Best Researcher Award

Phuong-Thao Tran
Hanoi University of Pharmacy, Vietnam

Phuong-Thao Tran is a researcher at Hanoi University of Pharmacy, Vietnam, whose work centers on medicinal chemistry and the discovery of compounds relevant to neurodegenerative disorders, particularly Alzheimer’s disease.[1] This article presents her profile in the context of the Best Researcher Award at the International Academic Achievements & Awards event.

Abstract

Phuong-Thao Tran is a medicinal chemistry researcher affiliated with Hanoi University of Pharmacy. Her publications address the design and evaluation of enzyme inhibitors for Alzheimer’s disease, including inhibitors of human glutaminyl cyclase and acetylcholinesterase, together with related studies in cancer biology.[2] With 51 indexed documents and 660 citations, her record reflects sustained and recognized scholarly activity in drug discovery.

Keywords

Medicinal chemistry, Alzheimer’s disease, neurodegenerative disorders, glutaminyl cyclase inhibitors, acetylcholinesterase, structure–activity relationship, computational drug design.

Introduction

Neurodegenerative disorders, especially Alzheimer’s disease, remain among the most difficult challenges in modern therapeutics. Medicinal chemists contribute by identifying molecular targets and designing compounds that can modulate them. Phuong-Thao Tran works in this field at Hanoi University of Pharmacy, combining synthetic chemistry, structure–activity analysis and computational approaches.[1] Her work has appeared in journals such as the Journal of Medicinal Chemistry, Bioorganic & Medicinal Chemistry, ACS Omega and Cancers.

Research Profile

According to Scopus, the researcher’s author record (ID 55908125500) includes 51 documents, 660 citations and an h-index of 17.[1] Her principal subject areas are medicinal chemistry and neurodegenerative disorders, with a particular emphasis on Alzheimer’s disease. Her ORCID record provides a further public listing of her scholarly outputs.[5]

Research Contributions

Her contributions can be grouped into several themes:

• Glutaminyl cyclase inhibitors. Rational design of potent human glutaminyl cyclase inhibitors as candidate anti-Alzheimer’s agents, together with structure–activity studies of inhibitors built on an imidazolyl propyl thiourea template.[2][3]
• Acetylcholinesterase studies. Computational and experimental work on predicting ligand affinity and identifying possible inhibitors through umbrella sampling and machine learning.[4]
• Cancer biology. A review of the emerging role of circulating tumor cells in gastric cancer, indicating a broader biomedical scope.

Publications

Selected highly cited publications, with citation counts as listed in the supplied profile data, include:

• “Discovery of potent human glutaminyl cyclase inhibitors as anti-Alzheimer’s agents based on rational design,” Journal of Medicinal Chemistry 60(6), 2573–2590 (2017); 64 citations.[2]
• “Emerging role of circulating tumor cells in gastric cancer,” Cancers 12(3), 695 (2020); 60 citations.
• “Structure Activity Relationship of Human Glutaminyl Cyclase Inhibitors Having an N-(5-Methyl-1H-imidazol-1-yl)propyl Thiourea Template,” Bioorganic & Medicinal Chemistry (2013); 45 citations.[3]
• “Prediction of AChE-ligand affinity using the umbrella sampling simulation,” Journal of Molecular Graphics and Modelling 93, 107441 (2019); 43 citations.
• “Identifying possible AChE inhibitors from drug-like molecules via machine learning and experimental studies,” ACS Omega 7(24), 20673 (2022); 35 citations.[4]

Research Impact

The researcher’s impact is reflected in citation metrics and in the longevity of her work. Publications from 2013 to 2022 continue to attract citations, and the most cited paper, on glutaminyl cyclase inhibitors, has 64 citations.[1] An h-index of 17 indicates that at least 17 of her documents have each been cited at least 17 times. Her combination of experimental and computational methods also supports the reuse of her findings in later drug-design studies.

Award Suitability

The Best Researcher Award at the International Academic Achievements & Awards event recognizes researchers with significant scholarly contributions.[5] Phuong-Thao Tran’s profile aligns with such criteria through:

• A focused research agenda in medicinal chemistry and Alzheimer’s disease therapeutics.
• A publication record in peer-reviewed international journals.
• Citation indicators of 660 citations and an h-index of 17.
• Methodological breadth spanning synthesis, structure–activity analysis and computational modelling.

Conclusion

Phuong-Thao Tran of Hanoi University of Pharmacy has built a research record centered on the discovery of enzyme inhibitors relevant to Alzheimer’s disease. Her publications, citation metrics and methodological range support her nomination for the Best Researcher Award at the International Academic Achievements & Awards event.[1]

External Links

• Scopus Profile
• Google Scholar
• ORCID Profile

References

1. Elsevier. (n.d.). Scopus author details: Phuong-Thao Tran, Author ID 55908125500. Scopus.
   https://www.scopus.com/authid/detail.uri?authorId=55908125500
2. Hoang, V. H., Tran, P. T., Cui, M., Ngo, V. T. H., Ann, J., Park, J., Lee, J., Choi, K., Cho, H., et al. (2017). Discovery of potent human glutaminyl cyclase inhibitors as anti-Alzheimer’s agents based on rational design. Journal of Medicinal Chemistry, 60(6), 2573–2590.
   https://pubmed.ncbi.nlm.nih.gov/28234463/
3. Tran, P. T., Hoang, V. H., Thorat, S. A., Kim, S. E., Ann, J., Chang, Y. J., Nam, D. W., et al. (2013). Structure activity relationship of human glutaminyl cyclase inhibitors having an N-(5-methyl-1H-imidazol-1-yl)propyl thiourea template. Bioorganic & Medicinal Chemistry.
   https://doi.org/10.1016/j.bmc.2013.08.027
4. Nguyen, T. H., Tran, P. T., Pham, N. Q. A., Hoang, V. H., Hiep, D. M., & Ngo, S. T. (2022). Identifying possible AChE inhibitors from drug-like molecules via machine learning and experimental studies. ACS Omega, 7(24), 20673.
   https://doi.org/10.1021/acsomega.2c01341
5. ORCID. (n.d.). Phuong-Thao Tran (ORCID iD 0000-0003-4855-2544). ORCID.
   https://orcid.org/0000-0003-4855-2544