使用ProteoSync分析Fbox底物适配器蛋白,这是一个将进化守恒投影到蛋白质原子坐标上的程序。

IF 4.1 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Computational and structural biotechnology journal Pub Date : 2025-09-11 eCollection Date: 2025-01-01 DOI:10.1016/j.csbj.2025.09.012
Elliot Sicheri, Daniel Mao, Michael Tyers, Frank Sicheri
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引用次数: 0

摘要

将守恒投影到蛋白质的三维结构表面是推断重要功能区域的有力方法。出于这个原因,我们创建了ProteoSync,这是一个Python程序,可以半自动化这个过程。该程序从一组不同的可选物种中创建一个带注释的同源物序列比对,并使氨基酸保护的快速投影到PyMOL 1中预测或已知的3D模型上。作为一个测试案例,我们使用ProteoSync分析了31个F-box蛋白的子集,这些蛋白是基于cul1的E3泛素连接酶大家族的底物识别亚基。我们正确地识别了11个F-box成员已知的衬底相互作用表面。我们还确定了16个其他成员可能的配体结合位点,从而证明了ProteoSync在发现保守的、功能相关的表面方面的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Fbox substrate adapter proteins using ProteoSync, a program for projection of evolutionary conservation onto protein atomic coordinates.

The projection of conservation onto the surface of a protein's 3D structure is a powerful way of inferring functionally important regions. For this reason, we created ProteoSync, a Python program that semi-automates the process. The program creates an annotated sequence alignment of orthologs from a diverse set of selectable species and enables the fast projection of amino acid conservation onto a predicted or known 3D model in PyMOL 1. As a test case, we used ProteoSync to analyze a subset of 31 F-box proteins, which function as substrate recognition subunits for a large family of Cul1-based E3 ubiquitin ligases. We correctly identified known substrate interaction surfaces for 11 F-box members with previously solved structures. We also identified likely ligand binding sites for 16 other members, thus demonstrating ProteoSync's utility for discovering conserved, functionally relevant surfaces.

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来源期刊
Computational and structural biotechnology journal
Computational and structural biotechnology journal Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
9.30
自引率
3.30%
发文量
540
审稿时长
6 weeks
期刊介绍: Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to: Structure and function of proteins, nucleic acids and other macromolecules Structure and function of multi-component complexes Protein folding, processing and degradation Enzymology Computational and structural studies of plant systems Microbial Informatics Genomics Proteomics Metabolomics Algorithms and Hypothesis in Bioinformatics Mathematical and Theoretical Biology Computational Chemistry and Drug Discovery Microscopy and Molecular Imaging Nanotechnology Systems and Synthetic Biology
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