A Multi-Modal AI/ML-based Framework for Protein Conformation Selection and Prediction in Drug Discovery Applications

This work presents an AI/ML-based multi-modal framework that integrates both global and local protein descriptors to classify binding and non-binding conformations more effectively, and demonstrates that integrating local and global structural perspectives significantly improves predictive accuracy and robustness.