Phytochemical profiling, network pharmacology, and molecular dynamics simulations of Sinularia levi metabolites as potential α-glucosidase inhibitors in metabolic syndrome

In silico evaluation of novel metabolites from Tricholoma pardinum: Insights into drug-likeness, toxicity and target interactions via molecular docking and dynamics.

Six previously uncharacterized metabolites isolated from the poisonous mushroom Tricholoma pardinum are investigated using an integrated in silico approach to evaluate their therapeutic potential, highlighting the potential of metabolites from T. pardinum as novel scaffolds for developing anticancer agents targeting PARP1 and PIP4K2γ.

Phytochemical profiling and in silico evaluation of Ficus racemosa fruit extract as potential α-amylase and α-glucosidase inhibitors

Identification of Bioactive Phytoconstituents from Michelia champaca L. Flowers and Their Interactions with CXCR4 and PTEN Targets: A Comprehensive ADMET,Molecular Docking, and Molecular Dynamics Study

P predictive findings suggest that specific M. champaca flower constituents possess strong targeted binding potential against PTEN and CXCR4 nodes, establishing a validated computational foundation that warrants downstream in vitro and in vivo functional experimental validation.

Metabolomics-guided network pharmacology and molecular modeling suggest bioactive components of Chiliadenus montanus associated with multi-target anticancer and anti-inflammatory activities

Computational Study of Terpenes from Schinus molle L. Fruit Essential Oil as Potential Modulators of Osteoarthritis-Related Inflammatory Pathways: A Network Pharmacology and Molecular Docking Study

This study investigated the effects of terpene compounds from Schinus molle fruit essential oil (EO) against osteoarthritis (OA) using integrated network pharmacology, molecular docking, and molecular dynamics. The EO, obtained by steam distillation (yield: 6.95%), was characterized by GC-MS, detecting 55 peaks (98.61% of the total), of which 49 were identified and dominated mainly by monoterpene hydrocarbons (73.93%), with α-phellandrene (20.35%), camphene (11.36%), and Z-β-ocimene (8.69%) as the major constituents. Additionally, seven compounds with favorable ADME profiles and low predicted toxicity were selected for the target prediction. Overlap analysis between compound targets and osteoarthritis-related genes (Os-teoDIP) revealed 171 common genes that triggered inflammatory pathways, including PI3K-Akt, HIF-1, and NOD-like receptor signaling. Protein–protein interaction network analysis identified 11 hub genes, including TLR4, HSP90AA1, PTGS2, and MAPK1. Molecular docking revealed that γ-cadinene exhibited the best binding affinities, particularly against HSP90AA1 (−6.38 kcal/mol) and TLR4 (−5.87 kcal/mol). A 200 ns molecular dynamics simulation confirmed the stability of the γ-cadinene–TLR4 complex through persistent hydrophobic contacts with residues F379, C391, F409, I310, and F377, with contact occupancy of up to 0.95. The receptor backbone RMSD plateaued between 2.5 and 3.5 Å after equilibration, and the ligand remained in the binding pocket throughout the trajectory. These findings suggest that the terpenes of S. molle EO, particularly γ-cadinene, may modulate the inflammatory pathways related to OA. However, it is necessary to complement experimental validation in vitro and in vivo.

Phytochemical profiling and mechanistic insights into the anxiolytic potential of Sphaeranthus indicus Linn.: A network pharmacology, molecular docking and simulation approach.

Anxiety problems, such as Generalized Anxiety Disorder, are a significant source of concern for people worldwide. Current medicines frequently have side effects or are ineffective. Sphaeranthus indicus Linn, often known as Mundi, is an Ayurvedic medication that has demonstrated promising results to aid with anxiety. However, the molecular mechanism underlying its function is not known. In this study we used computational tools to understand how Sphaeranthus indicus Linn might assist persons with anxiety disorders. A library of 57 phytochemicals was compiled from databases and literature sources and was tested for BBB permeability, ADMET and toxicity. Subsequently a network was built to link the compounds with their targets and anxiety related diseases. Upon investigation of the network, it was discovered that eight phytochemicals including Eugenol, β-sitosterol, Estragole, and Camphor interacted with several targets, while four targets seemed to be most important, the serotonin transporter (SLC6A4), the glucocorticoid receptor (NR3C1), acetylcholinesterase (ACHE) and the dopamine D2 receptor (DRD2). Docking of the eight phytochemicals was performed with all four targets, which revealed that β-sitosterol docked best to all targets, while several phytochemicals exhibited favourable binding. Further, 100 ns atomistic simulations were performed for β-sitosterol with all four targets, which indicated stable binding. Thus, we conclude that these phytochemicals probably work as serotonin reuptake inhibitors by blocking the serotonin transporter, probably modulate dopamine signalling as well by interacting with dopamine D2 receptor. We also predict that these phytochemicals interact with the acetylcholinesterase and the glucocorticoid receptor, suggesting their potential to modulate neurotransmission and glucocorticoid signalling that may influence neurotransmission and stress-related signalling. Taken together, the findings from this work, provide the first network pharmacology-based evidence for S. indicus' multitarget anxiolytic processes, support its traditional use in neuropsychiatric diseases, and identify various phytochemicals as promising natural lead candidates for anxiolytic medication development.