PUBLICATIONS
Selected publications
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Cross-modal graph contrastive learning with cellular images
Constructing discriminative representations of molecules lies at the core of a number of domains such as drug discovery, chemistry, and medicine. Here, we propose to assist the learning of molecular representation by using the perturbed high-content cell microscopy images at the phenotypic level. To incorporate the cross-modal pre-training, a unified framework, MIGA, is constructed to align them through multiple types of contrastive loss functions, which is proven effective in the formulated novel tasks to retrieve the molecules and corresponding images mutually.
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Predicting ligand-specific protein-ligand complex structure with a deep equivariant generative model
Understanding protein function requires considering their dynamic nature, which traditional rigid docking methods overlook. Molecular dynamics simulations are accurate but computationally intensive. We introduce DynamicBind, a deep learning method using equivariant geometric diffusion networks to facilitate efficient transitions between protein equilibrium states. DynamicBind accurately predicts ligand-specific conformations from unbound protein structures without needing holo-structures, showing state-of-the-art performance in docking and virtual screening.
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Accelerated rational PROTAC design via deep generative models
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Deep learning driven biosynthetic pathways navigation for natural products
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Predicting drug–protein interaction using quasi-visual question answering system
2024
Mei Li, Xiaoguang Liu, Hua Ji, Shuangjia Zheng*, Causal Subgraph Learning for Generalizable Inductive Relation Prediction. KDD, 2024.[Link][PDF]
Chenqing Hua, Bozitao Zhong, Sitao Luan, Liang Hong, Guy Wolf, Doina Precup, Shuangjia Zheng*, Reactzyme: A Benchmark for Enzyme-Reaction Prediction. NeurIPS, 2024.[Link][PDF]
Xiaoyi Liu, Chengwei Ai, Hongpeng Yang, Ruihan Dong, Jijun Tang, Shuangjia Zheng*, Fei Guo*. RetroCaptioner: beyond attention in end-to-end retrosynthesis transformer via contrastively captioned learnable graph representation. Bioinformatics, 2024.[Link][PDF]
Shuangjia Zheng*, Jiahua Rao, Jixian Zhang, Lianyu Zhou, Jiancong Xie, Ethan Cohen, Wei Lu, Chengtao Li, Yuedong Yang. Cross‐Modal Graph Contrastive Learning with Cellular Images. Advanced Science, 2024.[Link][PDF]
Tao Zeng, Zhehao Jin, Shuangjia Zheng, Tao Yu, Ruibo Wu, Developing BioNavi for Hybrid Retrosynthesis Planning. JACS Au, 2024.[Link][PDF]
Jiahua Rao, Jiancong Xie, Qianmu Yuan, Deqin Liu, Zhen Wang, Yutong Lu, Shuangjia Zheng*, Yuedong Yang*, A variational expectation-maximization framework for balanced multi-scale learning of protein and drug interactions. Nature Communications, 2024.[Link][PDF]
Jiancong Xie, Yi Wang, Jiahua Rao, Shuangjia Zheng*, Yuedong Yang*, Self-Supervised Contrastive Molecular Representation Learning with a Chemical Synthesis Knowledge Graph. Journal of Chemical Information and Modeling, 2024. [Link][PDF]
Jiahua Rao, Jiancong Xie, Hanjing Lin, Shuangjia Zheng, Zhen Wang, Yuedong Yang, Incorporating Retrieval-based Causal Learning with Information Bottlenecks for Interpretable Graph Neural Networks. arXiv, 2024. [Link][PDF]
Chenqing Hua, Connor Coley, Guy Wolf, Doina Precup, Shuangjia Zheng*, Effective Protein-Protein Interaction Exploration with PPIretrieval. arXiv, 2024.[Link][PDF]
Wei Lu, Jixian Zhang, Weifeng Huang, Ziqiao Zhang, Xiangyu Jia, Zhenyu Wang, Leilei Shi, Chengtao Li, Peter G Wolynes, Shuangjia Zheng*, DynamicBind: predicting ligand-specific protein-ligand complex structure with a deep equivariant generative model. Nature Communications, 2024.[Link][PDF]
Wei Lu, Jixian Zhang, Jihua Rao, Zhongyue Zhang, Shuangjia Zheng*. AlphaFold3, a secret sauce for predicting mutational effects on protein-protein interactions. bioRxiv, 2024.[Link][PDF]
Before 2023
Deqin Liu, Sheng Chen, Shuangjia Zheng, Sen Zhang, Yuedong Yang. SE (3) Equivalent Graph Attention Network as an Energy-Based Model for Protein Side Chain Conformation. in 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 2023. IEEE.[Link][PDF]
