Evidence map›Paper›PMID 40679956›Full record

ArticlePloS one2025

Targeted modulation of MMP9 and GRP78 via molecular interaction and in silico profiling of Curcuma caesia rhizome metabolites: A computational drug discovery approach for cancer therapy.

Mahek Desai, Soham Bhattacharya, Saurabhkumar Mehta, Kaushiki Joshi, Mitesh B Solanki, Trilok Akhani, Iva Viehmannová, Eloy Fernández Cusimamani

Erratum issuedAbstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Mahek DesaiDepartment of Life Sciences, Parul Institute of Applied Sciences, Parul University, Waghodia, Vadodara, Gujarat, India.ORCID https://orcid.org/0009-0008-1400-9969
Soham BhattacharyaDepartment of Agroecology and Crop Production, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Suchdol, Czech Republic.ORCID https://orcid.org/0000-0001-5998-4751
Saurabhkumar MehtaDepartment of Life Sciences, Parul Institute of Applied Sciences, Parul University, Waghodia, Vadodara, Gujarat, India.ORCID https://orcid.org/0009-0007-6645-1962
Kaushiki JoshiDepartment of Life Sciences, Parul Institute of Applied Sciences, Parul University, Waghodia, Vadodara, Gujarat, India.ORCID https://orcid.org/0009-0002-3853-3438
Mitesh B SolankiDepartment of Physics, Parul Institute of Applied Sciences, Parul University, Waghodia, Vadodara, Gujarat, India.ORCID https://orcid.org/0000-0002-4019-0203
Trilok AkhaniDepartment of Physics, Parul Institute of Applied Sciences, Parul University, Waghodia, Vadodara, Gujarat, India.ORCID https://orcid.org/0000-0002-3489-1708
Iva ViehmannováDepartment of Crop Sciences and Agroforestry, Faculty of Tropical AgriSciences, Czech University of Life Sciences Prague, Suchdol, Czech Republic.
Eloy Fernández CusimamaniDepartment of Crop Sciences and Agroforestry, Faculty of Tropical AgriSciences, Czech University of Life Sciences Prague, Suchdol, Czech Republic.ORCID https://orcid.org/0000-0001-7835-9310

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer remains a leading cause of mortality worldwide, with conventional therapies showing limited efficacy and high toxicity. The increasing incidence and therapeutic resistance necessitate alternative strategies. In this regard, phytochemicals have emerged as potential sources of developing safer and novel anti-cancer agents. This study employs a structure-based drug design approach, integrating molecular docking, molecular dynamics (MD) simulations, and in silico profiling, to investigate the anti-cancer potential of metabolites from Curcuma caesia rhizomes. The research targets key cancer-associated proteins, Matrix Metalloproteinase-9 (MMP9) and Glucose-Regulated Protein 78 (GRP78), identified through expression analysis, functional network mapping, and pathway enrichment as critical mediators of cancer progression and metastasis. A comprehensive molecular docking analysis of 101 bioactive compounds from C. caesia rhizomes identified curcumin and bis-demethoxycurcumin as promising candidates, demonstrating high binding affinities and stable interactions with MMP9 and GRP78. MD simulations further validated the stability and robustness of these interactions under dynamic physiological conditions. Pharmacological profiling, including ADMET analysis, Lipinski's rule compliance, and bioactivity scoring, revealed favorable drug-like properties for both compounds, including strong absorption, distribution, low toxicity, and potential therapeutic activities such as enzyme inhibition and nuclear receptor-mediated processes. KEGG pathway enrichment analysis confirmed their involvement in key biological pathways linked to cancer progression, underscoring their therapeutic potential. The findings highlight curcumin and bis-demethoxycurcumin as promising phytochemical candidates for cancer therapy, capable of modulating MMP9 and GRP78 to suppress tumor progression. While these results provide a solid basis for their therapeutic potential, further experimental studies and clinical trials are crucial to confirm their efficacy and safety for human applications.

Indexed as

Antineoplastic Agents, PhytogenicCurcumaDrug DiscoveryHeat-Shock ProteinsMatrix Metalloproteinase 9NeoplasmsRhizomeCurcuminDiarylheptanoidsEndoplasmic Reticulum Chaperone BiPHumansMolecular Docking SimulationMolecular Dynamics SimulationAntineoplastic Agents, PhytogenicCurcumindemethoxycurcuminDiarylheptanoidsEndoplasmic Reticulum Chaperone BiPHeat-Shock ProteinsHSPA5 protein, humanMatrix Metalloproteinase 9MMP9 protein, human

Identifiers

PMID40679956
PMCPMC12273913

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.