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Daily Signal March 05, 2026 · 9 min read

Issue #61: Investigation of the potential mechanism by which methylparaben induces psoriasis: an integrated study using network toxicology, molecular docking, molecular dynamics simulation, and eight machine learning algorithms.

Protein Design Digest - 2026-03-05 - Investigation of the potential mechanism by which methylparaben induces psoriasis: an integrated study using network toxicology, molecular docking, molecular dynamics simulation, and eight machine learning algorithms.

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Signal of the Day

Investigation of the potential mechanism by which methylparaben induces psoriasis: an integrated study using network toxicology, molecular docking, molecular dynamics simulation, and eight machine learning algorithms.

Psoriasis is a chronic inflammatory skin disease with limited safe and effective treatments. Methylparaben, a widely used preservative in cosmetics, pharmaceuticals, and food, is an emerging environmental pollutant linked to immune-related skin disorders, but its role and mechanism in psoriasis remain unclear. This study explored its potential mechanism using network toxicology, molecular docking, molecular dynamics simulation, and eight machine learning algorithms. Methylparaben targets were retrieved from GeneCards and TCMSP, and psoriasis-related targets from CTD and GeneCards. Overlapping targets were screened with Venny 2.1.0. A PPI network was constructed via STRING, and core targets identified using Cytoscape 3.10.2. GO and KEGG enrichment analyses were performed on DAVID. Molecular docking evaluated the binding affinity of methylparaben with key targets. A total of 138 compound-related and 5,592 psoriasis-related targets were identified. Core targets such as INS, HIF1A, and PPARG are involved in regulating immune-inflammatory responses, keratinocyte proliferation and differentiation, and oxidative stress. GO analysis revealed enrichment in xenobiotic metabolism, lipopolysaccharide response, and metal ion binding. KEGG analysis highlighted pathways related to cancer, chemical carcinogenesis from reactive oxygen species, and drug metabolism via cytochrome P450 enzymes. Molecular docking showed stable binding of methylparaben to INS (-4.5 kcal/mol), HIF1A (-5.9 kcal/mol), and PPARG (-5.5 kcal/mol), primarily through hydrogen bonds and hydrophobic interactions. Methylparaben may exert its effects on psoriasis via multi-target and multi-pathway mechanisms, influencing inflammation, oxidative stress, and cellular regulation. These findings provide valuable insight into its toxicological mechanism and potential therapeutic application.

Why this matters: Provides actionable mutations to enhance catalytic efficiency or thermostability.

Also Worth Reading

Identification of Bioactive Ingredients and Mechanistic Pathways of Xuefu Zhuyu Decoction in Ventricular Remodeling: A Network Pharmacology, Molecular Docking and Molecular Dynamics Simulations.

Background Xuefu Zhuyu Decoction (XFZYD) is clinically used in China to promote blood circulation, resolve blood stasis, and alleviate ventricular remodeling (VR). However, its molecular mechanisms remain unclear. Objective This study investigates the active components and underlying molecular mechanisms of XFZYD in treating VR. Methods Targets of XFZYD’s active components and VR-related targets were identified. A protein-protein interaction (PPI) network and a drug-ingredient-target network were constructed. GO functional annotation and KEGG pathway enrichment analysis were performed to explore biological functions. Hub targets and their corresponding active ingredients were validated through molecular docking and molecular dynamics (MD) simulations. Results A total of 1,089 active ingredients with high gastrointestinal absorption (GI) and drug-likeness (DL ≥ 2) were identified. Five hundred and thirty-eight common targets were shared between XFZYD and VR, with 10 core targets, including AKT1, STAT3, TP53, EGFR, SRC, TNF, MAPK3, CTNNB1, IL6, and VEGFA. GO analysis revealed XFZYD’s influence on wound healing, oxygen response, epithelial cell proliferation, and receptor signaling. KEGG analysis highlighted key pathways such as PI3K-Akt signaling, lipid and atherosclerosis, and fluid shear stress. Molecular docking revealed that active ingredients display favorable interactions with the hub genes, with binding energies from -9.5 to -6.0 kcal/mol. These interactions were further validated through MD simulations, demonstrating stable binding throughout the 100 ns simulation period. Conclusion XFZYD exhibits therapeutic effects on VR through multiple active components and pathways, providing a scientific basis for its clinical application and further research.

scDock: Streamlining drug discovery targeting cell-cell communication via scRNA-seq analysis and molecular docking.

