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Description

Purpose:

The purpose of this study is to investigate the intricate relationship between periodontal disease (PD) and coronary artery disease (CAD), as evidenced by epidemiological associations. Metalloproteinase inhibitor (TIMP1) plays a pivotal role in cellular signaling, differentiation, cell death, and migration by binding to target metalloproteinases, forming complexes with other molecules (collagenases) to inactivate them. However, the expression of TIMP1 is reduced in both PD and CAD, leading to an upregulation of other metalloproteinases. This research explores the hypothesis that metabolites released from (Porphyromonas gingivalis), a prevalent bacterium in atherosclerotic patients, may inhibit TIMP1, thereby influencing CAD progression.

Methods:

This research utilized a series of computational techniques, encompassing data mining, protein network analysis, molecular modeling, molecular docking, and molecular dynamics simulation. In the initial phase, metabolites from Porphyromonas gingivalis were retrieved from the Virtual Metabolic Human (VMH) database. The proteins associated with the TIMP1 were identified through the construction of a protein interaction network in Cytoscape. Subsequently, the TIMP1 underwent modeling using the Swiss-Model web server and was docked with bacterial metabolites. Furthermore, the structural stability of both the protein and metabolite was evaluated over a 100 ns simulation period.

Results:

In total, 370 metabolites from Porphyromonas gingivalis were obtained from the database. Notably, the network analysis revealed that MMP1, MMP9, and MMP14 were closely associated with TIMP1. Molecular docking outcomes demonstrated that Malonyl CoA displayed a binding affinity of -8.82 kcal/mol at the active sites of TIMP1. Additionally, a stable complex between TIMP1 and Malonyl CoA was observed throughout the simulation period, potentially influencing the activity of TIMP1.

Conclusion:

This investigation underscores the potential implications of Porphyromonas gingivalis metabolites as a risk factor in the development of CAD. The computational analysis suggests that these metabolites may disrupt the function of TIMP1, thereby contributing to the elevated levels of metalloproteinases observed in CAD patients. This emphasizes the critical need for further research to delve into the intricate mechanisms and exploring potential therapeutic interventions.

Disciplines

Bacteriology | Bioinformatics | Biotechnology | Cardiovascular Diseases | Periodontics and Periodontology

Document Type

Event

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Interplay of Periodontal Bacterial Metabolites in the Progression of Coronary Artery Disease: A System Biological Approach

Purpose:

The purpose of this study is to investigate the intricate relationship between periodontal disease (PD) and coronary artery disease (CAD), as evidenced by epidemiological associations. Metalloproteinase inhibitor (TIMP1) plays a pivotal role in cellular signaling, differentiation, cell death, and migration by binding to target metalloproteinases, forming complexes with other molecules (collagenases) to inactivate them. However, the expression of TIMP1 is reduced in both PD and CAD, leading to an upregulation of other metalloproteinases. This research explores the hypothesis that metabolites released from (Porphyromonas gingivalis), a prevalent bacterium in atherosclerotic patients, may inhibit TIMP1, thereby influencing CAD progression.

Methods:

This research utilized a series of computational techniques, encompassing data mining, protein network analysis, molecular modeling, molecular docking, and molecular dynamics simulation. In the initial phase, metabolites from Porphyromonas gingivalis were retrieved from the Virtual Metabolic Human (VMH) database. The proteins associated with the TIMP1 were identified through the construction of a protein interaction network in Cytoscape. Subsequently, the TIMP1 underwent modeling using the Swiss-Model web server and was docked with bacterial metabolites. Furthermore, the structural stability of both the protein and metabolite was evaluated over a 100 ns simulation period.

Results:

In total, 370 metabolites from Porphyromonas gingivalis were obtained from the database. Notably, the network analysis revealed that MMP1, MMP9, and MMP14 were closely associated with TIMP1. Molecular docking outcomes demonstrated that Malonyl CoA displayed a binding affinity of -8.82 kcal/mol at the active sites of TIMP1. Additionally, a stable complex between TIMP1 and Malonyl CoA was observed throughout the simulation period, potentially influencing the activity of TIMP1.

Conclusion:

This investigation underscores the potential implications of Porphyromonas gingivalis metabolites as a risk factor in the development of CAD. The computational analysis suggests that these metabolites may disrupt the function of TIMP1, thereby contributing to the elevated levels of metalloproteinases observed in CAD patients. This emphasizes the critical need for further research to delve into the intricate mechanisms and exploring potential therapeutic interventions.