2024
Generative Artificial Intelligence for Navigating Synthesizable Chemical Space
Wenhao Gao*, Shitong Luo*, Connor W. Coley (* equal contribution)
Preprint 2024
SynFormer, built upon the concept of ChemProjector, is a generative framework that ensures every generated molecule has a viable synthetic pathway.
Generative Artificial Intelligence for Navigating Synthesizable Chemical Space
Wenhao Gao*, Shitong Luo*, Connor W. Coley (* equal contribution)
Preprint 2024
SynFormer, built upon the concept of ChemProjector, is a generative framework that ensures every generated molecule has a viable synthetic pathway.
Projecting Molecules into Synthesizable Chemical Spaces
Shitong Luo*, Wenhao Gao*, Zuofan Wu*, Jian Peng, Connor W. Coley, Jianzhu Ma (* equal contribution)
International Conference on Machine Learning (ICML) 2024
ChemProjector "projects" any molecular graph into a new molecular representation called postfix notation of synthesis that guarantees synthesizability.
Projecting Molecules into Synthesizable Chemical Spaces
Shitong Luo*, Wenhao Gao*, Zuofan Wu*, Jian Peng, Connor W. Coley, Jianzhu Ma (* equal contribution)
International Conference on Machine Learning (ICML) 2024
ChemProjector "projects" any molecular graph into a new molecular representation called postfix notation of synthesis that guarantees synthesizability.
2023
Rotamer Density Estimator is an Unsupervised Learner of the Effect of Mutations on Protein-Protein Interaction
Shitong Luo, Yufeng Su, Zuofan Wu, Chenpeng Su, Jian Peng, Jianzhu Ma
International Conference on Learning Representations (ICLR) 2023
RDE estimates the distribution of amino acid side-chain conformations (rotamers), from which we can predict the effect of mutations on protein-protein interactions by comparing the entropy of the distributions.
Rotamer Density Estimator is an Unsupervised Learner of the Effect of Mutations on Protein-Protein Interaction
Shitong Luo, Yufeng Su, Zuofan Wu, Chenpeng Su, Jian Peng, Jianzhu Ma
International Conference on Learning Representations (ICLR) 2023
RDE estimates the distribution of amino acid side-chain conformations (rotamers), from which we can predict the effect of mutations on protein-protein interactions by comparing the entropy of the distributions.
Mutational Fitness Landscape of Human Influenza H3N2 Neuraminidase
Ruipeng Lei, Andrea Hernandez Garcia, Timothy J.C. Tan, Qi Wen Teo, Yiquan Wang, Xiwen Zhang, Shitong Luo, Satish K. Nair, Jian Peng, Nicholas C. Wu
Cell Reports 2023
Deep mutational scanning (DMS) of human influenza H3N2 neuraminidase head domain.
Mutational Fitness Landscape of Human Influenza H3N2 Neuraminidase
Ruipeng Lei, Andrea Hernandez Garcia, Timothy J.C. Tan, Qi Wen Teo, Yiquan Wang, Xiwen Zhang, Shitong Luo, Satish K. Nair, Jian Peng, Nicholas C. Wu
Cell Reports 2023
Deep mutational scanning (DMS) of human influenza H3N2 neuraminidase head domain.
2022
Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures
Shitong Luo, Yufeng Su, Xingang Peng, Sheng Wang, Jian Peng, Jianzhu Ma
Conference on Neural Information Processing Systems (NeurIPS) 2022
DiffAb is a diffusion model that can design new antibodies and optimize existing ones for antigen binding.
Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures
Shitong Luo, Yufeng Su, Xingang Peng, Sheng Wang, Jian Peng, Jianzhu Ma
Conference on Neural Information Processing Systems (NeurIPS) 2022
DiffAb is a diffusion model that can design new antibodies and optimize existing ones for antigen binding.
Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets
Xingang Peng, Shitong Luo, Jiaqi Guan, Qi Xie, Jian Peng, Jianzhu Ma
International Conference on Machine Learning (ICML) 2022
Pocket2Mol improves the efficiency and quality of our previous structure-based drug design model (Luo et al., NeurIPS'21) with equivariant graph neural networks.
Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets
Xingang Peng, Shitong Luo, Jiaqi Guan, Qi Xie, Jian Peng, Jianzhu Ma
International Conference on Machine Learning (ICML) 2022
Pocket2Mol improves the efficiency and quality of our previous structure-based drug design model (Luo et al., NeurIPS'21) with equivariant graph neural networks.
Deep Point Set Resampling via Gradient Fields
Haolan Chen, Bi'an Du, Shitong Luo, Wei Hu
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2022
A general framework for point cloud denoising, upsampling, and meshing built upon our previous work on score-based point cloud denoising (Luo and Hu, ICCV'21).
Deep Point Set Resampling via Gradient Fields
Haolan Chen, Bi'an Du, Shitong Luo, Wei Hu
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2022
A general framework for point cloud denoising, upsampling, and meshing built upon our previous work on score-based point cloud denoising (Luo and Hu, ICCV'21).
