Latent-X：用于从头蛋白质结合物设计的原子级前沿模型
Latent-X: An Atom-level Frontier Model for De Novo Protein Binder Design
AI总结：
本文提出全原子蛋白质设计模型 Latent-X，可依据目标表位端到端生成结合物结构与序列，在肽和小型结合物实验中展现高命中率、高亲和力与结构多样性。
摘要：
传统药物发现依赖对数百万候选分子进行多轮筛选，成功率低，导致药物发现耗费大量时间和资源。为克服这一瓶颈，我们推出 Latent-X，这是一种全原子蛋白质设计模型，开启了精准 AI 设计的新范式。给定目标蛋白质表位，Latent-X 联合生成蛋白质结合物与目标的全原子结构和序列，直接建模对特异性结合至关重要的非共价相互作用。我们通过大量湿实验，在两种具有治疗相关性的模态上验证了其效果，每个目标仅测试30至100个设计。对于大环肽，Latent-X 在所有评估的基准目标上实现了超过90%的实验命中率。对于小型结合物，它针对所有评估的基准目标持续产生强效候选物，结合亲和力达到低纳摩尔和皮摩尔范围，可与已获批疗法相媲美，同时在哺乳动物展示中表现出高度特异性。在相同条件下与最先进模型 AlphaProteo、RFdiffusion 和 RFpeptides 的直接比较表明，Latent-X 生成的结合物具有更高的命中率和更好的结合亲和力，并且能够独特地创建结构多样的结合物，包括复杂的β-折叠折叠。其端到端流程比现有的多步骤计算管线快一个数量级。通过大幅提高从头设计的效率和成功率，Latent-X 代表了向一键式生物制剂发现迈出的重要一步，也是蛋白质工程师的宝贵工具。Latent-X 可在 https://platform.latentlabs.com 获取，使用户无需 AI 基础设施或编程即可可靠地生成从头结合物。
英文摘要：
Traditional drug discovery relies on rounds of screening millions of candidate molecules with low success rates, making drug discovery time and resource intensive. To overcome this screening bottleneck, we introduce Latent-X, an all-atom protein design model that enables a new paradigm of precision AI design. Given a target protein epitope, Latent-X jointly generates the all atom structure and sequence of the protein binder and target, directly modelling the non-covalent interactions essential for specific binding. We demonstrate its efficacy across two therapeutically relevant modalities through extensive wet lab experiments, testing as few as 30-100 designs per target. For macrocyclic peptides, Latent-X achieves experimental hit rates exceeding 90% on all evaluated benchmark targets. For mini-binders, it consistently produces potent candidates against all evaluated benchmark targets, with binding affinities reaching the low nanomolar and picomolar range - comparable to those of approved therapeutics - whilst also being highly specific in mammalian display. In direct comparisons with the state-of-the-art models AlphaProteo, RFdiffusion and RFpeptides under identical conditions demonstrates, Latent-X generates binders with higher hit rates and better binding affinities, and uniquely creates structurally diverse binders, including complex beta-sheet folds. Its end-to-end process is an order of magnitude faster than existing multi-step computational pipelines. By drastically improving the efficiency and success rate of de novo design, Latent-X represents a significant advance towards push-button biologics discovery and a valuable tool for protein engineers. Latent-X is available at https://platform.latentlabs.com, enabling users to reliably generate de novo binders without AI infrastructure or coding.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
