Evidence map›Paper›PMID 42741578›Full record

ArticleTobacco induced diseases2026

Impact of cigarette toxicants on sarcopenic obesity: An in silico network toxicology and molecular dynamics study.

Zijing Li, Daoyuan Li, Yuli Huang, Yushang Liu, Xinye Ouyang, Yufei Xu, Wenjuan Wu, Yanbiao Zhong, Maoyuan Wang

Abstract read
In one paragraph

Article in Tobacco induced diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Zijing Li *Department of Rehabilitation Medicine, First Affiliated Hospital of Gannan Medical University, Ganzhou City, China.
Daoyuan Li *School of Rehabilitation and Sports Health, Gannan Medical University, Ganzhou City, China.
Yuli Huang *Department of Rehabilitation Medicine, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou City, China.
Yushang LiuDepartment of Rehabilitation Medicine, First Affiliated Hospital of Gannan Medical University, Ganzhou City, China.
Xinye OuyangThe First Clinical Medical College, Gannan Medical University, Ganzhou City, China.
Yufei XuSchool of Rehabilitation and Sports Health, Gannan Medical University, Ganzhou City, China.
Wenjuan WuThe First Clinical Medical College, Gannan Medical University, Ganzhou City, China.
Yanbiao ZhongDepartment of Rehabilitation Medicine, First Affiliated Hospital of Gannan Medical University, Ganzhou City, China.
Maoyuan WangDepartment of Rehabilitation Medicine, First Affiliated Hospital of Gannan Medical University, Ganzhou City, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSarcopenic obesity (SO) is a geriatric metabolic syndrome characterized by muscle mass loss, muscle strength decline, and excessive fat accumulation. Nicotine and coal tar disrupt skeletal muscle homeostasis and lipid metabolism. This study aims to elucidate the relevant molecular mechanisms by which nicotine and coal tar trigger sarcopenic obesity using an integrated in silico approach.

methodsThis in silico study was conducted in May 2026 using publicly available databases and computational platforms. Targets for nicotine, coal tar, and SO were retrieved from GeneCards and OMIM, and the intersection of targets was identified using Venny. KEGG enrichment was performed to detect key pathways. A protein-protein interaction (PPI) network was constructed via STRING, and the top 10 core genes were ranked by the Maximal Clique Centrality (MCC) algorithm in Cytoscape. Three GEO transcriptomic datasets (GSE290570, GSE262419, GSE226045) were used to cross-validate differentially expressed genes related to nicotine, coal tar, and SO. Molecular docking between nicotine and five core proteins was performed using CB-DOCK2, and 50 ns molecular dynamics simulations with GROMACS were used to assess complex stability via root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), solvent-accessible surface area (SASA), and hydrogen-bond analysis.

resultsTwenty intersection targets were identified. Enriched pathways included MAPK, PI3K/Akt, p53, cholesterol metabolism, and ferroptosis. Five core genes (IL1β, IGF1, FGF2, CTNNB1, and CXCL12) were cross-validated by GEO transcriptomic data. Nicotine bound stably to CTNNB1, CXCL12, IGF1, and IL1β with binding energies ranging from -3.3 to -4.2 kcal/mol, whereas FGF2 showed a positive value (0.7). MD simulations confirmed that all complexes maintained structural stability throughout the 50 ns trajectory.

conclusionsNicotine and coal tar may regulate core genes and inflammation- and metabolism-related pathways to promote SO progression. This study provides theoretical references for preventing tobacco exposure-induced SO.

Indexed as

coal tarmolecular dockingmolecular dynamics simulationnicotinesarcopenia obesity

Identifiers

PMID42741578
PMCPMC13572993

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.