The-Chuong Trinh

The-Chuong Trinh

PhD student in Bioinformatics at the Gen&Chem lab (BGE). Pharmacist and Master's degree holder in BioHealth Engineering with expertise in applying ML/DL methodologies to Computer-Aided Drug Discovery.

MIL 3D-GNN for Cdr1 Inhibitor Screening

Ligand-Based Drug Discovery Leveraging State-of-the-Art Machine Learning Methodologies Exemplified by Cdr1 Inhibitor Prediction

This research represents my Master’s project focusing on overcoming multidrug resistance in fungal infections. We implemented a comprehensive ligand-based drug discovery pipeline.

Project Overview

Overcoming the challenge of multidrug resistance in fungal infections necessitates the discovery of novel Candida albicans drug resistance 1 (Cdr1) inhibitors. In this work, we explored advanced techniques including Multi-Instance Learning (MIL) 3D Graph Neural Networks (3D-GNN) alongside traditional machine learning methods to identify potent Cdr1 inhibitors. The methodology demonstrates how cutting-edge AI can be effectively applied to screen and discover novel therapeutics.

Key Highlights

  • Methodology: Applied MIL 3D-GNN to represent and predict molecular properties.
  • Application: Focused on screening and identifying novel Cdr1 inhibitors.
  • Publication: The methodology and results from this project have been published in the Journal of Chemical Information and Modeling (JCIM).