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Network Pharmacology: An Emerging Field in Drug Discovery (2nd Edition)

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A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Pharmacology".

Deadline for manuscript submissions: 20 June 2026 | Viewed by 9568

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Prof. Dr. Weiwei Han

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Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, Jilin University, Changchun 130012, China
Interests: the relationship between enzyme structure and function; computer-aided drug design; computational structural biology; machine learning
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Dear Colleagues,

Network pharmacology is an emerging interdisciplinary field that integrates systems biology, network analysis, and pharmacology to explore the complex interactions between drugs, targets, and diseases. By analyzing the intricate networks of biological systems, network pharmacology aims to provide a holistic understanding of drug actions and their effects on the body, thereby addressing the multifaceted nature of diseases. This approach has revolutionized traditional drug discovery by shifting the focus from single-target to multi-target strategies, enabling the identification of novel therapeutic agents and the optimization of existing ones.

The purpose of this Special Issue is to provide a comprehensive overview of the state of the art in network pharmacology methodologies and their applications in drug discovery and development. We welcome original research articles, review articles, and short communications on one or more of the following topics:

Development, implementation, and application of network pharmacology databases;
Development and application of new network analysis tools and algorithms;
Integration of multi-omics data into network pharmacology studies;
Construction, visualization, and analysis of drug–target interaction networks;
Identification of novel drug targets and pathways through network pharmacology;
Application of network pharmacology in understanding complex diseases and multi-target drug discovery;
Development and application of computational models for predicting drug efficacy and safety;
Case studies on the successful application of network pharmacology in drug discovery and repurposing.

We hope that this Special Issue will serve as an entry point for newcomers into the exciting world of network pharmacology as well as a valuable reference for more experienced practitioners in the field.

Prof. Dr. Weiwei Han
Guest Editor

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

network pharmacology
machine learning
databases
drug discovery
computer-aided drug design (CADD)
data mining

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Network Pharmacology: An Emerging Field in Drug Discovery in International Journal of Molecular Sciences (13 articles)

Published Papers (7 papers)

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Research

23 pages, 5966 KB

Open AccessArticle

Drug Repurposing of Verapamil for H1N1 Influenza Virus Infection: A Multi-Target Strategy Revealed by Network Pharmacology and Experimental Validation

by Yan Cao, Jiajing Wu, Xuena Li, Feifan Qiu, Shuo Wang, Bingshuo Qian, Lingjun Fan, Yueqi Wang, Kun Xue, Junkui Zhang, Beilei Shen and Yuwei Gao

Int. J. Mol. Sci. 2026, 27(6), 2534; https://doi.org/10.3390/ijms27062534 - 10 Mar 2026

Viewed by 621

Abstract

Influenza A virus (IAV) infection constitutes a major public health threat. Severe influenza virus infection can induce intense inflammatory responses and lung injury, leading to serious clinical symptoms or even death. The utility of current anti-influenza drugs is often limited by side effects and the emergence of drug-resistant strains. Based on the critical role of L-type voltage-gated calcium channels (L-VGCCs) in influenza virus replication, this study investigates the antiviral activity and mechanism of verapamil, a classic L-type calcium channel antagonist, against H1N1-UI182 virus. Verapamil, an L-type calcium channel blocker, is widely used in the treatment of cardiovascular diseases and has a well-established safety profile. Through molecular dynamics (MD) simulation and network pharmacology analysis, we predicted the stable binding mode of verapamil to the target protein (PDB id: 6JPA) and its potential multi-target network. In vitro, verapamil exhibited antiviral activity against H1N1-UI182 in MDCK cells, enhancing the survival rate of infected cells and reducing viral nucleoprotein (NP) expression. In a lethal H1N1-UI182 infection mouse model, verapamil treatment markedly improved survival rates, alleviated weight loss and lung pathological damage, exhibiting a dose-dependent protective effect. Lung tissue analysis showed that verapamil effectively reduced the lung index and viral load, suppressed the activation of the Nuclear factor kappa B (NF-κB) signaling pathway, and decreased the expression of key inflammatory factors, thereby mitigating the cytokine storm. A comparison of administration regimens indicated that pre-treatment yielded optimal efficacy, suggesting verapamil acts primarily during the early stage of the viral life cycle. This study systematically elucidates that verapamil exerts antiviral and immunomodulatory effects by regulating the NF-κB pathway. Network pharmacology analysis suggested the potential involvement of multiple targets and pathways, including EGFR, SRC, and phospholipase D signaling, providing hypotheses for future mechanistic investigation. This paper supports a drug repurposing strategy against drug-resistant influenza viruses and highlights its significant potential for clinical translation. Full article

