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2022/23 I. félév
Árpád tér 2. Alagsor 6.
Peter Juma Ochieng
An Efficient Weighted Network Centrality Approach for Exploring Mechanisms of Action of the Ruellia Herbal Formula for Treating Rheumatoid Arthritis

Aim : This study outlines an efficient weighted network centrality measure
approach and its application in network pharmacology for exploring mechanisms
of action of the Ruellia prostrata (RP) and Ruellia bignoniiflora (RB) herbal
formula for treating rheumatoid arthritis.

Method: We first calculated interconnectivity scores all the network targets. We
then computed weighted centrality measure using the calculated interconnectivity
score to identify the major network targets. To apply our technology to network
pharmacology, a tripartite drug target network, was first built to identify the
potential RP-RB active compounds. An imbalance network was then built from a
union merge of a multi-level network of drug target network and disease target
network to explore the mechanism of action of RP-RB compositive compounds in
the treatment of rheumatoid arthritis. The major identified network targets were
then validated by the enrichment analysis and a molecular docking simulation.

Result : The experimental results indicated that out of 196 compounds, 22
actively interacted with the putative target genes associated with rheumatoid
arthritis. An imbalance network simulation identified a total of 33 major network
targets. These includes 8 RP-RB compositive compounds, 10 therapeutic targets
and 15 putative target genes. The the enrichment analysis based on the Gene
Ontology and a KEGG pathway demonstrated that majority of candidate putative
target genes were frequently involved in TNF, CCR5, IL-17 and G-protein coupled
receptors signaling pathways which are critical in the progression of rheumatoid
arthritis . The molecular docking simulation indicated that Glyceryl
diacetate-2-Oleate, Hexadecanoic acid, 2,3-bis(acetyloxy)propyl ester, Glycidyl
oleate, and Oleoyl chloride and candidate known rheumatoid arthritis therapeutic
targets had high binding affinity. Molecular descriptor analysis also confirm these
compounds were within the Lipinski limits hence indicating their potential drug
likeliness for the treatment of rheumatoid arthritis.

Conclusion : This study developed a new technology that integrate
interconnectivity-based weighted network centrality measure approach and
network pharmacology techniques to explore mechanisms of action of the Ruellia
prostrata (RP) and Ruellia bignoniiflora (RB) herbal formula that could lead us
to design and discover alternative drug compounds for the management and
treatment of rheumatoid arthritis.

Keywords: Network Centrality; Rheumatoid Arthritis; Ruellia