Van-Thinh To

Van-Thinh To

Erasmus Mundus double-degree master's student
Bioinformatics, University Paris Cite; Chemistry, University of Milan

van-thinh.to [AT] etu.u-paris.fr

About me

I am a double-degree master's student in Bioinformatics at University Paris Cite and Chemistry at the University of Milan. I previously completed a five-year Bachelor of Pharmacy at the University of Medicine and Pharmacy at Ho Chi Minh City. My research interests are cheminformatics and bioinformatics, with a particular emphasis on computer-aided drug design (CADD), QSAR modeling, generative models, fragment-based drug design, virtual screening, scoring functions, and docking.

Publications

Selected publications are highlighted below. A fuller and usually more current list is available on Google Scholar. ‡ indicates equal contribution.

KITE: Knowledge-Infused Transformer Encoder for Molecular Property Prediction

Nguyen, H.-H.‡, To, V.-T.‡, Truong, T. N., and Phan, T.-L.

ChemRxiv (preprint). 2026.

Paper

Enhancing Virtual Screening of Cystathionine beta-Synthase Inhibitors: Benchmarking Target-Specific Machine-Learning Scoring Functions Against State-of-the-Art AI Docking and Co-Folding Approaches

Truong, C.-M., To, V.-T., Janel, N., Dairou, J., Ballester, P. J., Taboureau, O., and Tran-Nguyen, V.-K.

Journal of Cheminformatics. 2026.

Paper

SynCat: molecule-level attention graph neural network for precise reaction classification

Van Nguyen, P.-C., To, V.-T., Tran, N.-V. N., Phan, T.-L., Truong, T. N., Gartner, T., Merkle, D., and Stadler, P. F.

Digital Discovery. 2026.

Paper

ProQSAR: A Modular and Reproducible Framework for Small-Data QSAR Modeling with Fit-and-Use Models

Phan, T.-M., Phan, T.-L., Van-Nguyen, P.-C., Le, H. S. L., To, V.-T., Truong, T. N., Merkle, D., and Stadler, P. F.

Journal of Cheminformatics. 2026.

Paper

KGG: Knowledge-Guided Graph Self-Supervised Learning to Enhance Molecular Property Predictions

To, V.-T., Van Nguyen, P.-C., Truong, G.-B., Phan, T.-M., Phan, T.-L., Fagerberg, R., Stadler, P. F., and Truong, T. N.

Journal of Chemical Information and Modeling. 2025.

Paper

Synergy of advanced machine learning and deep neural networks with consensus molecular docking for virtual screening of anaplastic lymphoma kinase inhibitors

Trinh, T.-C., Phan, T.-L., To, V.-T., Pham, T.-A., Truong, G.-B., Le, H. S. L., Tran, X.-T. D., and Truong, T. N.

Journal of Computer-Aided Molecular Design. 2025.

Paper

Novel machine learning approach toward classification model of HIV-1 integrase inhibitors

Phan, T.-L., To, V.-T., Pham, T.-A., Van Nguyen, P.-C., Phan, T.-M., and Truong, T. N.

RSC Advances. 2024.

Paper

Integration of the Butina algorithm and ensemble learning strategies for the advancement of a pharmacophore ligand-based model: an in silico investigation of apelin agonists

Tran, X.-T. D., Phan, T.-L., To, V.-T., Tran, N.-V. N., Nguyen, N.-N. S., Nguyen, D.-N. H., Tran, N.-T. N., and Truong, T. N.

Frontiers in Chemistry. 2024.

Paper

Discovery of Vascular Endothelial Growth Factor Receptor 2 Inhibitors Employing Junction Tree Variational Autoencoder with Bayesian Optimization and Gradient Ascent

Truong, G.-B., Pham, T.-A., To, V.-T., Le, H.-S. L., Van Nguyen, P.-C., Trinh, T.-C., Phan, T.-L., and Truong, T. N.

ACS Omega. 2024.

Paper

Innovative virtual screening of PD-L1 inhibitors: the synergy of molecular similarity, neural networks and GNINA docking

To, V.-T., Phan, T.-L., Doan, B.-V. N., Nguyen, P.-C. V., Le, Q.-H. N., Nguyen, H.-H., Trinh, T.-C., and Truong, T. N.

Future Medicinal Chemistry. 2024.

Paper

A graph neural network model enables accurate prediction of anaplastic lymphoma kinase inhibitors compared to other machine learning models

Trinh, T.-C., Phan, T.-L., To, V.-T., Truong, G.-B., Pham, T.-A., Le, H. S. L., Van Nguyen, P.-C., and Truong, T. N.

15th International Conference on Knowledge and Systems Engineering. 2023.

Paper

CV

My training combines pharmacy, bioinformatics, chemistry, and machine learning for computer-aided drug discovery. I am currently an Erasmus Mundus scholar in a double-degree master's program at University Paris Cite and the University of Milan. Before that, I completed a Bachelor of Pharmacy at the University of Medicine and Pharmacy at Ho Chi Minh City, with thesis work on knowledge-guided graph self-supervised learning for molecular property prediction.

CV page Download PDF

Mentorship

Bachelor students

2025-2026

Nguyen Hoang Huy

Project themes: MolKite: Knowledge-Infused Transformer Encoder for Molecular Property Prediction.

Blog

I will use this section for short notes on computer-aided drug discovery, the CADD ecosystem, and practical translation of AI-enabled drug discovery for Vietnam.

Computer-aided drug discovery workflows

Notes on practical CADD pipelines, including QSAR modeling, docking, virtual screening, molecular representation learning, and reproducible cheminformatics workflows.

The CADD market and innovation landscape

Reflections on drug discovery start-ups, platform companies, software vendors, and how scientific methods move from research prototypes into deployable products.

AI for healthcare and drug discovery in Vietnam

Ideas on how AI, CADD, and data-centric biomedical research can be adapted to local healthcare needs, education, and research infrastructure in Vietnam.