Figure 5
Salient feature maps of ligands during PLA-Net training stages. Salient feature maps predicted by the LM trained only on original molecules (LM), the LM trained with adversarial augmentations (LM \(+\) A), and the LM and PM jointly trained (LM \(+\) PM) for representative ligands of 7 protein targets. The average precision (AP) of each model is presented below their respective feature map and TLI-relevant substructures are shown to the left. All of these substructures have been previously identified through experimental and/or molecular docking analyses between the shown ligand and its respective target protein39,40,41,42,43,44. The predicted importance of ligand substructures significantly shifts at each training stage despite small changes in AP. The augmented LM achieves predictions that best align with substructures of natural ligands that have been previously reported to participate in TLIs. Created with BioRender.com.
