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Viet Khoa TRAN NGUYEN

MCF Université Paris Cité

viet-khoa.tran-nguyen@u-paris.fr

 

Assistant Professor in Cheminformatics at Université Paris Cité, France since September 2023

Nationality: French, Vietnamese

Postal address: Bâtiment Lamarck A, 35 rue Hélène Brion, 75013 Paris, France

Email addresses: viet-khoa.tran-nguyen@u-paris.fr

LinkedIn: www.linkedin.com/in/viet-khoa-tran-nguyen

ResearchGate: www.researchgate.net/profile/Viet_Khoa_Tran-Nguyen

GitHub: github.com/vktrannguyen   

ORCID: 0000-0001-7497-333X

 

DIPLOMAS

2020                            Doctoral degree in Cheminformatics-Theoretical Chemistry

                                    University of Strasbourg, France

                                    Two PhD thesis prizes from the Foundation for Research in Chemistry and the French Society of Cheminformatics

2017                            Master’s degree in Medicinal Chemistry and Innovations in Pharmacology

                                    Grenoble Alpes University, France – GPA: 16.946/20; Ranking: 1st/12; Grade: Very Good

2016                            National Pharmacist degree

                                    University of Medicine and Pharmacy of Ho Chi Minh City, Vietnam – GPA: 8.12/10; Grade: Very Good

 

PROFESSIONAL EXPERIENCE

Sep 2023 – present: Assistant Professor (MCF)

Department of Life Sciences, Faculty of Sciences, Université Paris Cité, France

Research project: Application of machine-learning algorithms and data integration in drug design/drug discovery

Project overview:

• A new support vector machine model, called “ClassyPose,” was developed to predict native and near-native target-bound conformations of docked molecules, and was proven effective as a pose selection tool in various virtual screening tasks. An article presenting this model (as 1st and co-corresponding author) was published in Advanced Intelligent Systems, and a possible extension of “ClassyPose” is being planned.

• Experimental bioactivity data from PubChem and ChEMBL are being processed to develop ligand-based and structure-based machine-learning models/scoring functions for bioactivity prediction. These models will be used in virtual screening campaigns to explore polypharmacological profiles of drug-like molecules.

Teaching duty:

Cheminformatics and bioinformatics courses for Master’s students (1st year and 2nd year, in English and in French): structural analysis of protein structures and ligand-protein interactions; structural fingerprints; pharmacophores; molecular docking; principal component analysis; virtual screening in drug design/drug discovery.

Oct 2021 – Aug 2023: Post-Doctoral Fellow

Cancer Research Center of Marseille, Paoli-Calmettes Institute, INSERM, France

Research project: Development and evaluation of target-specific machine-learning scoring functions used in virtual screening/drug discovery

Project overview:

• A detailed protocol to design a benchmarking data set for a particular therapeutic target, to train and evaluate machine-learning scoring functions specific to that target was established.

• Data from various public repositories were retrieved and processed: PubChem, ChEMBL, Protein Data Bank; including small molecules tested in vitro on the target, and the target’s X-ray 3D structure(s).

• Various scoring functions used in structure-based virtual screening were investigated.

• Various supervised learning algorithms were involved: random forest, support vector machine, artificial neural network, etc.

• Diverse molecular modeling/cheminformatics programs were involved: Smina (docking), Chimera and Open Babel (structure-processing), etc.

• Bash scripts and Python code/Jupyter notebooks were used to execute the steps of the protocol (available on GitHub).

• Three manuscripts issued from this project (all 1st-authored) were published in Nature ProtocolsJournal of Chemical Information and Modeling and Current Research in Structural Biology.

Sep 2020 – Aug 2021: Temporary Lecturer-Researcher

Laboratory of Therapeutic Innovations (UMR 7200), Faculty of Pharmacy, University of Strasbourg, France

Research project: Evaluation of scoring functions on an unbiased pharmaco-chemical database

Project overview:

• One classical, one interaction-based, and two generic machine-learning scoring functions were tested on the LIT-PCBA data sets.

• Bash scripts were written to execute virtual screening jobs and evaluate screening performance.

• The article issued from this project (1st-authored) was published in Journal of Chemical Information and Modeling and selected as an “ACS Editors’ Choice”.

Teaching duty:

MOE software (2019 version): visualization, analysis and preparation of 3D structures (proteins, ligands); structural analysis of bioactive molecules and ligand-protein interactions; retrospective virtual screening based on pharmacophores and molecular docking.

