e-learning
Comparing ligand-binding site predictions across different protein structure modalities using SIMORGH
Abstract
Proteins are not static objects. They constantly move and change shape, and these conformational changes can be especially important when a ligand binds.
About This Material
This is a Hands-on Tutorial from the GTN which is usable either for individual self-study, or as a teaching material in a classroom.
Questions this will address
- How does the structural modality (Apo, Holo, or Predicted) affect ligand-binding site prediction?
- Can integrating protein dynamics improve binding site predictions across different modalities?
Learning Objectives
- Prepare and preprocess experimental and predicted protein structures for binding site prediction.
- Run SIMORGH to predict ligand-binding sites.
- Compare predictions using static structures versus dynamic structural ensembles.
Licence: Creative Commons Attribution 4.0 International
Keywords: Statistics and Machine Learning
Competency level: • Beginner
Target audience: Students
Resource type: e-learning
Version: 1
Status: Active
Learning objectives:
- Prepare and preprocess experimental and predicted protein structures for binding site prediction.
- Run SIMORGH to predict ligand-binding sites.
- Compare predictions using static structures versus dynamic structural ensembles.
Date modified: 2026-09-24
Date published: 2026-09-24
Authors: 
Amirhossein Naghsh Nilchi, Omid Mokhtari
Scientific topics: Statistics and probability
External resources:
Activity log