(This article belongs to the Special Issue Network Pharmacology: An Emerging Field in Drug Discovery (2nd Edition))

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21 pages, 5951 KB

Open AccessArticle

Uncovering the Potential Mechanisms of Ergothioneine in Neuroinflammation Through Network Pharmacology, Molecular Docking, Molecular Dynamics Simulation, and In Vitro Validation

by Deyou Cao, Jingxuan Jia, Yishu Yin and Weihong Lu

Int. J. Mol. Sci. 2026, 27(5), 2179; https://doi.org/10.3390/ijms27052179 - 26 Feb 2026

Viewed by 701

Abstract

Neuroinflammation is a critical pathological process implicated in several neurological disorders. It arises from complex interactions among immune cells and the excessive release of pro-inflammatory mediators, ultimately leading to neuronal damage. Ergothioneine (EGT), a naturally occurring antioxidant, has attracted attention for its potential anti-inflammatory role in neuroinflammation, although it remains poorly understood. We employed a comprehensive strategy combining network pharmacology, molecular docking, molecular dynamics simulations, and in vitro experiments to explore how EGT influences neuroinflammatory pathways. Computational analyses indicated that EGT might regulate several inflammation-related signaling cascades by targeting key molecules such as Tumor Necrosis Factor (TNF), AKT Serine/Threonine Kinase 1 (AKT1), Caspase 3 (CASP3), and Interleukin 6 (IL-6). Docking and dynamics simulations confirmed strong and stable binding between EGT and these targets. Experiments using lipopolysaccharide-stimulated BV2 microglia cells demonstrated that EGT significantly reduced pro-inflammatory cytokine production, primarily through modulation of the phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling pathways. By integrating multi-omics approaches with cellular validation, this study sheds light on the molecular mechanisms underlying EGT’s anti-inflammatory effect and supports its potential application as a functional food ingredient for managing neuroinflammation. Full article

(This article belongs to the Special Issue Network Pharmacology: An Emerging Field in Drug Discovery (2nd Edition))

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16 pages, 2268 KB

Open AccessArticle

Deciphering the Skin Anti-Aging and Hair Growth Promoting Mechanisms of Opophytum forskahlii Seed Oil via Network Pharmacology

by Shaimaa R. Ahmed, Hanan Khojah, Maram Aldera, Jenan Alsarah, Dai Alwaghid, Luluh Hamdan, Hadeel Aljuwair, Manal Alshammari, Hanadi Albalawi, Reema Aldekhail, Abdullah Alazmi and Sumera Qasim

Int. J. Mol. Sci. 2026, 27(1), 277; https://doi.org/10.3390/ijms27010277 - 26 Dec 2025

Viewed by 2008

Abstract

Opophytum forskahlii has a well-established ethnopharmacological significance. This study aimed to assess the skin anti-aging and hair growth-promoting activities of O. forskahlii seed oil (OFSO) and the underlying mechanism. GC-MS profiling revealed high levels of unsaturated fatty acids, linoleic acid (55.46%), and oleic acid (38.54%). The skin anti-aging activity of OFSO (3.125–100 µg/mL) was evaluated in normal human dermal fibroblasts (NHDFs) using MTT and enzyme inhibition assays. OFSO was non-cytotoxic and enhanced fibroblast proliferation in a dose-dependent manner, reaching 145.5% of control at 100 µg/mL (p < 0.05). OFSO significantly (p < 0.05) inhibited collagenase (48%), hyaluronidase (53%), elastase (57%), and tyrosinase (55%). The oil showed anti-inflammatory activity by inhibiting COX-1 and COX-2 (0.01–100 µg/mL) with IC₅₀ = 0.125 and 0.014 µg/mL, respectively. The hair growth promoting efficacy was assessed using adult male Wistar rats, randomly divided into control, OFSO-treated, and 2% minoxidil-treated groups (5 rats/group). Hair growth was assessed through visual scoring over 14 days of topical application and confirmed by histological examination and hair follicle counting. On day 14, the OFSO-treated group displayed almost complete hair coverage (score about 5.0), exceeding minoxidil (about 4.0), and significantly increased hair follicle number (14.0 ± 1 vs. 9.2 ± 0.8, p < 0.05). Histology confirmed that OFSO promoted hair follicle growth, differentiation, and transition from the telogen to the anagen phase. Network pharmacology analysis, integrating targets predicted via SwissTargetPrediction and disease-associated genes from GeneCards, identified PPARG, ESR1, and IL6 as key hub genes underlying OFSO’s effects. PPARG enhances antioxidant defenses, anti-inflammatory responses, and sebaceous gland function; ESR1 supports collagen production, skin elasticity, and follicle vascularization; and IL6 modulates inflammation and triggers the anagen phase of hair growth. Functional enrichment revealed modulation of PPAR, estrogen, prolactin, and arachidonic acid metabolism pathways, suggesting that OFSO may regulate lipid metabolism, inflammation, hormonal signaling, and tissue regeneration. OFSO demonstrated promising anti-aging and hair growth activities, supporting further development and testing of cosmetic formulations. Full article

