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. 2022 Apr 7;27(8):2398.
doi: 10.3390/molecules27082398.

Defining the Role of Isoeugenol from Ocimum tenuiflorum against Diabetes Mellitus-Linked Alzheimer's Disease through Network Pharmacology and Computational Methods

Reshma Mary Martiz  1   2 , Shashank M Patil  1 , Mohammed Abdulaziz  3 , Ahmed Babalghith  4 , Mahmoud Al-Areefi  5 , Mohammed Al-Ghorbani  6   7 , Jayanthi Mallappa Kumar  8 , Ashwini Prasad  2 , Nagendra Prasad Mysore Nagalingaswamy  9 , Ramith Ramu  1
Affiliations

Defining the Role of Isoeugenol from Ocimum tenuiflorum against Diabetes Mellitus-Linked Alzheimer's Disease through Network Pharmacology and Computational Methods

Reshma Mary Martiz et al. Molecules. .

Abstract

The present study involves the integrated network pharmacology and phytoinformatics-based investigation of phytocompounds from Ocimum tenuiflorum against diabetes mellitus-linked Alzheimer's disease. It aims to investigate the mechanism of the Ocimum tenuiflorum phytocompounds in the amelioration of diabetes mellitus-linked Alzheimer's disease through network pharmacology, druglikeness and pharmacokinetics, molecular docking simulations, GO analysis, molecular dynamics simulations, and binding free energy analyses. A total of 14 predicted genes of the 26 orally bioactive compounds were identified. Among these 14 genes, GAPDH and AKT1 were the most significant. The network analysis revealed the AGE-RAGE signaling pathway to be a prominent pathway linked to GAPDH with 50.53% probability. Upon the molecular docking simulation with GAPDH, isoeugenol was found to possess the most significant binding affinity (-6.0 kcal/mol). The molecular dynamics simulation and binding free energy calculation results also predicted that isoeugenol forms a stable protein-ligand complex with GAPDH, where the phytocompound is predicted to chiefly use van der Waal's binding energy (-159.277 kj/mol). On the basis of these results, it can be concluded that isoeugenol from Ocimum tenuiflorum could be taken for further in vitro and in vivo analysis, targeting GAPDH inhibition for the amelioration of diabetes mellitus-linked Alzheimer's disease.

Keywords: AGE-RAGE; Alzheimer’s disease; GAPDH; GO analysis; Ocimum tenuiflorum; binding free energy analysis; diabetes mellitus; druglikeness and pharmacokinetics; isoeugenol; molecular docking simulation; molecular dynamics simulation; network pharmacology.

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Conflict of interest statement

All authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Venn diagram representing the interaction of T2D with AD.
Figure 2
Figure 2
The interaction network of common genes built using STRING for T2D and AD.
Figure 3
Figure 3
The (A) CytoCluster result, with highly significant clusters shown in red; (B) the significant clusters with p-values of less than 0.05 obtained after analysis.
Figure 4
Figure 4
Compound target network obtained using Cytoscape (significance based on color intensity).
Figure 5
Figure 5
The pie chart result of GO term analysis with interaction pathway obtained using ClueGo.
Figure 6
Figure 6
The cellular location of the potential marker based on CluePedia analysis.
Figure 7
Figure 7
(A) The surface interaction view of GAPDH protein bound with isoeugenol (grey) and myrcene (orange). (B,C) The 3D representation of isoeugenol and myrcene binding to the residues, respectively. (D,E) The 2D representation of isoeugenol and myrcene binding to the residues, respectively. Teal: surrounding non-binding residues, colored: bound residues.
Figure 8
Figure 8
Analysis of RMSD, RMSF, Rg, SASA, and number of hydrogen bonds of GAPDH–isoeugenol complex (black), GAPDH–myrcene complex (orange), and GAPDH protein backbone atoms (red) at 100 ns. (A) RMSD of protein complex and protein backbone. (B) RMSF. (C) Radius of gyration (Rg). (D) SASA. (E) Ligand hydrogen bonds. Source like 1e+005 means 1 × 105.
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