Curriculum vitae

Education

• 2010-2013: Baccalaureate, High school for the gifted.
• 2013-2018: B.S. in Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh city.
• 2020-2022: MSc. in Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh city.
  • GPA: 8.68/10 - ranking 1%
  • Thesis: In silico modeling for prediction of potential HIV integrase inhibitors - Grade: 9.6/10
• 2023+: PhD Candidate TACys Program .

Work experience

• 2018 - now: Research Assistant - Organic Chemistry Department
  • Methodology development
    • MolUtil: molecular standardization, featurization, medicinal chemistry filtration, and chemical space visualization (incorporate with RDKit)
    • mlqsar: QSAR-machine learning pipeline development incorporate with post hoc Wilcoxon for decision making
    • MolAD: applicability domains detection with convex hull
    • MoleculeClustering: molecules clustering with Butina algorithms and diverse subsets selection
    • MolPh4: pharmacophore validation, statistical comparison (Wilcoxon); ensemble pharmacophore development
    • DockValid: automated result extraction and validation (retrospective control-ROC plot)
    • Mol2DSimi: molecular similarity searching, validation, and comparison between different fingerprints
  • Application of AI methods in drug discovery
    • HIV-1 integrase (Master thesis): QSAR pipeline for data type selection and model building, pharmacophore modeling with ensemble methods, alphafold2 for protein curation and benchmarking molecular docking packages (Vina, Smina, Qvina2, Vina GPU, Autodock GPU)
    • SGLT2i: comparison between MACCs and ECFP4 in QSAR model, pharmacophore optimization by query threshold
    • PD-1/PD-L1 immune checkpoint: similarity comparison among MACCs, ECFP4 and RDK5; similarity searching
  • Supervisor for undergraduate students’ thesis
    • Tubulin: prediction of protein-ligand interaction using graph neural networks; molecular dynamics (Gromacs)
    • ALK: ANN model development, 3D-Image-QSAR using CNN with 6 times rotation, GNN with pytorch geometric
    • VEGF: QSAR model development integrated into JT-VAE network for molecules optimizaztion
    • Apelin: Comparative study of molecular similarity and pharmacophore targeting Apelin
• 2016 - 2018: Research internship - Organic Chemistry Department
  • Duties included:
    • Experienced in silico techniques by collaborating in lab seminars and academic projects.
    • Collaborated with labmates to conduct 2D-QSAR utilizing MOE software to screen anticancer bioactivities of some isothiocyanate derivates.
    • Performed FlexX and Autodock Vina for CDK2 protein (PDB ID: 2C4G), interaction analysis.
  • Supervisor: Assoc.Prof.Truong Ngoc Tuyen, PhD

Supervision of undergraduate students

• In progress
  • D18
    1. The Chuong Trinh: Develop machine learning model, feed forward neural network, 3D image based convolutional neural network and graph neural network targeting ALK protein
    2. Hoang Son Le Lai: Perform, compare performance of six molecular docking tools and develop graph neural networks to predict potential interaction between ligands and Tubulin receptor
    3. Gia Bao Truong: Optimize molecules targeting VEGFR using variation autoencoder
    4. Xuan Truc Tran Dinh: Perform and compare performance of similarity searching and traditional pharmacophore using ensemble learning.
  • D19
    1. Thinh Van To: Develop molecular representation using 3D-CNN incorporating graph neural networks.
    2. Thanh An Pham: Develop molecular docking tools incorporating graph neural networks to predict conformation of ligands interacting with protein.
    3. Phuoc Chung Nguyen Van: Enhance reaction yield using bayesian optimization.
• Completed
  • D17
    1. Bao Vy Doan Ngoc: Application of molecular similarity, machine learning and molecular docking method for PD-L1 inhibitors virtual screening.
    2. Tuyet Minh Phan : Machine learning models development to screen HIV integrase inhibitors followed with total synthesis and in vitro evaluation.
    3. Hoai Phuong Nguyen Thi: In silico study of SGLT2 inhibitors from classical to applied machine learning.
    4. Ha My Dao Nguyen: Application of pharmaceutical chemistry filter funnel and molecular docking model to screen for STAT3 inhibitors from derivatives of Cucurbitacin E.