Equivariant Point Cloud Analysis via Learning Orientations for Message Passing
Shitong Luo*, Jiahan Li*, Jiaqi Guan*, Yufeng Su, Chaoran Cheng, Jian Peng, Jianzhu Ma (* equal contribution)
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2022 Oral
A neural network layer that learns local orientations for each point in a point cloud, enabling equivariant message passing for point cloud analysis.
Equivariant Point Cloud Analysis via Learning Orientations for Message Passing
Shitong Luo*, Jiahan Li*, Jiaqi Guan*, Yufeng Su, Chaoran Cheng, Jian Peng, Jianzhu Ma (* equal contribution)
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2022 Oral
A neural network layer that learns local orientations for each point in a point cloud, enabling equivariant message passing for point cloud analysis.
Deep Learning-Guided Optimization of Human Antibody Against SARS-CoV-2 Variants with Broad Neutralization
Sisi Shan*, Shitong Luo*, Ziqing Yang*, Junxian Hong*, Yufeng Su, Fan Ding, Lili Fu, Chenyu Li, Peng Chen, Jianzhu Ma, Xuanling Shi, Qi Zhang, Bonnie Berger, Linqi Zhang, Jian Peng (* equal contribution)
Proceedings of the National Academy of Sciences (PNAS) 2022
Optimizing antibodies against SARS-CoV-2 variants with geometric deep learning, experimentally validated.
Deep Learning-Guided Optimization of Human Antibody Against SARS-CoV-2 Variants with Broad Neutralization
Sisi Shan*, Shitong Luo*, Ziqing Yang*, Junxian Hong*, Yufeng Su, Fan Ding, Lili Fu, Chenyu Li, Peng Chen, Jianzhu Ma, Xuanling Shi, Qi Zhang, Bonnie Berger, Linqi Zhang, Jian Peng (* equal contribution)
Proceedings of the National Academy of Sciences (PNAS) 2022
Optimizing antibodies against SARS-CoV-2 variants with geometric deep learning, experimentally validated.
2021
A 3D Generative Model for Structure-Based Drug Design
Shitong Luo, Jiaqi Guan, Jianzhu Ma, Jian Peng
Conference on Neural Information Processing Systems (NeurIPS) 2021
Learning the distribution of atom occurence in protein binding pockets to generate 3D molecules.
A 3D Generative Model for Structure-Based Drug Design
Shitong Luo, Jiaqi Guan, Jianzhu Ma, Jian Peng
Conference on Neural Information Processing Systems (NeurIPS) 2021
Learning the distribution of atom occurence in protein binding pockets to generate 3D molecules.
EBM-Fold: Fully-Differentiable Protein Folding Powered by Energy-based Models
Jiaxiang Wu, Shitong Luo, Tao Shen, Haidong Lan, Sheng Wang, Junzhou Huang
Technical Report 2021
Applying our gradient field method (Shi*, Luo*, et al., ICML'21) to protein folding.
EBM-Fold: Fully-Differentiable Protein Folding Powered by Energy-based Models
Jiaxiang Wu, Shitong Luo, Tao Shen, Haidong Lan, Sheng Wang, Junzhou Huang
Technical Report 2021
Applying our gradient field method (Shi*, Luo*, et al., ICML'21) to protein folding.
Score-Based Point Cloud Denoising
Shitong Luo, Wei Hu
International Conference on Computer Vision (ICCV) 2021
Estimating the score of noisy point distributions for effective and robust point cloud denoising and beyond.
Score-Based Point Cloud Denoising
Shitong Luo, Wei Hu
International Conference on Computer Vision (ICCV) 2021
Estimating the score of noisy point distributions for effective and robust point cloud denoising and beyond.
Learning Gradient Fields for Molecular Conformation Generation
Chence Shi*, Shitong Luo*, Minkai Xu, Jian Tang (* equal contribution)
International Conference on Machine Learning (ICML) 2021 Oral
An equivariant score matching technique to generate molecular conformations.
Learning Gradient Fields for Molecular Conformation Generation
Chence Shi*, Shitong Luo*, Minkai Xu, Jian Tang (* equal contribution)
International Conference on Machine Learning (ICML) 2021 Oral
An equivariant score matching technique to generate molecular conformations.
Diffusion Probabilistic Models for 3D Point Cloud Generation
Shitong Luo, Wei Hu
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2021 Oral
Simply a diffusion model for 3D point cloud generation.
[Paper] [Code] [Suppl.(Corrected)] [Demo Created by S.H.] [Publication]
Diffusion Probabilistic Models for 3D Point Cloud Generation
Shitong Luo, Wei Hu
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2021 Oral
Simply a diffusion model for 3D point cloud generation.
[Paper] [Code] [Suppl.(Corrected)] [Demo Created by S.H.] [Publication]