(This article belongs to the Special Issue Network Pharmacology: An Emerging Field in Drug Discovery (2nd Edition))

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33 pages, 3813 KB

Open AccessArticle

Therapeutic Potential of Beaucarnea recurvata Leaf Extract Against Ulcerative Colitis: Integrating Phytochemical Profiling, Network Pharmacology, and Experimental Validation

by Nora Tawfeek, Raha Orfali, Shagufta Perveen, Safina Ghafar, Eman Fikry, Mahmoud H. Elbatreek, Samar S. Elbaramawi, Maher M. El-Domiaty and Azza M. El-Shafae

Int. J. Mol. Sci. 2025, 26(24), 12053; https://doi.org/10.3390/ijms262412053 - 15 Dec 2025

Cited by 1 | Viewed by 812

Abstract

Ulcerative colitis represents a chronic inflammatory bowel disease with limited therapeutic options due to inadequate efficacy and adverse effects of current treatments. This study investigated the therapeutic potential of Beaucarnea recurvata leaf extract (BRLE) against ulcerative colitis using integrated computational and experimental approaches to address the need for safer, multi-targeted interventions. Phytochemical profiling was performed using UPLC-ESI-MS/MS analysis. Network pharmacology and molecular docking predicted therapeutic targets and mechanisms. In vivo validation employed an acetic acid-induced ulcerative colitis rat model with BRLE treatment at 100, 200, and 400 mg/kg doses, evaluating clinical parameters, histopathology, oxidative stress markers, inflammatory cytokines, and protein expression. UPLC-ESI-MS/MS revealed diverse bioactive compounds including steroidal saponins, triterpenes, and flavonoids. Network pharmacology identified 24 hub targets, and molecular docking revealed strong binding affinities (−6.5 to −9.1 kcal/mol) between BRLE compounds and inflammatory proteins including EGFR, SRC, STAT3, and AKT1. BRLE at 200 mg/kg significantly improved disease activity, restored glutathione levels, reduced malondialdehyde, normalized IL-10 and TNF-α levels, downregulated EGFR, SRC, STAT3, and AKT1 expression, and enhanced mucosal healing with reduced inflammatory infiltration. BRLE demonstrates significant anti-inflammatory, antioxidant, and tissue-protection effects through multi-target mechanisms, representing a promising therapeutic intervention for ulcerative colitis treatment. Further studies in chronic models, pharmacokinetic assessments, and clinical trials are needed to support its translation into therapeutic use. Full article

(This article belongs to the Special Issue Network Pharmacology: An Emerging Field in Drug Discovery (2nd Edition))

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21 pages, 3723 KB

Open AccessArticle

Computational Insights into the Molecular Mechanisms of Coptis chinensis Franch. in Treating Chronic Atrophic Gastritis: An Integrated Network Pharmacology, Machine Learning, and Molecular Dynamics Study

by Chengxiang Hu, Yang Liu, Yiyao Ding, Yue Jin and Weiwei Han

Int. J. Mol. Sci. 2025, 26(24), 11998; https://doi.org/10.3390/ijms262411998 - 12 Dec 2025

Viewed by 889

Abstract

Chronic atrophic gastritis (CAG) is a precancerous gastric condition with limited therapeutic interventions, and the mechanisms underlying the benefits of Coptis chinensis Franch. (CCF) remain insufficiently defined. This study employed an integrated computational strategy to clarify the molecular basis of CCF activity against CAG. Network pharmacology was used to identify potential targets of the major CCF constituents berberine, coptisine, and palmatine, followed by molecular docking, machine learning-based IC₅₀ prediction, and molecular dynamics simulations. Fifty-eight overlapping targets between CCF compounds and CAG-related genes were identified, highlighting SRC, STAT3, MAPK1, and NFKB1 as central nodes enriched in inflammatory and immune pathways, including TNF and MAPK signaling. Docking analyses revealed strong interactions between all three compounds and SRC kinase, and machine learning models predicted IC₅₀ values in the low micromolar range (1.38–1.82 μM). Molecular dynamics simulations further suggest that berberine may stabilize the crucial regulatory regions of SRC, specifically the activation loop. It is hypothesized that this stabilization maintains the inactive conformation of the kinase domain and potentially shields Tyr416 from phosphorylation, thus potentially influencing kinase activation. These findings suggest that CCF may modulate key inflammatory and immune pathways implicated in CAG progression, with SRC emerging as a central node for further investigation. Full article