Oct 2017 – Sep 2020: Contractual PhD Student

Laboratory of Therapeutic Innovations (UMR 7200), Faculty of Pharmacy, University of Strasbourg, France

Research project: Development of unbiased data sets and new methods for virtual screening

Project overview:

• A new structure-based virtual screening workflow was established: this workflow involved cavity-based pharmacophore generation using the IChem toolkit, pharmacophore-based molecular alignment and pose selection using OpenEye and Szybki; the workflow was evaluated in terms of ligand posing accuracy and virtual screening performance.

• A new unbiased pharmaco-chemical database called LIT-PCBA was designed, based on data retrieved from PubChem and Protein Data Bank (small-molecule structures and X-ray 3D protein structures).

• Diverse molecular modeling/cheminformatics programs were used: MOE, Sybyl (structure visualization), Pipeline Pilot (data-processing and 2D similarity search), Surflex-Dock (docking), ROCS from OpenEye (3D similarity search), AVE (data-unbiasing).

• Bash scripts were written to execute the jobs.

• Three articles issued from this project (all 1st-authored) were published in Journal of Chemical Information and Modeling (two) and International Journal of Molecular Sciences (one).

Teaching duty:

• LigandScout (version 4.3): creation, analysis and exploitation of ligand-based pharmacophores; retrospective virtual screening.

• ChemSketch and PyMOL: visualization, analysis and preparation of 2D and 3D structures (proteins, ligands).

• AutoDock Vina (version 1.1.2): retrospective virtual screening by molecular docking.

Jan 2017 – Jun 2017: Master’s Degree Intern

Department of Molecular Pharmaco-chemistry (UMR 5063), Grenoble Alpes University, France

Research project: In silico studies and organic synthesis of chalcone derivatives as inhibitors of the Cdr1p efflux pump involved in Candida albicans resistance to azoles

Project overview:

• Molecular docking (using GOLD, PLANTS) of several chalcone derivatives was carried out into putative ligand-binding sites of the CaCdr1p structure created by homology modeling.

• Synthesis of the chosen derivatives based on molecular docking results.

• A review article (1st-authored) on CaCdr1p inhibitors (structures and mechanisms of action) was published in Current Medicinal Chemistry.

 

SCIENTIFIC PUBLICATIONS (INTERNATIONAL PEER-REVIEWED JOURNALS)        

Full list here: https://scholar.google.fr/citations?user=y3ybMoAAAAAJ&hl=en

 

PRIZES & HONORS (SINCE THE DOCTORATE)

2024     Laureate of the SCT Award for Young Academic Investigator in Medicinal Chemistry – French Society of Medicinal Chemistry (SCT)

             Laureate of the Best Oral Presentation prize – Science Day of the Department of Life Sciences, Université Paris Cité

2022     Laureate of the Best Poster prize (Post-doctorate) – Young Researchers’ Conference of the ARC Foundation for Cancer Research

2021     Laureate of a PhD thesis prize awarded by the French Society of Cheminformatics

             Laureate of a PhD thesis prize awarded by the Foundation for Research in Chemistry

             First author of an “ACS Editors’ Choice” paper, American Chemical Society (ACS)

2020     Regional finalist (Grand Est) of the contest “Ma Thèse en 180 Secondes” (Three-Minute Thesis), 2020 edition

 

FUNDING

2021     Funding of the ARC Foundation for Cancer Research (Post-Doctoral Fellowship in France)

 

STUDENT SUPERVISION

Internship (co-)supervisor of four Master’s students (three M1 students and one M2 student) in 2023-2024

 

PERSONAL COMPETENCES

Languages            French: Level C2 of the CEFR (DALF C2, June 2019)

                              English: Level C2 of the CEFR (Certificate of Proficiency in English – CPE, June 2018)

Informatics           Cheminformatics/molecular modeling programs/tools: MOE, Sybyl, PyMOL, SeeSAR, Chimera, Open Babel, ChemAxon, Autodock Vina, Surflex-Dock, GOLD, PLANTS, LigandScout, Pipeline Pilot, KNIME

                              Programming languages: Bash, Python, R

 

OTHER ACTIVITIES

Feb 2025                           Member of the organizing committee for the 32nd Young Research Fellows Meeting of the French Society of Medicinal Chemistry (SCT)

Mar 2024 – present        Member of the admission board of the Erasmus Mundus Joint Master’s program “ChEMoinformatics+”

Sep 2019 – Aug 2021      Council member of the Laboratory of Therapeutic Innovations

Dec 2017 – present         Guest lecturer in Computer-Aided Drug Design, Faculty of Medicine-Pharmacy, Grenoble Alpes University, France

Oct 2017 – Sep 2018      Member of the Association of PhD Students and Doctors of Alsace