Page 93 - ITPS-7-1

INNOSC Theranostics and
Pharmacological Sciences Plants immunoactivity: In silico study

I-PWs associated with these targets. Furthermore, the allows for interactively visualizing and analyzing molecular
nodes include the connection between bioactive-multiple structures and data. To begin, we downloaded the 3D
myeloma’s immune targets. structures of chemicals and proteins from Pubchem and
[31]
The bioactive-immune target (compound-target the Protein Data Bank (PDB) , respectively. Subsequently,
[36]
[C-T]) (interactome level) and the bioactive-multiple using the Discovery Studio and the Dock Prep plugin
myeloma’s immune gene target (diseasome level) networks (in the Chimera program), the structures of proteins and
were constructed by linking the active compounds and bioactives were prepared for the docking process. This
their corresponding targets, and the active compounds, encompassed replacing missing side chains, as well as
their immune targets and their corresponding multiple adding hydrogens and charges, all integral to the preparation
myeloma targets, respectively. In addition, the bioactive- process. Furthermore, the molecular docking was carried
multiple myeloma’s immune targets-pathway (compound- out utilizing the PyRx software and the AutoDock Vina
[37]
target-pathway [C-T-P]) network was built by linking plugin . Finally, the Discovery Studio and Ligplot+ were
[38]
the bioactive-multiple myeloma’s immune targets with used to visually present 3D and docking models .
relevant signaling pathways. 3. Results
These networks were constructed and visualized using
Cytoscape 3.2.1, an open-source Java-based software 3.1. Chemical composition of each herbal plant
platform designed for visualizing complex networks After eliminating duplicates, a total of 67 compounds were
[30]
and integrating them with diverse attribute data . identified in W. somnifera, and a total of 159 compounds
Furthermore, the Cytoscape network analyzer tool were identified in A. barbadensis, resulting in a combined
facilitated network analysis. count of 226 compounds.

In these networks, nodes represent active phytochemical 3.2. Screening of potential active compounds/
compounds derived from the herbal plant, targets, or ingredients
signaling pathways, while edges signify the interactions
between the nodes . The degree of a node corresponds All 226 compounds underwent ADMET and drug-
[31]
to the number of connections it maintains to other nodes likeness screenings. Among these, 19 bioactives were
[32]
within the network . sourced from A. barbadensis, and 18 bioactives were
sourced from W. somnifera. These bioactives include
2.8. Functional enrichment analysis (gene ontology the major constituents of each plant, even though some
[GO]) at the interactome and diseasome levels did not meet the inclusion criteria. Consequently, 36
The functional enrichment analysis of the bioactives’ compounds were selected as phytocompounds for further
immune targets (interactome level) and also the analysis analysis (Table 1).
of the bioactive-multiple myeloma’s immune gene targets 3.3. Targets of the bioactives
(diseasome level) was conducted using two tools: These
tools are robust online server-based platforms specialized Active phytocompounds in A. barbadensis bioactives
in functional STRING and g: Profiler profiling of gene or predicted a total of 590 targets, while W. somnifera
protein sets. To identify the immune pathways and other bioactives indicated 684 targets. Using Swiss Target
interacting pathways involving the bioactives, the KEGG Prediction and Pharmmapper, a total of 820 targets
database was employed. The GO process involves the emerged after all duplicates were removed.
identification of biological processes, molecular functions, 3.4. Related targets in the immune system and the
and cellular compartments associated with these gene sets. involved pathways
It also provided estimations of the degree of enrichment of
these gene sets in each of the three different categories . A total of 1378 immune genes were identified from the
[33]
This comprehensive analysis aimed to identify the innate immune database. An overlap between these
plants’ target-immune pathways, as well as their relevant immune gene targets and the bioactives’ targets produced
interacting pathways on the interactome level and also on a total of 169 bioactive immune targets.
the diseasome level (which concerns multiple myeloma) .
[34]
3.5. Targets of multiple myeloma and control drugs
2.9. Molecular docking simulation From GeneCards, 3,045 multiple myeloma gene targets
The molecular docking simulation of the hub genes (core were retrieved, and Disgenet contributed a further 1740,
genes) and their corresponding bioactive components was culminating in 1088 gene targets associated with multiple
performed using PyRx software , an application that myeloma after eliminating duplicates.
[35]

Volume 7 Issue 1 (2024) 4 https://doi.org/10.36922/itps.1076