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All Journal Journal of Tropical Life Science : International Journal of Theoretical, Experimental, and Applied Life Sciences
Mohd Nasir, Mohd Hamzah
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Agriculture, Biological Sciences & Forestry Environmental Science

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Three-Dimensional Structure of Human Epididymis Protein 4 (HE4): A Protein Modelling of an Ovarian Cancer Biomarker Through In Silico Approach: HE4 Protein Structure Modelling and Validation Abdul Rashid, Nur Nadiah; Mohd Nasir, Mohd Hamzah; Hamzah, Nurasyikin; Ismail, Che Muhammad Khairul Hisyam; Nor Hishamuddin, Siti Aishah Sufira; Mohamed Suffian, Izzat Fahimuddin; Abdul Hamid, Azzmer Azzar
Journal of Tropical Life Science Vol. 14 No. 2 (2024)
Publisher : Journal of Tropical Life Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/jtls.14.02.13

Abstract

The Human Epididymis Protein 4 (HE4) biomarker has been extensively investigated for its potential in diagnosing ovarian cancer (OC). For the application of diagnostic techniques and drug delivery, it is crucial to understand the protein tertiary structure. However, the Protein Data Bank (PDB) does not currently contain the three-dimensional (3D) structure of HE4. Therefore, an in silico analysis was conducted to model the HE4 protein using AlphaFold, I-TASSER, and Robetta servers, with the sequence retrieved from UniProt (ID: Q14508). These three servers employed deep learning algorithms, threading templates, and de novo methods, respectively. Subsequently, Molecular Dynamics (MD) simulation using the GROMACS software package improved each 3D structure model, resulting in optimised and refined structures: RF1, RF2, and RF3. PROCHECK and ERRAT programmes were employed to assess the structure quality. The Ramachandran plots from PROCHECK indicated that 100% of residues were within the allowed regions for all servers except for I-TASSER. For the refined structures, RF1 and RF3, all residues were concentrated within the allowed regions. According to the ERRAT programme, the RF1 model exhibited the highest overall quality factor of 97.701, followed by RF3 and AlphaFold models with scores of 94.643 and 93.750, respectively. After these validations, RF1 emerged as the most accurately predicted 3D structure of HE4 and has one tunnel identified by CAVER 3.0 tool that facilitates the transportation of small particles to the active site, supported by FTsite and PrankWeb binding site predictions. This model holds potential for various computational studies, including the development of OC diagnostic kits. It will enhance our comprehension of the interactions between the protein and other biomolecules.
Three-Dimensional Structure of Human Epididymis Protein 4 (HE4): A Protein Modelling of an Ovarian Cancer Biomarker Through In Silico Approach: HE4 Protein Structure Modelling and Validation Abdul Rashid, Nur Nadiah; Mohd Nasir, Mohd Hamzah; Hamzah, Nurasyikin; Ismail, Che Muhammad Khairul Hisyam; Nor Hishamuddin, Siti Aishah Sufira; Mohamed Suffian, Izzat Fahimuddin; Abdul Hamid, Azzmer Azzar
Journal of Tropical Life Science Vol. 14 No. 2 (2024)
Publisher : Journal of Tropical Life Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/jtls.14.02.13

Abstract

The Human Epididymis Protein 4 (HE4) biomarker has been extensively investigated for its potential in diagnosing ovarian cancer (OC). For the application of diagnostic techniques and drug delivery, it is crucial to understand the protein tertiary structure. However, the Protein Data Bank (PDB) does not currently contain the three-dimensional (3D) structure of HE4. Therefore, an in silico analysis was conducted to model the HE4 protein using AlphaFold, I-TASSER, and Robetta servers, with the sequence retrieved from UniProt (ID: Q14508). These three servers employed deep learning algorithms, threading templates, and de novo methods, respectively. Subsequently, Molecular Dynamics (MD) simulation using the GROMACS software package improved each 3D structure model, resulting in optimised and refined structures: RF1, RF2, and RF3. PROCHECK and ERRAT programmes were employed to assess the structure quality. The Ramachandran plots from PROCHECK indicated that 100% of residues were within the allowed regions for all servers except for I-TASSER. For the refined structures, RF1 and RF3, all residues were concentrated within the allowed regions. According to the ERRAT programme, the RF1 model exhibited the highest overall quality factor of 97.701, followed by RF3 and AlphaFold models with scores of 94.643 and 93.750, respectively. After these validations, RF1 emerged as the most accurately predicted 3D structure of HE4 and has one tunnel identified by CAVER 3.0 tool that facilitates the transportation of small particles to the active site, supported by FTsite and PrankWeb binding site predictions. This model holds potential for various computational studies, including the development of OC diagnostic kits. It will enhance our comprehension of the interactions between the protein and other biomolecules.
Ferula assafoetida as a Multi-Target Therapeutic Candidate for Parkinson's Disease: A Narrative Review Selvaraju, Anusia; Mahat, Naji Arafat; Jemon, Khairunadwa; Mohd Nasir, Mohd Hamzah; Abdul Hamid, Azzmer Azzar; Mohamed Huri, Mohamad Afiq
Journal of Tropical Life Science Vol. 16 No. 2 (2026)
Publisher : Journal of Tropical Life Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/jtls.16.02.01

Abstract

Parkinson’s disease (PD) presents a complex challenge in neurodegenerative research due to the persistent lack of disease-modifying therapies, prompting exploration of natural compounds with multi-target capabilities to modulate multiple pathways. Hence, this review evaluates the therapeutic potential of the ayurvedic plant, Ferula assafoetida, as a candidate for PD treatment. The phytochemical profile of F. assafoetida, rich in bioactive sulfur volatiles, phenolic acids, coumarins, and terpenes, aligns with mechanisms implicated in PD pathogenesis, including oxidative stress, inflammation, and mitochondrial dysfunction. Critically, recent activity-guided isolation studies have successfully identified specific sesquiterpene coumarins, such as karatavicinol and farnesiferol C, as potent monoamine oxidase-B (MAO-B) inhibitors, demonstrating efficacy in ameliorating motor deficits and protecting dopaminergic neurons in a murine 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) model of PD. This breakthrough provides the first direct experimental evidence for F. assafoetida in a PD model, transitioning its status from a traditional remedy to a source of validated, bioactive lead compounds. While mammalian models offer crucial translational validation, zebrafish, with their conserved dopaminergic pathways, genetic tractability, and suitability for high-throughput screening, emerge as an ideal complementary platform for accelerating future research. Advanced phytochemical profiling, integrating chromatographic methods and in silico molecular docking, could prioritize lead compounds for further investigation. The integration of gene expression analysis in zebrafish models, alongside behavioral assays, enables a comprehensive understanding of the impact of this plant on PD-related pathways. This pertinent evidence now positions F. assafoetida as a viable preclinical candidate. Future research should prioritize chemical standardization across different plant sources and in vivo mechanistic studies in zebrafish. By illustrating the synergy between phytochemistry and innovative model systems, this review lays the groundwork for exploring F. assafoetida as a promising candidate for novel PD therapies and related neurodegenerative disorders.
Co-Authors Abdul Hamid, Azzmer Azzar Abdul Rashid, Nur Nadiah Hamzah, Nurasyikin Ismail, Che Muhammad Khairul Hisyam Jemon, Khairunadwa Mahat, Naji Arafat Mohamed Huri, Mohamad Afiq Mohamed Suffian, Izzat Fahimuddin Nor Hishamuddin, Siti Aishah Sufira Selvaraju, Anusia