{"ID":2895794,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.08920","arxiv_id":"2507.08920","title":"AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model","abstract":"We introduce AMix-1, a powerful protein foundation model built on Bayesian Flow Networks and empowered by a systematic training methodology, encompassing pretraining scaling laws, emergent capability analysis, in-context learning mechanism, and test-time scaling algorithm. To guarantee robust scalability, we establish a predictive scaling law and reveal the progressive emergence of structural understanding via loss perspective, culminating in a strong 1.7-billion model. Building on this foundation, we devise a multiple sequence alignment (MSA)-based in-context learning strategy to unify protein design into a general framework, where AMix-1 recognizes deep evolutionary signals among MSAs and consistently generates structurally and functionally coherent proteins. This framework enables the successful design of a dramatically improved AmeR variant with an up to $50\\times$ activity increase over its wild type. Pushing the boundaries of protein engineering, we further empower AMix-1 with an evolutionary test-time scaling algorithm for in silico directed evolution that delivers substantial, scalable performance gains as verification budgets are intensified, laying the groundwork for next-generation lab-in-the-loop protein design.","short_abstract":"We introduce AMix-1, a powerful protein foundation model built on Bayesian Flow Networks and empowered by a systematic training methodology, encompassing pretraining scaling laws, emergent capability analysis, in-context learning mechanism, and test-time scaling algorithm. To guarantee robust scalability, we establish...","url_abs":"https://arxiv.org/abs/2507.08920","url_pdf":"https://arxiv.org/pdf/2507.08920v3","authors":"[\"Changze Lv\",\"Jiang Zhou\",\"Siyu Long\",\"Lihao Wang\",\"Jiangtao Feng\",\"Dongyu Xue\",\"Yu Pei\",\"Hao Wang\",\"Zherui Zhang\",\"Yuchen Cai\",\"Zhiqiang Gao\",\"Ziyuan Ma\",\"Jiakai Hu\",\"Chaochen Gao\",\"Jingjing Gong\",\"Yuxuan Song\",\"Shuyi Zhang\",\"Xiaoqing Zheng\",\"Deyi Xiong\",\"Lei Bai\",\"Wanli Ouyang\",\"Ya-Qin Zhang\",\"Wei-Ying Ma\",\"Bowen Zhou\",\"Hao Zhou\"]","published":"2025-07-11T17:02:25Z","proceeding":"q-bio.BM","tasks":"[\"q-bio.BM\",\"cs.AI\"]","methods":"[]","has_code":false}