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Article

Systems Biology and Structure-Based In Silico Evaluations of Quercetin–Psychobiotic Interactions for the Management of Depression

1
Department of Pharmaceutical Sciences and Drug Research, Punjabi University Patiala, Patiala 147002, Punjab, India
2
Chitkara College of Pharmacy, Chitkara University, Rajpura 140401, Punjab, India
3
Department of Pharmaceutical Sciences, Faculty of Pharmacy, Zarqa University, Zarqa 13111, Jordan
*
Authors to whom correspondence should be addressed.
Pharmaceuticals 2026, 19(9), 1366; https://doi.org/10.3390/ph19091366
Submission received: 22 July 2026 / Revised: 23 August 2026 / Accepted: 27 August 2026 / Published: 28 August 2026

Abstract

Background/Objectives: Psychobiotics are live microorganisms that, when administered in appropriate amounts, can enhance mental health. Through the production of neuroactive metabolites, regulation of immune responses, and interactions along the gut–brain axis, they modulate host neurophysiology. However, significant strain-specific variability exists in their metabolic capabilities, colonization potential, and functional interactions, necessitating a systematic approach for psychobiotic strain selection. Methods: In the present study, an integrated in silico systems biology approach combining comparative genomics, genome-scale metabolic modeling, network pharmacology, molecular docking, molecular dynamics, and ADMET analysis was employed to computationally evaluate the therapeutic potential and molecular interactions of a quercetin-psychobiotic co-delivery system for managing depression by modulating the gut–brain axis. Results: Comparative genomic analysis of candidate psychobiotic strains from the genera Bifidobacterium and Lactobacillus predicted the presence of key functional genes involved in neuroactive metabolite production, immune modulation, oxidative stress tolerance, and adhesion. The presence of acetate-producing pathways alongside the absence of classical butyrate biosynthesis genes indicated an indirect contribution to short-chain fatty acid production via microbial cross-feeding interactions. Genome-scale metabolic Modeling under the conditions of quercetin supplementation predicted a significant inter-strain variation in terms of predicted biomass flux, nutrient utilization, and metabolic adaptability. Results of molecular docking showed that the binding energies were in the range of −5.854 to −9.489 kcal/mol. Conclusion: Collectively, these in silico findings provided a computational basis for the selection of psychobiotic strains and predicted that a combination of psychobiotics and quercetin could present a promising strategy for the modulation of the gut–brain axis.
Keywords: structure-based drug design; network pharmacology; genome-scale metabolic modelling; molecular docking; molecular dynamics simulation; gut–brain axis; psychobiotics structure-based drug design; network pharmacology; genome-scale metabolic modelling; molecular docking; molecular dynamics simulation; gut–brain axis; psychobiotics

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MDPI and ACS Style

Kurl, S.; Mittal, N.; Kaur, R.; Chandrasekaran, B.; Kaur, G. Systems Biology and Structure-Based In Silico Evaluations of Quercetin–Psychobiotic Interactions for the Management of Depression. Pharmaceuticals 2026, 19, 1366. https://doi.org/10.3390/ph19091366

AMA Style

Kurl S, Mittal N, Kaur R, Chandrasekaran B, Kaur G. Systems Biology and Structure-Based In Silico Evaluations of Quercetin–Psychobiotic Interactions for the Management of Depression. Pharmaceuticals. 2026; 19(9):1366. https://doi.org/10.3390/ph19091366

Chicago/Turabian Style

Kurl, Samridhi, Neeraj Mittal, Rajwinder Kaur, Balakumar Chandrasekaran, and Gurpreet Kaur. 2026. "Systems Biology and Structure-Based In Silico Evaluations of Quercetin–Psychobiotic Interactions for the Management of Depression" Pharmaceuticals 19, no. 9: 1366. https://doi.org/10.3390/ph19091366

APA Style

Kurl, S., Mittal, N., Kaur, R., Chandrasekaran, B., & Kaur, G. (2026). Systems Biology and Structure-Based In Silico Evaluations of Quercetin–Psychobiotic Interactions for the Management of Depression. Pharmaceuticals, 19(9), 1366. https://doi.org/10.3390/ph19091366

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