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
Estimating the effect of mutations (binding ΔΔG) on PPIs from a generative model for rotamers.
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
A diffusion-based "swiss army knife" model for targeted antibody design and optimization.
High-Resolution De Novo Structure Prediction From Primary Sequence
Ruidong Wu, Fan Ding, Rui Wang, Rui Shen, Xiwen Zhang, Shitong Luo, Chenpeng Su, Zuofan Wu, Qi Xie, Bonnie Berger, Jianzhu Ma, Jian Peng
Technical Report (bioRxiv) 2022
Protein structure prediction with protein language models.
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
Using equivariant graph neural networks to improve efficiency and molecule quality of our previous structure-based drug design model (Luo et al., NeurIPS'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
An extension to score-based point cloud denoising (Luo and Hu, ICCV'21). Applying gradient fields to denoising, upsampling, and meshing.
Equivariant Point Cloud Analysis via Learning Orientations for Message Passing
Shitong Luo*, Jiahan Li*, Jiaqi Guan*, Yufeng Su, Chaoran Cheng, Jian Peng, Jianzhu Ma (* indicates equal contribution)
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2022 Oral
Learning virtual orientations for each point. Projecting neighbor points to local orientations before aggregating information from them.
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 (* indicates equal contribution)
Proceedings of the National Academy of Sciences (PNAS) 2022
Spotting candidates with potentially better neuralization in silico using deep learning. Assaying the candidates in vitro in the wet-lab.
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
Generating 3D molecules for protein binding sites. Learning the distribution of atom occurence in the 3D space.
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 (arXiv) 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.
Learning Gradient Fields for Molecular Conformation Generation
Chence Shi*, Shitong Luo*, Minkai Xu, Jian Tang (* indicates equal contribution)
International Conference on Machine Learning (ICML) 2021 Oral / Long Talk
End-to-end conformation sampling; Equivariant score matching.
Diffusion Probabilistic Models for 3D Point Cloud Generation
Shitong Luo, Wei Hu
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2021 Oral Best Paper Candidate
Inspired by the diffusion process in non-equilibrium thermodynamics; Markov chain; Competitive performance in generation and auto-encoding.
[Paper] [Code] [Suppl.(Corrected)] [Demo Created by S.H.] [Proceedings]
2020
Differentiable Manifold Reconstruction for Point Cloud Denoising
Shitong Luo, Wei Hu
ACM International Conference on Multimedia (ACM MM) 2020 Oral
Neural network architecture for point cloud denoising; Surface-fitting; Downsample-upsample scheme; Robust against high noise.