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  • 6-Gingerol (PubChem CID 442793): Integrated Curated and In Silico Analysis of Cancer-Relevant Molecular Associations and Predicted Candidate Targets

  • Mostafa Mohammadi Nodehi,1,*
    1. National Institute of Genetic Engineering and Biotechnology (NIGEB)


  • Introduction: Introduction 6-Gingerol is a major bioactive phenolic compound of Zingiber officinale that has been investigated for effects on apoptosis, cellular stress, inflammation, and cancer-associated processes. Molecular evidence concerning bioactive compounds is distributed across resources that capture different types of evidence. The Comparative Toxicogenomics Database (CTD) provides curated chemical–gene associations derived from reported experimental evidence, whereas SwissTargetPrediction uses chemical similarity and related structural information to prioritize potential protein targets. Integrating these complementary evidence types may help distinguish curated molecular associations from computationally predicted candidates and prioritize targets for further investigation. In this study, molecular evidence associated with 6-gingerol was comparatively characterized by integrating curated chemical–gene associations from CTD, retrieved under the database-defined chemical identifier C007845 (gingerol), with SwissTargetPrediction results generated specifically for 6-gingerol (PubChem CID 442793). Because the two resources represent related but non-equivalent evidence types and chemical records, the analysis was considered hypothesis-generating and was not intended to establish direct target engagement, therapeutic efficacy, or clinical relevance.
  • Methods: Methods The identity and chemical structure of 6-gingerol (PubChem CID 442793) were verified using PubChem and used as the compound input for SwissTargetPrediction. Curated chemical–gene associations were obtained from the Comparative Toxicogenomics Database (CTD) using chemical identifier C007845 (gingerol). This CTD identifier was retained to preserve the database-defined source record, whereas PubChem CID 442793 was used to specify the chemical structure of 6-gingerol for computational target prediction. The CTD dataset was examined for unique associated genes, the direction of reported chemical–gene associations, and database-reported Gene Ontology (GO) and pathway enrichment. Potential protein targets were predicted for Homo sapiens using SwissTargetPrediction. A probability score of ≥0.7 was adopted a priori as a pragmatic prioritization threshold, consistent with a previously published network-pharmacology workflow. This threshold was used to prioritize higher-scoring predictions and was not interpreted as an experimentally validated probability of binding or target engagement. Of the 100 predicted human targets, 19 had SwissTargetPrediction probability scores ≥0.7. Gene-level overlap between the 19 higher-scoring predicted targets and the unique genes in the CTD gingerol record was then assessed using the reported gene identifiers. Shared identifiers were considered cross-resource overlapping candidates. No molecular docking, molecular dynamics, protein–protein interaction analysis, machine learning, or experimental validation was performed.
  • Results: Results The CTD dataset retrieved under C007845 (gingerol) contained 83 unique associated genes. Database-reported enrichment included apoptosis (corrected P = 1.75 × 10⁻⁵¹), response to chemical stimulus (P = 6.92 × 10⁻⁶²), intracellular signal transduction (P = 6.33 × 10⁻⁵⁶), and cellular response to stress (P = 4.34 × 10⁻⁴⁹). Cancer-associated pathways included pathways in cancer (hsa05200, corrected P = 1.13 × 10⁻⁴⁵), apoptosis (hsa04210, P = 2.91 × 10⁻³²), p53 signaling (hsa04115, P = 3.31 × 10⁻²⁷), PI3K-Akt signaling (hsa04151, P = 9.51 × 10⁻¹⁹), and HIF-1 signaling (hsa04066, P = 3.36 × 10⁻¹⁴). Reported curated associations included increased associations involving BAX, CASP3, CASP8, TP53, and APAF1, and decreased associations involving BCL2, BIRC5, XIAP, and CFLAR in the corresponding experimental contexts. SwissTargetPrediction generated 100 candidate human protein targets, of which 19 had probability scores ≥0.7. The highest-scoring candidates included HTR1A (0.994), ALOX5 (0.960), CA2 (0.937), CA1 (0.937), CA9 (0.920), CA12 (0.920), TRPA1 (0.850), HSD11B1 (0.833), and PPARG (0.802). Comparison of the 19 higher-scoring predicted targets with the 83 genes associated with the CTD gingerol record identified two shared gene identifiers, PPARG and PTGES. These represented 2/19 (10.5%) of the higher-scoring predicted targets and 2/83 (2.4%) of the CTD-associated genes. PPARG had a SwissTargetPrediction probability score of 0.802, while its CTD evidence was reported in Mus musculus. PTGES had a probability score of 0.737, with CTD evidence reported in Homo sapiens.
  • Conclusion: Conclusion Integration of the CTD gingerol record and SwissTargetPrediction results identified 83 unique genes associated with the CTD record, 100 predicted human protein targets, and 19 targets with SwissTargetPrediction probability scores ≥0.7. PPARG and PTGES were the only shared gene identifiers between the two datasets. These findings provide a hypothesis-generating framework for prioritizing molecular candidates potentially relevant to biological and cancer-associated effects reported for gingerol-related compounds. However, the observed overlap represents cross-resource overlap rather than direct target validation, particularly because the CTD record corresponds to database-defined gingerol (C007845) whereas the computational analysis specifically used 6-gingerol (PubChem CID 442793). Independent biochemical, cellular, and mechanistic studies are therefore required to determine whether these candidates are directly involved in the molecular actions of 6-gingerol.
  • Keywords: Keywords 6-Gingerol; PubChem CID 442793; Comparative Toxicogenomics Database; SwissTargetPrediction

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