Summary Identifying drugs that target intercellular communication networks represents a promising therapeutic strategy, yet linking single-cell RNA sequencing (scRNA-seq) analysis to structure-based drug screening remains technically challenging and requires substantial bioinformatics expertise. We present scDock, an integrated and user-friendly pipeline that seamlessly connects scRNA-seq data processing, cell-cell communication inference, and molecular docking-based drug discovery. Through a single configuration file, users can execute the complete workflow, from raw scRNA-seq data to ranked drug candidates, without programming skills. scDock automates the identification of disease-relevant ligand-receptor interactions from scRNA-seq data and performs structure-based virtual screening against these communication targets using Protein Data Bank (PDB) or AlphaFold-predicted protein structures. The pipeline generates comprehensive outputs at each stage, enabling users to explore intercellular signaling alterations and discover therapeutic compounds targeting specific cell-cell communications. scDock addresses a critical gap by providing an accessible end-to-end solution for communication-targeted drug discovery from single-cell data. Availability and implementation scDock is freely available at https://doi.org/10.6084/m9.figshare.31370368 and https://github.com/Andrewneteye4343/scDock. It is implemented in R, Python, shell scripts, and supports Linux systems, including Ubuntu and Debian. Supplementary information Supplementary data are available at Bioinformatics online.

Exploring the Mechanism of Action of Chicoric Acid Against Influenza Virus Infection Based on Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation.

This study theoretically explores the mechanism of action of Chicoric acid against influenza virus based on network pharmacology, molecular docking, and molecular dynamics simulation techniques, aiming to provide insights for the development of new veterinary drugs for influenza. Potential targets for influenza virus action were identified using the PharmMapper (i.e. Version 2017) server and disease databases including GeneCards and OMIM. The STRING online analysis platform and Cytoscape 3.9.1 software were employed to construct a protein-protein interaction (PPI) network of the target proteins, followed by topological analysis to screen for key targets. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on the intersecting targets using the DAVID database. A “drug-target-pathway” network diagram was constructed using Cytoscape 3.9.1 software. Molecular docking was carried out with AutoDock 1.5.6 and PyMOL 2.5 software to identify dominant binding targets, followed by molecular dynamics simulation analysis. The results of network analysis showed that there were 31 potential targets of Chicoric acid; the protein interaction network suggested that UBC, UBA52, RPS27A, HCK, and CDKN1B may be the core targets of Chicoric acid; 55 cell biological processes were obtained by GO enrichment analysis, and 15 related signaling pathways were obtained by KEGG pathway enrichment analysis; molecular docking showed that UBC and UBA52 had a good affinity to Chicoric acid and may be the dominant target of Chicoric acid exerting its effect. Chicoric acid may play a role in antiviral activity by acting on the dominant protein of UBC and UBA52, thus achieving an anti-influenza virus effect.

Research & AI Updates

From the Industry

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Batai orthobunyavirus (BATV) is a mosquito-borne orthobunyavirus that affects both humans and animals, and currently no licensed vaccine is available. Read more →

Inference-Time Toxicity Mitigation in Protein Language Models

Protein language models (PLMs) are becoming practical tools for de novo protein design, yet their dual-use potential raises safety concerns. Read more →

Interpretation of the anti-colitis active ingredients and potential mechanisms of Wumei Wan based on spectrum-effect relationships, network pharmacology, molecular docking and experimental validation.

Wumei Wan (WMW), a renowned classic traditional Chinese medicine formula, is traditionally indicated for regulating cold-heat imbalance, exerting intestinal astringent effects, and arresting diarrhea. Read more →

Aloperine exerts anti-ovarian cancer effects by regulating the tricarboxylic acid cycle and glycolysis: A comprehensive study integrating network pharmacology, molecular docking, metabolomics, and experimental validation.

Aloperine (ALO), an alkaloid derived from Sophora alopecuroides L., demonstrates therapeutic potential against malignant tumors, while the role of ALO and its molecular mechanisms in ovarian cancer remain unclear. Read more →

Integrating ensemble machine-learning and fibril docking to discover potent, novel triazole-naphthalene tau-aggregation inhibitors.

Tau-protein aggregation is a central pathological feature of Alzheimer’s disease, so blocking fibril growth is an attractive therapeutic goal. Read more →

Synergistically Enhanced Peroxidase-like Activity of FeSe2/rGO Nanohybrids: Kinetic, Mechanistic, and Molecular Docking Studies.

FeSe2/rGO nanohybrids were prepared via in situ one-pot synthesis using the hydrothermal method and were assessed for their potential for peroxidase-like activity. Read more →

Synthesis, Characterization, In Vitro Anticancer Activity, In Silico ADMET Profiling, and Molecular Docking Studies of Novel 2-Substituted Benzothiazoles: (2-((1S,2S)-2-((E)-substituestyryl)cyclopentyl)benzo[d]thiazoles).

In line with the need for new candidate molecules in cancer treatment, 2-substituted benzothiazole derivatives were synthesized in this study, their antiproliferative activities were evaluated, and their potential was investigated through ADMET, DFT, and molecular docking studies. Read more →

Elucidating the Therapeutic Potential of Potentilla nivea L. for Rheumatoid Arthritis Through Network Pharmacology, Molecular Docking, and Experimental Validation.

This study explored the molecular mechanism of Potentilla nivea in treating rheumatoid arthritis (RA) using network pharmacology (NP) and experimental validation. Read more →

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The protein structure is the language of life; design is its poetry. — Recep Adiyaman

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