System level modeling and analysis of TNF- α mediated sphingolipid signaling pathway in neurological disorders for the prediction of therapeutic targets

Sanam Banaras; Rehan Zafar Paracha; Maryum Nisar; Ayesha Arif; Jamil Ahmad; Muhammad Tariq Saeed; Zartasha Mustansar; Malik Nawaz Shuja; Rizwan Nasir Paracha

doi:10.3389/fphys.2022.872421

System level modeling and analysis of TNF- α mediated sphingolipid signaling pathway in neurological disorders for the prediction of therapeutic targets

Front Physiol. 2022 Aug 19:13:872421. doi: 10.3389/fphys.2022.872421. eCollection 2022.

Authors

Sanam Banaras¹, Rehan Zafar Paracha¹, Maryum Nisar¹, Ayesha Arif¹, Jamil Ahmad², Muhammad Tariq Saeed¹, Zartasha Mustansar¹, Malik Nawaz Shuja³, Rizwan Nasir Paracha⁴

Affiliations

¹ School of Interdisciplinary Engineering and Sciences (SINES), National University of Sciences and Technology (NUST), Islamabad, Pakistan.
² Computer Science and Information Technology (CS&IT), University of Malakand, Chakdara, Pakistan.
³ Kohat University of Science and Technology, Kohat, Pakistan.
⁴ Department of Chemistry, University of Sargodha, Sub Campus Bhakkar, Bhakkar, Pakistan.

Abstract

Sphingomyelin (SM) belongs to a class of lipids termed sphingolipids. The disruption in the sphingomyelin signaling pathway is associated with various neurodegenerative disorders. TNF-α, a potent pro-inflammatory cytokine generated in response to various neurological disorders like Alzheimer's disease (AD), Parkinson's disease (PD), and Multiple Sclerosis (MS), is an eminent regulator of the sphingomyelin metabolic pathway. The immune-triggered regulation of the sphingomyelin metabolic pathway via TNF-α constitutes the sphingomyelin signaling pathway. In this pathway, sphingomyelin and its downstream sphingolipids activate various signaling cascades like PI3K/AKT and MAPK/ERK pathways, thus, controlling diverse processes coupled with neuronal viability, survival, and death. The holistic analysis of the immune-triggered sphingomyelin signaling pathway is imperative to make necessary predictions about its pivotal components and for the formulation of disease-related therapeutics. The current work offers a comprehensive in silico systems analysis of TNF-α mediated sphingomyelin and downstream signaling cascades via a model-based quantitative approach. We incorporated the intensity values of genes from the microarray data of control individuals from the AD study in the input entities of the pathway model. Computational modeling and simulation of the inflammatory pathway enabled the comprehensive study of the system dynamics. Network and sensitivity analysis of the model unveiled essential interaction parameters and entities during neuroinflammation. Scanning of the key entities and parameters allowed us to determine their ultimate impact on neuronal apoptosis and survival. Moreover, the efficacy and potency of the FDA-approved drugs, namely Etanercept, Nivocasan, and Scyphostatin allowed us to study the model's response towards inhibition of the respective proteins/enzymes. The network analysis revealed the pivotal model entities with high betweenness and closeness centrality values including recruit FADD, TNFR_TRADD, act CASP2, actCASP8, actCASP3 and 9, cytochrome C, and RIP_RAIDD which profoundly impacted the neuronal apoptosis. Whereas some of the entities with high betweenness and closeness centrality values like Gi-coupled receptor, actS1PR, Sphingosine, S1P, actAKT, and actERK produced a high influence on neuronal survival. However, the current study inferred the dual role of ceramide, both on neuronal survival and apoptosis. Moreover, the drug Nivocasan effectively reduces neuronal apoptosis via its inhibitory mechanism on the caspases.

Keywords: TNF-α; drug repurposing; microglia; network analysis; neurological disorders; neurons; quantitative analysis; sphingomyelin.