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Daily Signal February 04, 2026 · 10 min read

Issue #40: Decrypting potential mechanisms linking ochratoxin A to hepatocellular carcinoma: an integrated approach combining toxicology, machine learning, molecular docking, and molecular dynamics simulation.

Protein Design Digest - 2026-02-04 - Decrypting potential mechanisms linking ochratoxin A to hepatocellular carcinoma: an integrated approach combining toxicology, machine learning, molecular docking, and molecular dynamics simulation.

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Decrypting potential mechanisms linking ochratoxin A to hepatocellular carcinoma: an integrated approach combining toxicology, machine learning, molecular docking, and molecular dynamics simulation.

Background Ochratoxin A (OTA), a common food-borne mycotoxin, is a potential human carcinogen, yet the specific molecular mechanisms linking it to hepatocellular carcinoma (HCC) remain unclear. Methods We integrated network toxicology to predict OTA targets and intersected them with HCC transcriptomic data to identify key candidate genes. Functional enrichment analysis was then conducted. Multiple machine learning algorithms were applied to screen and validate core genes. Furthermore, molecular docking and molecular dynamics (MD) simulations were employed to evaluate the binding stability between OTA and key target proteins. Results A total of 50 key genes were identified as potential targets for potential OTA-associated hepatocarcinogenesis. Enrichment analysis revealed their significant involvement in critical processes such as xenobiotic metabolism and oxidative stress response. Machine learning analysis prioritized eight core genes (AURKA, GABARAPL1, CA2, PARP1, LMNA, SLC27A5, EPHX2, and GSTP1), and a combined diagnostic model demonstrated outstanding performance (AUC = 0.986). Structural analyses via molecular docking and MD simulations confirmed stable binding interactions between OTA and these core targets. Conclusions This integrated computational study identifies a set of candidate genes through which OTA may potentially interact with HCC-associated molecular networks. The robust binding predicted between OTA and the core targets provides a structural basis for these interactions. These findings offer a prioritized list of targets and a theoretical framework for subsequent experimental validation and investigation into OTA’s toxicological role in HCC.

Why this matters: Enhances small-molecule or peptide docking accuracy for targeted drug discovery.

Also Worth Reading

Study on the Mechanism of Ku Diding in the Treatment of Diabetes based on Network Pharmacology, Molecular Docking Technology, and Molecular Dynamics.

Introduction To explore how Ku Diding (KDD) works in managing Diabetes Mellitus (DM), researchers utilized network pharmacology, molecular docking, and molecular dynamics methodologies. Methods Key active components of KDD were identified using the Traditional Chinese Medicine Systematic Pharmacology Database and Analysis Platform (TCMSP). Data for diabetesrelated targets were retrieved from the Human Genetic Comprehensive Databases (Genecards) and the Online Mendelian Inheritance in Man (OMIM) database. The intersection of these targets was analyzed to determine potential therapeutic targets for diabetes treatment. Proteinprotein interaction networks (PPI) were constructed using the STRING database and Cytoscape software, followed by Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Molecular docking between the components and key targets was performed using the AutoDock Vina platform. Results This study identified that Dihydrosanguinarine, (S)-Scoulerine, among others, are the main active ingredients of KDD for treating DM, showing high affinity for critical targets like PTGS2 and PRKACA, through multiple pathways including vascular regulation, neuromodulation, metabolic regulation, and endocrine regulation. The molecular docking results showed that there are interactions between the active ingredients and the key targets, with the majority of the effective components exhibiting a stronger binding affinity than Metformin. Among them, (S)-Scoulerine and Dihydrosanguinarine demonstrated high docking affinity with the key target proteins PTGS2 and PRKACA. Discussion DM is closely linked to oxidative stress, chronic inflammation, and insulin signaling dysregulation. This study reveals that KDD exerts anti-diabetic effects via a multi-target network involving proteins such as PRKACA, PTGS2, ESR1, FOS, and DRD2. These targets are associated with glucose metabolism, inflammation, oxidative stress, and neural regulation. Modulation of these pathways likely enhances insulin sensitivity, lowers blood glucose, suppresses inflammation, and protects against oxidative damage. GO and KEGG analyses further indicate involvement in MAPK signaling, synaptic transmission, and vascular regulation, forming a multidimensional “metabolism-inflammation-neural” regulatory network. Compared to Metformin, most KDD-derived compounds showed stronger binding, highlighting their therapeutic potential. Molecular dynamics simulations support the stability of the observed binding conformations, suggesting their potential as therapeutic targets. These findings underscore KDD’s ability to simultaneously target multiple pathological mechanisms, offering a holistic treatment strategy for DM. Conclusion This study provides preliminary evidence that KDD is characterized by a multicomponent, multi-target, and multi-pathway approach in the treatment of diabetes mellitus (DM), thereby establishing a scientific foundation for further in-depth exploration of KDD’s molecular mechanisms.