Jingbang Chen, Yian Wang, Xingwei Qu, Shuangjia Zheng, Yaodong Yang, Hao Dong, Jie Fu, Mixup-Augmented Meta-Learning for Sample-Efficient Fine-Tuning of Protein Simulators. arXiv preprint 2023.[Link][PDF]
Jiahua Rao, Chengtao Li, Jixian Zhang, Yuedong Yang, Lianyu Zhou, Ethan Cohen, Wei Lu, Shuangjia Zheng,Cross-modal Graph Contrastive Learning with Cellular Images. Advanced Science, 2022.[Link][PDF]
Jiahua Rao, Shuangjia Zheng, Yuedong Yang, Integrating supercomputing and artificial intelligence for life science. Patterns, 2022.[Link][PDF]
Jiahua Rao, Shuangjia Zheng, Yutong Lu, Yuedong Yang,Quantitative evaluation of explainable graph neural networks for molecular property prediction. Patterns, 2022.[Link][PDF]
Youhai Tan, Lingxue Dai, Weifeng Huang, Yinfeng Guo, Shuangjia Zheng, Jinping Lei, Hongming Chen, Yuedong Yang,Drlinker: Deep reinforcement learning for optimization in fragment linking design. Journal of Chemical Information and Modeling, 2022. [Link][PDF]
Yi Wang, Shuangjia Zheng, Jiahua Rao, Yunan Luo, Yuedong Yang, ReaKE: Contrastive Molecular Representation Learning with Chemical Synthetic Knowledge Graph. Journal of Chemical Information and Modeling, 2022.[Link][PDF]
Shuangjia Zheng, Youhai Tan, Zhenyu Wang, Chengtao Li, Zhiqing Zhang, Xu Sang, Hongming Chen, Yuedong Yang, Accelerated rational PROTAC design via deep learning and molecular simulations. Nature Machine Intelligence, 2022.[Link][PDF]
Sijie Mai, Shuangjia Zheng, Ya Sun, Ying Zeng, Yuedong Yang, Haifeng Hu, Dynamic graph dropout for subgraph-based relation prediction. Knowledge-Based Systems, 2022.[Link][PDF]
Shuangjia Zheng, Tao Zeng, Chengtao Li, Binghong Chen, Connor W Coley, Yuedong Yang, Ruibo Wu, Deep learning driven biosynthetic pathways navigation for natural products with BioNavi-NP. Nature Communications, 2022.[Link][PDF]
Jiahua Rao, Shuangjia Zheng, Sijie Mai, Yuedong Yang, Communicative subgraph representation learning for multi-relational inductive drug-gene interaction prediction. IJCAI 2022.[Link][PDF]
Sijie Mai, Ying Zeng, Shuangjia Zheng, Haifeng Hu, Hybrid contrastive learning of tri-modal representation for multimodal sentiment analysis. IEEE Transactions on Affective Computing, 2022.[Link][PDF]
Qianmu Yuan, Sheng Chen, Jiahua Rao, Shuangjia Zheng, Huiying Zhao, Yuedong Yang, AlphaFold2-aware protein–DNA binding site prediction using graph transformer. Briefings in bioinformatics, 2022.[Link][PDF]
Penglei Wang, Shuangjia Zheng, Yize Jiang, Chengtao Li, Junhong Liu, Chang Wen, Atanas Patronov, Dahong Qian, Hongming Chen, Yuedong Yang, Structure-aware multimodal deep learning for drug–protein interaction prediction. Journal of chemical information and modeling, 2022.[Link][PDF]
Wei Lu, Qifeng Wu, Jixian Zhang, Jiahua Rao, Chengtao Li, Shuangjia Zheng, Tankbind: Trigonometry-aware neural networks for drug-protein binding structure prediction. Advances in neural information processing systems, 2022.[Link][PDF]
Xie, C., X.-X. Zhuang, Z. Niu, R. Ai, S. Lautrup, S. Zheng, Y. Jiang, R. Han, T.S. Gupta, and S. Cao, Amelioration of Alzheimer’s disease pathology by mitophagy inducers identified via machine learning and a cross-species workflow. Nature Biomedical Engineering, 2022.[Link][PDF]
Jianzhao Gao, Shuangjia Zheng, Mengting Yao, Peikun Wu, Precise estimation of residue relative solvent accessible area from Cα atom distance matrix using a deep learning method. Bioinformatics, 2022.[Link][PDF]
Shuangjia Zheng, Ying Song, Zhang Pan, Chengtao Li, Le Song, Yuedong Yang, Molecular Attributes Transfer from Non-Parallel Data. arXiv preprint 2021.[Link]
Lizhao Hu, Yuyao Yang, Shuangjia Zheng, Jun Xu, Ting Ran, Hongming Chen, Kinase inhibitor scaffold hopping with deep learning approaches. Journal of Chemical Information and Modeling, 2021.[Link]
Shuangjia Zheng, Zengrong Lei, Haitao Ai, Hongming Chen, Daiguo Deng, Yuedong Yang, Deep scaffold hopping with multimodal transformer neural networks. Journal of cheminformatics, 2021.[Link]
Shuangjia Zheng, Sijie Mai, Ya Sun, Haifeng Hu, Yuedong Yang, Subgraph-aware few-shot inductive link prediction via meta-learning. IEEE Transactions on Knowledge and Data Engineering, 2022.[Link]
