研究人员假设随机噪声的自由扩散可以生成与复杂靶标形状匹配的结合分子，并在肿瘤坏死因子受体1（TNFR1）上测试了这一方法。
研究人员获得了具有低皮摩尔亲和力的设计，这些设计的特异性可以通过部分扩散完全转向其他家族成员。当以更高价态呈现时，这些设计在OX40和4-1BB上作为拮抗剂或超激动剂发挥作用。
能够为药理学重要靶标设计高亲和力和高特异性的拮抗剂和激动剂，预示着蛋白质设计的新时代即将来临，即：结合分子的设计将由计算生成，而非通过免疫接种或随机筛选的方法。
据悉，尽管在设计蛋白质结合蛋白方面取得了一定进展，但设计的结构与靶标的匹配度低于许多天然蛋白质复合物，且针对TNFR1和其他具有相对平坦和极性表面的，蛋白质靶标的设计工作未能成功。
附：英文原文
Title: Target-conditioned diffusion generates potent TNFR superfamily antagonists and agonists
Author: Matthias Glgl, Aditya Krishnakumar, Robert J. Ragotte, Inna Goreshnik, Brian Coventry, Asim K. Bera, Alex Kang, Emily Joyce, Green Ahn, Buwei Huang, Wei Yang, Wei Chen, Mariana Garcia Sanchez, Brian Koepnick, David Baker
Issue&Volume: 2024-12-06
Abstract: Despite progress in designing protein-binding proteins, the shape matching of designs to targets is lower than in many native protein complexes, and design efforts have failed for the tumor necrosis factor receptor 1 (TNFR1) and other protein targets with relatively flat and polar surfaces. We hypothesized that free diffusion from random noise could generate shape-matched binders for challenging targets and tested this approach on TNFR1. We obtain designs with low picomolar affinity whose specificity can be completely switched to other family members using partial diffusion. Designs function as antagonists or as superagonists when presented at higher valency for OX40 and 4-1BB. The ability to design high-affinity and high-specificity antagonists and agonists for pharmacologically important targets in silico presages a coming era in protein design in which binders are made by computation rather than immunization or random screening approaches.
DOI: adp1779
Source: https://www.science.org/doi/10.1126/science.adp1779