NVIDIA 发布 RFD4-Proteina 蛋白质设计模型
原标题：Design Proteins with RFD4-Proteina Using Reward-Guided Inference-Time Search
AI 摘要
NVIDIA 与华盛顿大学蛋白质设计研究所联合发布开源模型 RFD4-Proteina，可同时设计蛋白质序列与全原子结构，并通过奖励引导的推理时搜索聚焦高潜力候选。该模型基于残基级潜在表示，采样步数从约400步降至60步，速度和内存效率优于 RFD3。教程以 PD-L1 为靶点演示设计蛋白结合体候选，并提供开源模型与 NIM 微服务两种使用方式。
正文节选
Protein design is a search problem. Choose amino acids for an eight-residue protein sequence and more than 25 billion combinations are possible. Choose amino acids for a 100-residue protein sequence and the number of possibilities exceeds the number of atoms in the observable universe. Somewhere in that space is a protein that opens a path to a new therapy. There are too many combinations to search exhaustively, so finding it depends on knowing where to look. RFD4-Proteina, an NVIDIA BioNeMo ope