Jianwen Chen✝, Shuangjia Zheng✝, Ying Song, Jiahua Rao, Yuedong Yang, Learning attributed graph representations with communicative message passing transformer. IJCAI 2021.[Link]
Shuangjia Zheng, Jiahua Rao, Ying Song, Jixian Zhang, Xianglu Xiao, Evandro Fei Fang, Yuedong Yang, Zhangming Niu, PharmKG: a dedicated knowledge graph benchmark for bomedical data mining. Briefings in bioinformatics, 2021.[Link]
Shuangjia Zheng, Tao Zeng, Chengtao Li, Binghong Chen, Connor W Coley, Yuedong Yang, Ruibo Wu, BioNavi-NP: Biosynthesis Navigator for Natural Products. Nature Communications 2021.[Link]
Jiahao Wang, Shuangjia Zheng, Jianwen Chen, Yuedong Yang, Meta learning for low-resource molecular optimization. Journal of Chemical Information and Modeling, 2021.[Link]
Ying Song*, Shuangjia Zheng*, Liang Li, Xiang Zhang, Xiaodong Zhang, Ziwang Huang, Jianwen Chen, Huiying Zhao, Yusheng Jie, Ruixuan Wang, Yutian Chong, Jun Shen, Yunfei Zha, Yuedong Yang, Deep learning enables accurate diagnosis of novel coronavirus (COVID-19) with CT images. IEEE/ACM transactions on computational biology and bioinformatics, 2021.[Link]
Jiahua Rao, Shuangjia Zheng, Ying Song, Jianwen Chen, Chengtao Li, Jiancong Xie, Hui Yang, Hongming Chen, Yuedong Yang, MolRep: A deep representation learning library for molecular property prediction. bioRxiv, 2021.[Link]
Zhihong Liu, Dane Huang, Shuangjia Zheng, Ying Song, Bingdong Liu, Jingyuan Sun, Zhangming Niu, Qiong Gu, Jun Xu, Liwei Xie, Deep learning enables discovery of highly potent anti-osteoporosis natural products. European Journal of Medicinal Chemistry, 2021.[Link]
Pan Zhang, Shuangjia Zheng, Jianwen Chen, Yaoqi Zhou, Yuedong Yang. DeepANIS: Predicting antibody paratope from concatenated CDR sequences by integrating bidirectional long-short-term memory and transformer neural networks. in 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 2021. IEEE.[Link]
Sijie Mai*, Shuangjia Zheng*, Yuedong Yang, Haifeng Hu. Communicative message passing for inductive relation reasoning. in Proceedings of the AAAI Conference on Artificial Intelligence. 2021.[Link]
Shimin Su, Yuyao Yang, Hanlin Gan, Shuangjia Zheng, Fenglong Gu, Chao Zhao, Jun Xu, Predicting the feasibility of copper (i)-catalyzed alkyne–azide cycloaddition reactions using a recurrent neural network with a self-attention mechanism. Journal of Chemical Information and Modeling, 2020.[Link]
Shuangjia Zheng, Yongjian Li, Sheng Chen, Jun Xu, Yuedong Yang, Predicting drug–protein interaction using quasi-visual question answering system. Nature Machine Intelligence, 2020.[Link]
Chaochao Yan, Qianggang Ding, Peilin Zhao, Shuangjia Zheng, Jinyu Yang, Yang Yu, Junzhou Huang, Retroxpert: Decompose retrosynthesis prediction like a chemist. Advances in Neural Information Processing Systems, 2020.[Link]
Ying Song*, Shuangjia Zheng*, Zhangming Niu, Zhang-Hua Fu, Yutong Lu, Yuedong Yang. Communicative Representation Learning on Attributed Molecular Graphs. IJCAI. 2020.[Link]
Jianwen Chen*, Shuangjia Zheng*, Huiying Zhao, Yuedong Yang, Structure-aware protein solubility prediction from sequence through graph convolutional network and predicted contact map. Journal of cheminformatics, 2021.[Link]
Yuyao Yang*, Shuangjia Zheng*, Shimin Su, Chao Zhao, Jun Xu, Hongming Chen, SyntaLinker: automatic fragment linking with deep conditional transformer neural networks. Chemical science, 2020.[Link]
Zhe Sun, Shuangjia Zheng, Huiying Zhao, Zhangming Niu, Yutong Lu, Yi Pan, Yuedong Yang, To improve prediction of binding residues with DNA, RNA, carbohydrate, and peptide via multi-task deep neural networks. IEEE/ACM transactions on computational biology and bioinformatics, 2021.[Link]
Shuangjia Zheng, Jiahua Rao, Zhongyue Zhang, Jun Xu, Yuedong Yang, Predicting retrosynthetic reactions using self-corrected transformer neural networks. Journal of chemical information and modeling, 2019.[Link]
Shuangjia Zheng, Xin Yan, Qiong Gu, Yuedong Yang, Yunfei Du, Yutong Lu, Jun Xu, QBMG: quasi-biogenic molecule generator with deep recurrent neural network. Journal of cheminformatics, 2019.[Link]
Shuangjia Zheng, Xin Yan, Yuedong Yang, Jun Xu, Identifying structure–property relationships through smiles syntax analysis with self-attention mechanism. Journal of chemical information and modeling, 2019.[Link]