Zobrazeno 1 - 10
of 64
pro vyhledávání: '"Luo, ShiTong"'
Autor:
Li, Jiahan, Chen, Tong, Luo, Shitong, Cheng, Chaoran, Guan, Jiaqi, Guo, Ruihan, Wang, Sheng, Liu, Ge, Peng, Jian, Ma, Jianzhu
Peptides, short chains of amino acids, interact with target proteins, making them a unique class of protein-based therapeutics for treating human diseases. Recently, deep generative models have shown great promise in peptide generation. However, seve
Externí odkaz:
http://arxiv.org/abs/2411.18463
We introduce SynFormer, a generative modeling framework designed to efficiently explore and navigate synthesizable chemical space. Unlike traditional molecular generation approaches, we generate synthetic pathways for molecules to ensure that designs
Externí odkaz:
http://arxiv.org/abs/2410.03494
Autor:
Wu, Ruidong, Guo, Ruihan, Wang, Rui, Luo, Shitong, Xu, Yue, Li, Jiahan, Ma, Jianzhu, Liu, Qiang, Luo, Yunan, Peng, Jian
Despite the striking success of general protein folding models such as AlphaFold2(AF2, Jumper et al. (2021)), the accurate computational modeling of antibody-antigen complexes remains a challenging task. In this paper, we first analyze AF2's primary
Externí odkaz:
http://arxiv.org/abs/2407.01649
Discovering new drug molecules is a pivotal yet challenging process due to the near-infinitely large chemical space and notorious demands on time and resources. Numerous generative models have recently been introduced to accelerate the drug discovery
Externí odkaz:
http://arxiv.org/abs/2406.04628
Autor:
Li, Jiahan, Cheng, Chaoran, Wu, Zuofan, Guo, Ruihan, Luo, Shitong, Ren, Zhizhou, Peng, Jian, Ma, Jianzhu
Peptides, short chains of amino acid residues, play a vital role in numerous biological processes by interacting with other target molecules, offering substantial potential in drug discovery. In this work, we present PepFlow, the first multi-modal de
Externí odkaz:
http://arxiv.org/abs/2406.00735
Deep generative models have achieved tremendous success in designing novel drug molecules in recent years. A new thread of works have shown the great potential in advancing the specificity and success rate of in silico drug design by considering the
Externí odkaz:
http://arxiv.org/abs/2205.07249
Equivariance has been a long-standing concern in various fields ranging from computer vision to physical modeling. Most previous methods struggle with generality, simplicity, and expressiveness -- some are designed ad hoc for specific data types, som
Externí odkaz:
http://arxiv.org/abs/2203.14486
We study a fundamental problem in structure-based drug design -- generating molecules that bind to specific protein binding sites. While we have witnessed the great success of deep generative models in drug design, the existing methods are mostly str
Externí odkaz:
http://arxiv.org/abs/2203.10446
Autor:
Li, Jiahan, Luo, Shitong, Deng, Congyue, Cheng, Chaoran, Guan, Jiaqi, Guibas, Leonidas, Peng, Jian, Ma, Jianzhu
By folding to particular 3D structures, proteins play a key role in living beings. To learn meaningful representation from a protein structure for downstream tasks, not only the global backbone topology but the local fine-grained orientational relati
Externí odkaz:
http://arxiv.org/abs/2201.13299
3D point clouds acquired by scanning real-world objects or scenes have found a wide range of applications including immersive telepresence, autonomous driving, surveillance, etc. They are often perturbed by noise or suffer from low density, which obs
Externí odkaz:
http://arxiv.org/abs/2111.02045