XieResearchGroup/Physics-aware-Multiplex-GNN
Source code for "A universal framework for accurate and efficient geometric deep learning of molecular systems" (Nature Scientific Reports)
PAMNet helps scientists accurately predict properties of small molecules, determine 3D structures of RNA, and estimate how strongly proteins and drug-like molecules will bind. You input molecular data (like chemical structures or sequences), and it outputs predictions for specific properties or structures. This tool is for researchers in drug discovery, materials science, and structural biology who need precise computational modeling of molecular systems.
Use this if you need highly accurate and efficient predictions for molecular properties, RNA 3D structures, or protein-ligand binding affinities.
Not ideal if your primary focus is on other types of biomolecules or if you require predictions for properties not related to molecular geometry.
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23
Language
Python
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Last pushed
Nov 12, 2025
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0
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