Suppr超能文献

通过窗口化多序列比对提高嵌合蛋白的预测准确性。

Improving prediction accuracy in chimeric proteins with windowed multiple sequence alignment.

作者信息

Vedula Sanketh, Bronstein Alex M, Marx Ailie

机构信息

Technion - Israel Institute of Technology, Haifa 32000, Israel.

Institute of Science and Technology Austria, Klosterneuberg 3400, Austria.

出版信息

Comput Struct Biotechnol J. 2025 Jul 23;27:3292-3298. doi: 10.1016/j.csbj.2025.07.039. eCollection 2025.

Abstract

A key step in protein structure prediction involves the detection of co-evolving pairs of residues, a signal for spatial proximity. This information is gleaned from multiple sequence alignment and underscores Alphafold's structure prediction for almost every known protein. A simple means to create proteins beyond those found in nature, is by unnaturally fusing together two known proteins or protein parts. Here we demonstrate that structured peptides are predicted with significantly reduced accuracy when added to the terminal ends of scaffold proteins. Appending the multiple sequence alignment for the individual peptide tags to that of the scaffold protein often restores prediction accuracy. This work suggests that this windowed multiple sequence alignment approach can be a useful tool for predicting the structure of fused, chimeric proteins.

摘要

蛋白质结构预测中的一个关键步骤涉及检测共同进化的残基对,这是空间接近性的一个信号。该信息从多序列比对中收集,并突出了AlphaFold对几乎所有已知蛋白质的结构预测。一种创造自然界中不存在的蛋白质的简单方法是将两种已知蛋白质或蛋白质部分非天然地融合在一起。在这里,我们证明,当将结构化肽添加到支架蛋白的末端时,预测准确性会显著降低。将单个肽标签的多序列比对附加到支架蛋白的多序列比对上,通常可以恢复预测准确性。这项工作表明,这种窗口化多序列比对方法可能是预测融合嵌合蛋白结构的有用工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f43/12328686/fc896e294ae5/ga1.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验