2024
DOI: 10.1101/2024.06.26.600802
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RNA-ligand interaction scoring via data perturbation and augmentation modeling

Hongli Ma,
Letian Gao,
Yunfan Jin
et al.

Abstract: RNA-targeting drug discovery is undergoing an unprecedented revolution. Despite recent advances in this field, developing data-driven deep learning models remains challenging due to the limited availability of validated RNA-small molecule interactions and the scarcity of known RNA structures. In this context, we introduce RNAsmol, a novel sequence-based deep learning framework that incorporates data perturbation with augmentation, graph-based molecular feature representation and attention-based feature fusion … Show more

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