria of drug-likeness ≥0.18 and oral bioavailability ≥30%. The GraphBAN tool was used to predict high-confidence compound–protein interaction pairs, so as to obtain the corresponding candidate active components and candidate genes. Meanwhile, the ADMETlab3 platform was employed to evaluate the druggability and toxicity of these active components, thereby determining the core active components and core genes. Candidate genes were screened were screened out by machine learning, and relevant interaction networks were constructed. Finally, further studies such as pathway enrichment, immune infiltration, molecular docking, and molecular dynamics simulation were carried out. Results: Of the 95 candidate active components subjected to toxicological screening, only 8 passed the safety evaluation, and 6 of these met both physicochemical and toxicological criteria; five candidate genes (DNAJC19, MRFAP1L1, TBPL1, RPS21, and NABP1) and two key active components (polyacetylene PQ-2, PQ-2) were identified, and these candidate genes corresponded to the DFH substance “ Panacis Quinquefolii Radix ”. The abovementioned candidate genes were enriched in pathways such as ribosome and oxidative phosphorylation, and they were correlated with most differential immune cells. Except for RPS21 and MRFAP1L1, the binding abilities of the other candidate genes with the key active components were good (binding energies <−5.0 kcal/mol). Molecular dynamics simulation confirmed that the interaction of their binding was stable. Discussion: Panacis Quinquefolii Radix might intervene in HA illness via active components (PQ-2) that target five candidate genes, regulating immunity and metabolism. This provided a preliminary computational basis for DFH-based HA illness prevention/treatment.