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《科学》 第391卷 第6790期 · 2026年3月12日 · 中文解读

构象偏置突变计算设计以改变蛋白质功能

Computational design of conformation-biasing mutations to alter protein functions
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这篇讲什么
本文介绍了一种名为构象偏置(CB)的计算方法,利用逆折叠模型预测偏向目标构象状态的蛋白质变体,并在多种蛋白质上验证了其改善构象特异性功能的能力。
原文开头
Peter E. Cavanagh1†, Andrew G. Xue2†, Shizhong A. Dai3, Albert Qiang3, Tsutomu Matsui4, Alice Y. Ting3,5,6,7,8* Conformational biasing (CB) is a rapid and streamlined computational method that uses contrastive scoring by inverse folding models to predict protein variants biased toward desired conformational states. We successfully validated CB across seven diverse datasets, identifying variants of K-Ras, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein, the β2 adrenergic receptor, and Src kinase with improved conformation-specific functions such as enhanced binding or enzymatic activity. Applying CB to the enzyme lipoic acid ligase (LplA), we uncovered a previously unknown mechanism controlling its promiscuous activity. …
摘自《科学》(Science)第391卷 第6790期 · 2026年3月12日。仅引用开头一小段供了解文章,版权归原刊所有,全文请阅读原刊。
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