Skills

• Programming: Python, C++, Linux, Git, OOP
• Cheminformatics: RDKit, MOE, Pymol, Autodock, Gromacs, VMD
• Data science
  • Data analysis: visualization (seaborn, matplotlib, plotly), linear algebra, calculus, probability and statistics (numpy, pandas)
  • Data mining: data pipeline development including handle low variance features, missing values, univariate and multivariate outliers; conduct statistical test for decision making in model selection using cross-validation
  • Machine learning: scikit-learn, imblearn, XGBoost, CatBoost, optimization (grid search and bayesian search)
  • Deep Learning: Pytorch, Tensorflow, Keras, CNNs, RNNs, GNN.
• Process Automation
• Personal skill: Problem solving, crictical thinking, communication

Language

• English: Full Professional Proficiency - IELTS 7.5
• Japanese: Professional Working Proficiency - JPLT N3

Course

1. Python for developers - VTC Academy
2. AI specialist and machine enygineer - VTC Academy

Teaching

Cheminformatics

Molecular Docking

Deep Learning

Molecular Docking Colab

Publications

Application of machine learning in virtual screening of HIV integrase inhibitors

Tieu Long Phan, Xuan Truc Tran Dinh, The Chuong Trinh, Hoang Son Le Lai, Ngoc Tuyen Truong (2022). Application of machine learning in virtual screening of HIV integrase inhibitors - Vietnamese Pharmacy Journal, 506, 21-25.

Design, synthesis, antimicrobial evaluations and in silico studies of novel pyrazol-5(4H)-one and 1H-pyrazol-5-ol derivatives

Em, P. C., L. T. Tuong Vi, T. P. Long, T. N. Huong-Giang, N. B. L. Khanh, and N. T. Tuyen. "Design, synthesis, antimicrobial evaluations and in silico studies of novel pyrazol-5 (4H)-one and 1 H-pyrazol-5-ol derivatives." Arab. J. Chem 15 (2022): 103682.

Study on the effect of molecular fingerprints on the performance of machine learning model predicting hiv integrase bioactivty

Tieu Long Phan, Thanh An Pham, Bao Vy Doan Ngoc, Hoang Son Le Lai, Ngoc Tuyen Truong (2023). Study on the effect of molecular fingerprints on the performance of machine learning model predicting HIV integrase bioactivty. Vietnamese Pharmacy Journal (Accepted).

Application of medicinal chemistry filtration and molecular docking in selecting STAT3 inhibitors from CUCURBITACIN E derivatives

Tieu Long Phan, Anh Hao Huynh, Nhu Ngoc Nguyen Song, Dong Nghi Nguyen Hoang, Ngoc Tam Chan Nguyen, Ngoc Tuyen Truong (2023). Application of medicinal chemistry filtration and molecular docking in selecting STAT3 inhibitors from CUCURBITACIN E derivatives. Vietnamese Pharmacy Journal (Accepted).

Honours

• 2018 - Best poster presentation - “Synthesis, biological activity evaluations of some N-alkyl/ aryl-2-aryl benzimidazole”- Pharmaceutical sciences and Technology conference.
• 2013 - Silver medal for Vietnamese Chemistry Olympiad (top 32, member of bootcam for ICho)
• 2012 - Gold medal in 30/4 Chemistry Olympiad of southern Vietnam

References

• Assoc.Prof.Truong Ngoc Tuyen, PhD
  • Position: Head of Department of Organic Chemistry, Pharmacy Faculty, University of Medicine and pharmacy at Ho Chi Minh city
  • Email: truongngoctuyen@ump.edu.vn
• Assoc.Prof. Tran Nguyen Minh An, PhD
  • Position: Vice Dean of Chemical Technology Faculty, Industrial University of Ho Chi Minh city
  • Email: trannguyenminhan@iuh.edu.vn