Mechanism Research of Platelet Core Marker Prediction and Molecular
Recognition in Cardiovascular Events

Hongdan      Wang; Bingyu      Zhang; Xianhua      Zhong; Dui      Qin; Zhangyong      Li

doi:10.2174/1386207325666220328091748

Abstract

Background: Thrombosis triggered by platelet activation plays a vital role in the pathogenesis of cardiovascular and cerebrovascular diseases.

Objective: This study aims to find platelet combined biomarkers for cardiovascular diseases and investigate the possibility of Concanavalin A (ConA) acting on platelets as a new pharmacological target.

Methods: High-throughput Technology and bioinformatics analysis were combined and groups of microarray chip gene expression profiles for acute myocardial infarction (AMI) and sickle cell disease (SCD) were obtained using GEO database screening. R language limma package was used to obtain differentially expressed genes (DEGs). GO, KEGG, and other databases were utilized to perform the enrichment analysis of DEGs’ functions, pathways, etc. PPI network was constructed using STRING database and Cytoscape software, and MCC algorithm was used to obtain the 200 core genes of the two groups of DEGs. Core targets were confirmed by constructing an intersection area screening. A type of molecular probe, ConA, was molecularly docked with the above core targets on the Zdock, HEX, and 3D-DOCK servers.

Results: We found six core markers, CD34, SOCS2, ABL1, MTOR, VEGFA, and SMURF1, which were simultaneously related to both diseases, and the docking effect showed that VEGFA is the best-performing.

Conclusion: VEGFA is most likely to reduce its expression by binding to ConA, which could affect the downstream regulation of the PI3K/Akt signaling pathway during platelet activation. Some other core targets also have the opportunity to interact with ConA to affect platelet-activated thrombosis and trigger changes in cardiovascular events.

Keywords: Cardiovascular diseases, platelet activation, gene regulation, enrichment analysis, molecular docking, sickle cell disease.

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Graphical Abstract

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DOI https://dx.doi.org/10.2174/1386207325666220328091748	Print ISSN 1386-2073
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Combinatorial Chemistry & High Throughput Screening

Mechanism Research of Platelet Core Marker Prediction and Molecular Recognition in Cardiovascular Events

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