Exploring the Mechanism of Oral Cancer With Shikonin Based on the Network Pharmacology and Molecular Docking Technology.

To explore the underlying mechanisms of shikonin in treating oral cancer using network pharmacology and molecular docking methods. Targets of shikonin were obtained from the TCMSP, BATMAN, ChEMBL, PharmMapper and HERB databases. Targets of oral cancer were gathered from the OMIM, STITCH, GeneCards and Drugbank databases. The intersection targets of shikonin and oral cancer were obtained for subsequent analysis. The intersecting targets of shikonin and oral cancer were entered into the DAVID database and used its functions to perform Gene Ontology (GO) and Kyoto encyclopaedia of genes and genomes (KEGG) enrichment analysis on the intersection targets to obtain the relevant pathways and biological functions of shikonin in the treatment of oral cancer. The protein-protein interaction (PPI) network of shikonin and oral cancer targets was constructed in STRING platform. Subsequently, using Cytoscape 3.8.0 to obtain the key targets of shikonin and oral cancer. Finally, molecular docking and molecular dynamics simulations were used to evaluate the strength of binding between shikonin and key targets, as well as the hydrogen bonds involved. In total, 481 targets were screened for shikonin, and 10,058 targets were identified for oral cancer. By GO and KEGG analysis, the targets of shikonin and oral cancer may be involved in the mediation of apoptosis, inflammation and immune response. And the associated signalling pathways that targets may be involved in the treatment of oral cancer, including the FoxO signalling pathway, HIF-1 signalling pathway, TNF signalling pathway, and Th17 cell differentiation, etc. Cytoscape software screened the key genes including AKT1, MAPK1, CXCR4, CXCL8, CCL3, CCL4, CCL5, CYBB, BCL2, NOX1, HIF-1, TP53. The results of molecular docking and molecular dynamics simulations showed that shikonin exhibits good binding interactions with CCL3, AKT1 and NOX1. Mulitple molecular mechanisms involved in oral cancer management with shikonin have been elucidated providing a glimpse og the underlying therapeutic targets for the disease..

Vapour-Phase-Metalation Nanosurgery by ALD: A Tool for Single Molecular Replacement on Enterobactin for Drug Discovery and Nanomaterial Design

Abstract For the first time, the innovative vapour-phase metalation (VPM) process has been employed to functionalize soft materials such as Ferric Enterobactin (FeH x EB) and Enterobactin (H 6 EB) by linking ZnOH fragments, solely pulsing diethylzinc (DEZ). The samples were characterised through a suite of advanced techniques, including 1H and 13C 2D-HSQC nuclear magnetic resonance (NMR), infrared (IR) spectroscopy, UV-Vis spectroscopy, and MALDI-TOF mass spectrometry (MS). Groundbreaking density functional theory calculations successfully correlated the IR and NMR data, shedding light on the profound influence of the ZnOH fragments on the architectures of FeH 3 EB and H 6 EB. Moreover, insightful molecular dynamics and molecular docking studies were conducted to explore the affinity energy between the ZnOH-modified and non-modified siderophore and the ferric protein enterobactin receptor (FepA). Spectroscopic analyses not only confirmed the successful Zn-modification of FeH 3 EB and H 6 EB but also underscored the potential of the VPM process for attaching metals to soft materials. The docking results revealed a compelling interaction between the ZnOH-modified siderophore and FepA, boasting an affinity equal to or even surpassing that of their unmodified counterparts. This work positions VPM as a cornerstone technology for atomic-level molecular engineering, with transformative implications across healthcare, materials science, and environmental sustainability.

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