All in One: Cavity Detection, Druggability Estimate, Cavity-Based Pharmacophore Perception, and Virtual Screening. - Viet-Khoa Tran-Nguyen; Franck Da Silva; Guillaume Bret; Didier Rognan (J. Chem. Inf. Model., 2019)

LIT-PCBA: An Unbiased Data Set for Machine Learning and Virtual Screening. - Viet-Khoa Tran-Nguyen; Célien Jacquemard; Didier Rognan (J. Chem. Inf. Model., 2020)

True Accuracy of Fast Scoring Functions to Predict High-Throughput Screening Data from Docking Poses: The Simpler the Better. - Viet-Khoa Tran-Nguyen; Guillaume Bret; Didier Rognan (J. Chem. Inf. Model., 2021)

Beware of Simple Methods for Structure-Based Virtual Screening: The Critical Importance of Broader Comparisons. - Viet-Khoa Tran-Nguyen; Pedro J. Ballester (J. Chem. Inf. Model., 2023)

ClassyPose: A Machine-Learning Classification Model for Ligand Pose Selection Applied to Virtual Screening in Drug Discovery. - Viet-Khoa Tran-Nguyen; Anne-Claude Camproux; Olivier Taboureau (Adv. Intell. Syst., 2024)

Comprehensive machine learning boosts structure-based virtual screening for PARP1 inhibitors. - Klaudia Caba; Viet-Khoa Tran-Nguyen; Taufiq Rahman; Pedro J. Ballester (J. Cheminformatics, 2024)

Ligand-Based Drug Discovery Leveraging State-of-the-Art Machine Learning Methodologies Exemplified by Cdr1 Inhibitor Prediction. - The-Chuong Trinh; Pierre Falson; Viet-Khoa Tran-Nguyen; Ahcène Boumendjel (J. Chem. Inf. Model., 2025)

HERGAI: an artificial intelligence tool for structure-based prediction of hERG inhibitors. - Viet-Khoa Tran-Nguyen; Ulrick Fineddie Randriharimanamizara; Olivier Taboureau (J. Cheminformatics, 2025)