生成式AI如何助力蛋白质科学研究

Large-Scale Generative AI for Protein Modeling & DesignZaixiang ZhengByteDance Researchzhengzaixiang@bytedance.com
https://%%zhengzx-nlp.github.ioYSSNLP2024YSSNLP2024YSSNLP2024YSSNLP2024YSSNLP2024YSSNLP2024We’re doing Generative AI for Science at ByteDance ResearchProtein■Learning Harmonic Molecular Representations on Riemannian Manifold. In ICLR 2023■On Pre-training Language Model for Antibody. In ICLR 2023■Structure-informed Language Models Are Protein Designers. In ICML 2023 (oral)■Diffusion Language Models Are Versatile Protein Learners. In ICML 2024.■Protein Conformation Generation via Force-Guided SE(3) Diffusion Models. In ICML 2024. ■Antigen-Specific Antibody Design via Direct Energy-based Preference Optimization. preprint. 2024Small Molecule■Regularized Molecular Conformation Fields. In NeurIPS 2022■Zero-Shot 3D Drug Design by Sketching and Generating. In NeurIPS 2022■Diffusion Models with Decomposed Priors for Structure-Based Drug Design. In ICML 2023■DecompOpt: Controllable