Network pharmacology

Background: Psoriasis is a chronic immune-mediated inflammatory skin disease with multiple phenotypically distinct subtypes.  Therapeutic options for psoriasis include topical therapy, phototherapy or systemic treatment.  Treatment targets include at least 75% or 90% improvement in PASI.  Despite its growing prevalence, current pharmacological options remain limited. Manjishta (Rubia cordifolia L), described in classical Ayurvedic literature under Varnya, Vishaghna and Jwarahara mahakashaya, possesses documented hepatoprotective, anti-inflammatory, anti-proliferative and antioxidant properties. This study aimed to evaluate the potential molecular mechanisms of Manjishta phytoconstituents against psoriasis associated targets using in-silico approaches. Methods: Phytoconstituents of Rubia cordifolia L were retrieved from the IMPPAT and PubChem databases. ADME properties and drug-likeness were assessed using SwissADME, and bioavailability was visualized using the Boiled Egg model. Protein–protein interaction (PPI) networks were constructed via STRING. Molecular docking was performed using AutoDock Vina against key psoriasis related proteins. Docking interactions were analyzed in Discovery Studio Visualizer. Results: Phytoconstituents such as lucidin ethyl ether, xanthopurpurin, 1-hydroxy-2-methoxyanthraquinone, rubiadin, 1-hydroxy-2-methylanthraquinone and 2-(methoxymethyl)-1,3-dihydroxyanthraquinone demonstrated strong binding affinities (−7.0 to −8.4 kcal mol-1) toward estrogen receptor beta, neutrophil elastase, induced myeloid leukemia cell differentiation protein Mcl-1 and M-phase inducer phosphatase . ADME analysis indicated favorable oral bioavailability and compliance with Lipinski’s rule of five. The PPI network highlighted ESR1, BCL2, CASP3, DNMT1, TERT, PTPRC, DNMT3A, ESR2, MCL1 and ELANE as central nodes associated with psoriasis pathology, suggesting multi-target modulatory potential. Conclusion: This in-silico analysis predicts potential interactions of Rubia cordifolia phytoconstituents with key apoptotic, anti-inflammatory, anti-proliferative and antioxidant pathways implicated in psoriasis. These findings warrant further experimental research to validate their biological relevance.

Ayurveda, with its emphasis on Prakriti (individual constitution), Tridosha (functional principles), Rasayana (rejuvenation), and lifestyle-based prevention, provides a time-tested framework for personalised and preventive healthcare. In parallel, New Biology, empowered by high-throughput omics technologies, epigenetics, systems biology and network pharmacology offer novel tools to decode biological complexity at multiple scales. This article examines how emerging research in new biology and Ayurveda, is integrating empirical traditions with molecular science by translating traditional views into quantifiable biological correlates. The promise of network pharmacology to reveal the synergistic mechanisms of polyherbal formulations, multi-omics techniques to examine Prakriti and systems modelling to predict health and disease dynamics are discussed. Together, Ayurveda and New Biology form the basis for predictive, preventive and personalised medicine. This approach suggests a scientifically coherent and sustainable model that advances Ayurveda into a data-driven, evidence-based discipline, bridging traditional principles with precision medicine.