Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation to Elucidate the Molecular Targets and Potential Mechanism of Phoenix dactylifera (Ajwa Dates) against Candidiasis

Abstract

Candidiasis, caused by opportunistic fungal pathogens of the Candida genus, poses a significant threat to immunocompromised individuals. Natural compounds derived from medicinal plants have gained attention as potential sources of anti-fungal agents. Ajwa dates (Phoenix dactylifera L.) have been recognized for their diverse phytochemical composition and therapeutic potential. In this study, we employed a multi-faceted approach to explore the anti-candidiasis potential of Ajwa dates' phytochemicals. Utilizing network pharmacology, we constructed an interaction network to elucidate the intricate relationships between Ajwa dates phytoconstituents and the Candida-associated molecular targets of humans. Our analysis revealed key nodes in the network (STAT3, IL-2, PTPRC, STAT1, CASP1, ALB, TP53, TLR4, TNF and PPARG), suggesting the potential modulation of several crucial processes (the regulation of the response to a cytokine stimulus, regulation of the inflammatory response, positive regulation of cytokine production, cellular response to external stimulus, etc.) and fungal pathways (Th17 cell differentiation, the Toll-like receptor signaling pathway, the C-type lectin receptor signaling pathway and necroptosis). To validate these findings, molecular docking studies were conducted, revealing the binding affinities of the phytochemicals towards selected Candida protein targets of humans (ALB-rutin (-9.7 kJ/mol), STAT1-rutin (-9.2 kJ/mol), STAT3-isoquercetin (-8.7 kJ/mol), IL2-β-carotene (-8.5 kJ/mol), CASP1-β-carotene (-8.2 kJ/mol), TP53-isoquercetin (-8.8 kJ/mol), PPARG-luteolin (-8.3 kJ/mol), TNF-βcarotene (-7.7 kJ/mol), TLR4-rutin (-7.4 kJ/mol) and PTPRC-rutin (-7.0 kJ/mol)). Furthermore, molecular dynamics simulations of rutin-ALB and rutin-STAT1 complex were performed to gain insights into the stability and dynamics of the identified ligand-target complexes over time. Overall, the results not only contribute to the understanding of the molecular interactions underlying the anti-fungal potential of specific phytochemicals of Ajwa dates in humans but also provide a rational basis for the development of novel therapeutic strategies against candidiasis in humans. This study underscores the significance of network pharmacology, molecular docking and dynamics simulations in accelerating the discovery of natural products as effective anti-fungal agents. However, further experimental validation of the identified compounds is warranted to translate these findings into practical therapeutic applications.

Keywords: Ajwa dates; Phoenix dactylifera; candidiasis; fungal infection; molecular dynamics; network pharmacology.

Figure 1

Venn diagram showing common targets between phytochemical constituents of Ajwa dates and candidiasis in humans.

Figure 2

A common protein target network of phytochemical constituents of Ajwa dates and candidiasis-associated targets of humans constructed using Cytoscape (different-color circles represent common target proteins and orange-color edges represent interactions between common targets).

Figure 3

An Ajwa date–phytochemical constituent–intersected candidiasis protein target network, which is a network between the phytochemical constituents of Ajwa dates and the intersected genes (the pink ‘V’ shape represents common protein targets, orange diamonds represent phytochemical constituents of Ajwa dates and green-color edges denote the association between targets).

Figure 4

A PPI network of identified hub targets from the obtained common targets of phytochemical constituents of Ajwa dates and candidiasis for humans. A gradient of orange shades indicates the centrality degree of the nodes. Darker shades represent nodes with higher-degree centrality (i.e., they have more connections (edges) to other nodes in the network). Conversely, lighter or paler shades indicate nodes with lower-degree centrality (i.e., signifying fewer connections).

Figure 5

Network of hub targets against candidiasis in humans analyzed using GeneMANIA. The functional association of targets was analyzed, and connecting lines with different colors represent different correlations. Targets (cyan-color triangles) on the inner side were submitted as query terms in searches. Nodes (purple-color diamonds) on the outer side represent targets associated with query targets. (Peach-pink-color edges represent physical interactions, purple-color edges represent co-expression, green-color edges represent genetic interactions, cyan-color edges represent pathways, sand-brown-color edges represent colocalization, and orange-color edges represent shared protein domains).

Figure 6

GO enrichment and KEGG pathway analyses of identified hub target proteins (p-value ≤ 0.05). (A) The top 10 biological processes, (B) the top 10 cellular components, (C) the top 10 molecular functions and (D) the top 10 KEGG pathways. The color scales indicate the different thresholds for the p-values, and the sizes of the dots represent the number of targets corresponding to each term.

Figure 7

Binding affinities of the top-rated pose of the ligand–receptor complex.

Figure 8

(A,B) Visualization of docking analysis of ALB and rutin, and (C,D) visualization of docking analysis of CASP1 and β-carotene.

Figure 9

(A,B) Visualization of docking analysis of IL-2 and β-carotene, and (C,D) visualization of docking analysis of PPARG and luteolin.

Figure 10

(A,B) Visualization of docking analysis of PTPRC and rutin, and (C,D) visualization of docking analysis of STAT1 and rutin.

Figure 11

(A,B) Visualization of docking analysis of STAT3 and isoquercetin, and (C,D) visualization of docking analysis of TLR4 and rutin.

Figure 12

(A,B) Visualization of docking analysis of TNF and β-carotene, and (C,D) visualization of docking analysis of TP53 and isoquercetin.

Figure 13

Molecular dynamics of ALB and its binding with rutin. (A) RMSD plot of ALB before and after rutin binding, (B) RMSF plot of ALB–rutin complex, (C) time evolution of intermolecular H-bonds formed within 0.35 nm in the ALB–rutin complex, (D) Rg distribution of ALB–rutin complex and (E) SASA plot analysis of ALB–rutin complex.

Figure 14

Molecular dynamics of STAT1 and its binding with rutin. (A). RMSD plot of STAT1 before and after rutin binding, (B). RMSF plot of STAT1–rutin complex, (C). Time evolution of intermolecular H-bonds formed within 0.35 nm between STAT1–rutin complex, (D). The Rg distribution of STAT1–rutin complex, (E). SASA plot analysis of STAT1–rutin complex.