(This article belongs to the Special Issue Network Pharmacology: An Emerging Field in Drug Discovery (2nd Edition))

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21 pages, 6806 KB

Open AccessArticle

Elucidating the Mechanisms of Chrysanthemum Action on Atopic Dermatitis via Network Pharmacology and Machine Learning

by Shiying Li, Yongxin Jiang, Chengxiang Hu, Yiyao Ding, Xueqi Fu, Shu Xing and Linlin Zeng

Int. J. Mol. Sci. 2025, 26(23), 11262; https://doi.org/10.3390/ijms262311262 - 21 Nov 2025

Viewed by 1500

Abstract

Chrysanthemum (Chrysanthemum morifolium Ramat.) has been recognized as both a food and medicinal substance in China since 2002 and possesses antioxidant, anti-inflammatory, antibacterial, and immunomodulatory activities. Previous studies suggest that Chrysanthemum may alleviate skin lesions resembling atopic dermatitis (AD); however, its underlying mechanisms remain unclear. In this study, we integrated network pharmacology and machine learning to systematically explore the potential mechanisms of Chrysanthemum in AD treatment. Four algorithms—Random Forest (RF), Lasso regression with cross-validation (LassoCV), Elastic Net (EN), and Extreme Gradient Boosting (XGB)—were compared, among which the XGB model achieved the best performance (accuracy = 0.9393). Further analysis identified 15 optimal features, two core targets (PTGS2 and MMP9), and one critical pathway (NF-κB signaling). To experimentally validate these findings, HaCaT keratinocytes were co-stimulated with TNF-α and IFN-γ to establish an in vitro inflammatory model, and co-treatment with three major flavonoids from Chrysanthemum—Acacetin, Diosmetin, and Chryseriol—significantly suppressed cytokine-induced COX-2 overexpression and reduced NF-κB p65 phosphorylation, confirming their inhibitory effects on NF-κB activation. These results were consistent with molecular docking and dynamics simulations, which demonstrated that these flavonoids, along with celecoxib, could stably bind to COX-2, thereby enhancing system stability and reducing residue fluctuations at the binding interface, revealing the molecular basis by which Chrysanthemum alleviates AD and supporting its modernization and therapeutic potential. Full article

(This article belongs to the Special Issue Network Pharmacology: An Emerging Field in Drug Discovery (2nd Edition))

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32 pages, 15870 KB

Open AccessArticle

Molecular Insights into Bromocriptine Binding to GPCRs Within Histamine-Linked Signaling Networks: Network Pharmacology, Pharmacophore Modeling, and Molecular Dynamics Simulation

by Doni Dermawan, Lamiae Elbouamri, Samir Chtita and Nasser Alotaiq

Int. J. Mol. Sci. 2025, 26(17), 8717; https://doi.org/10.3390/ijms26178717 - 7 Sep 2025

Cited by 2 | Viewed by 2157

Abstract

This study aimed to investigate the molecular binding mechanisms of bromocriptine toward histamine-associated targets, exploring both antagonist-like and other potential interaction modes that may support therapeutic repurposing. Network pharmacology was applied to identify histamine-related pathways and prioritize potential protein targets. CXCR4, GHSR, and OXTR were selected based on combined docking scores and pharmacophore modeling evidence. Molecular dynamics (MD) simulations over 100 ns assessed structural stability, flexibility, compactness, and solvent exposure. Binding site contact analysis and MM/PBSA free binding energy calculations were conducted to characterize binding energetics and interaction persistence. Bromocriptine exhibited stable binding to all three receptors, engaging key residues implicated in receptor modulation (e.g., Asp187 in CXCR4, Asp99 in GHSR, Arg232 in OXTR). The MM/PBSA ΔG_binding values of bromocriptine were −22.67 ± 3.70 kcal/mol (CXCR4 complex), −22.11 ± 3.55 kcal/mol (GHSR complex), and −21.43 ± 2.41 kcal/mol (OXTR complex), stronger than standard agonists and comparable to antagonists. Contact profiles revealed shared and unique binding patterns across targets, reflecting their potential for diverse modulatory effects. Bromocriptine demonstrates high-affinity binding to multiple histamine-associated GPCR targets, potentially exerting both inhibitory and modulatory actions. These findings provide a molecular basis for further experimental validation and therapeutic exploration in histamine-related conditions. Full article

(This article belongs to the Special Issue Network Pharmacology: An Emerging Field in Drug Discovery (2nd Edition))

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