Elliot Sicheri, Daniel Mao, Michael Tyers, Frank Sicheri
{"title":"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。","authors":"Elliot Sicheri, Daniel Mao, Michael Tyers, Frank Sicheri","doi":"10.1016/j.csbj.2025.09.012","DOIUrl":null,"url":null,"abstract":"<p><p>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 <sup>1</sup>. 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.</p>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"4026-4039"},"PeriodicalIF":4.1000,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12475580/pdf/","citationCount":"0","resultStr":"{\"title\":\"Analysis of Fbox substrate adapter proteins using <i>ProteoSync</i>, a program for projection of evolutionary conservation onto protein atomic coordinates.\",\"authors\":\"Elliot Sicheri, Daniel Mao, Michael Tyers, Frank Sicheri\",\"doi\":\"10.1016/j.csbj.2025.09.012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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 <sup>1</sup>. 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.</p>\",\"PeriodicalId\":10715,\"journal\":{\"name\":\"Computational and structural biotechnology journal\",\"volume\":\"27 \",\"pages\":\"4026-4039\"},\"PeriodicalIF\":4.1000,\"publicationDate\":\"2025-09-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12475580/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational and structural biotechnology journal\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1016/j.csbj.2025.09.012\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational and structural biotechnology journal","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.csbj.2025.09.012","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
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.
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