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AUTODIFF: Autoregressive Diffusion Modeling for Structure-based Drug Design

Structure-based drug design (SBDD), which aims to generate molecules that can bind tightly to the target protein, is an essential problem in drug discovery, and previous approaches have achieved initial success. However, most existing methods still suffer from invalid local structure or unrealistic conformation issues, which are mainly due to the poor learning of bond angles or torsional angles.

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Cite this as

Xinze Li, Penglei Wang, Tianfan Fu, Wenhao Gao, Chengtao Li, Leilei Shi, Junhong Liu (2024). Dataset: AUTODIFF: Autoregressive Diffusion Modeling for Structure-based Drug Design. https://doi.org/10.57702/p8fohpjv

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Additional Info

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Created December 2, 2024
Last update December 2, 2024
Defined In https://doi.org/10.48550/arXiv.2404.02003
Author Xinze Li
More Authors
Penglei Wang
Tianfan Fu
Wenhao Gao
Chengtao Li
Leilei Shi
Junhong Liu
Homepage https://arxiv.org/abs/2305.13997