reproducible-computational-workflow-for-drug-discovery-to-standardize

Reproducible Computational Workflow for Drug Discovery to Standardize Network Pharmacology and Molecular Docking Analyses

Network pharmacology and molecular docking are widely applied in drug discovery, yet fragmented workflows and inconsistent operations frequently undermine ...

Beijing University of Chinese Medicine

Southern Medical University

 Our study focused on whether macrophages ferroptosis is associated with the pathogenesis of chronic obstructive pulmonary disease (COPD) or not.  We first identified macrophage module genes by weighted gene co-expression network analysis (WGCNA) in RNA sequencing (RNA-seq) date from COPD, and then identified macrophage marker genes by comprehensive analysis of single-cell RNA sequencing (scRNA-seq) data from COPD macrophages. There were 126 macrophage marker genes identified, and functional enrichment analyses indicated that ferroptosis pathway genes were significantly enriched. Secondly, we identified eight macrophage ferroptosis related genes and based on these eight genes, we performed co-expression analysis and drug prediction. Thirdly, two biomarkers (SOCS1 and HSPB1) were screened by the least absolute shrinkage and selection operator (LASSO), random forest (RF), and support vector machine-recursive feature elimination (SVM-RFE) and established an artificial neural network (ANN) for diagnosis. Subsequently, the biomarkers were validated in the dataset and validation set. These two biomarkers were then subjected to single gene-gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) analysis, and the ceRNA network was constructed. Finally, we carried out molecular validation with COPD models  for cell counting kit-8 (CCK8) experiments, Western blot and quantitative real-time PCR (qRT-PCR) analysis and transmission electron microscopy (TEM).  This study revealed the vital role of macrophage ferroptosis in COPD, and novel biomarkers (SOCS1 and HSPB1) may be involved in the pathogenesis of COPD by regulating macrophage ferroptosis.  Taken together, our results suggest that targeting SOCS1 and HSPB1 could treat COPD by inhibiting macrophage ferroptosis.

Integrating RNA-seq and scRNA-seq to explore the mechanism of macrophage ferroptosis associated with COPD.

Influenza viruses cause seasonal epidemics almost every year, and it is difficult to diagnose quickly and accurately. Machine learning and peripheral blood protein omics have brought new ideas to the research of clinical markers.

Prediction of influenza virus infection based on deep learning and peripheral blood proteomics: A diagnostic study.

COVID-19 has caused over 7 million deaths worldwide since its onset in 2019, and the virus remains a significant health threat. Identifying sensitive and specific biomarkers, along with elucidating immune-mediated mechanisms, is essential for improving the diagnosis, treatment, and prevention of COVID-19. To predict key molecular markers of COVID-19 using an established multi-omics framework combined with machine learning models.

Multi-omics and machine learning identify novel biomarkers and therapeutic targets of COVID-19.

Chronic inflammation within the tumor microenvironment (TME) is a critical driver of immune evasion, resistance to therapy, and progression of cancer, while epidemiological and immunological evidence indicates that allergic inflammation is also associated with the risk of several cancer types. Key pro-inflammatory cytokines: IL-6, IL-1β, TNF-α, and TGF-β activate key signaling pathways such as STAT3, NF-κB, and HIF-1α which create a self-amplifying cycle fostering angiogenesis, epithelial–mesenchymal transition, and immunosuppression. The accumulation of regulatory T cells, myeloid-derived suppressor cells, and tumor-associated macrophages additionally promotes an immunologically “cold” TME limiting the efficacy of immune checkpoint blockade, chemotherapy, and radiotherapy. Recent advances have elucidated on how inflammatory signaling dynamically changes cellular and metabolic states fostering resistance. Targeting these inflammatory signaling axes has demonstrated promising therapeutic efficacy: IL-6R and IL-1β neutralization, JAK/STAT3 and NF-κB inhibition, TGF-β blockade, and CXCR2 targeted strategies all have demonstrated the ability to restore anti-tumor immunity. Rationally designed combination therapies utilizing cytokine inhibition in combination with checkpoint blockades or anti-angiogenic agents are beginning to convert refractory tumors to responsive tumors. Herein we review mechanistic insights linking chronic inflammation to immunosuppression and treatment failure across multiple cancer types and discuss the translational promise of inflammation-targeted treatments. Targeting the TME through multi-variate inhibition of inflammatory pathways may be able to allow durable therapeutic responses to be achieved in tumors previously resistant to conventional and immune-based therapies.

Article	Year
Integrating RNA-seq and scRNA-seq to explore the mechanism of macrophage ferroptosis associated with COPD. Frontiers in pharmacology\| PubMed ID: 36969832	2023
Prediction of influenza virus infection based on deep learning and peripheral blood proteomics: A diagnostic study. Journal of advanced research\| PubMed ID: 40158620	2026
Multi-omics and machine learning identify novel biomarkers and therapeutic targets of COVID-19. Frontiers in immunology\| PubMed ID: 41112249	2025
Targeting inflammatory microenvironments: overcoming therapy resistance and immunosuppression. Molecular cancer\| PubMed ID: 41703602	2026

Pengbei Fan

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