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O. Moultos

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Jun 2026

Evaluating Molecular Representations for Predicting Cyclodextrin-PFAS Binding Energy with Machine Learning: Domain Transfer and Data Limitations.

This study systematically compares molecular representations (Mordred, ECFP, ChemBERTa, UniMol2, etc.) across several machine learning architectures to predict CD-PFAS binding energies, demonstrating that molecular representation choice is critical for small-data host-guest binding prediction.

Cole Brzakala, O. Moultos, J. P. van der Hoek et al. · 1 citation