Article

Advancing Ligand Binding Affinity Prediction with Cartesian Tensor-Based Deep Learning

2025-06-07

Abstract excerpt

0. We present PBCNet2.0, a cartesian tensor-based Siamese Neural Network for protein-ligand relative binding affinity prediction. Trained on 8.6 million protein-ligand complex structure pairs, PBCNet2.0 achieves zero-shot performance comparable to computationally intensive physics-based simulations. Our prioritization experiments show that PBCNet2.0 speeds up binding affinity optimization by 718% while reducing re...

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Literature Corpus work: 34288d59-fe68-5da0-852d-9abf8b87d5db
DOI: 10.1101/2025.06.04.657800

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