Suppr超能文献

SCOWLP 更新:跨折叠的蛋白质-蛋白质、蛋白质-肽、蛋白质-聚糖和蛋白质-核酸相互作用的 3D 分类,以及基于结构的结合推断。

SCOWLP update: 3D classification of protein-protein, -peptide, -saccharide and -nucleic acid interactions, and structure-based binding inferences across folds.

机构信息

Structural Bioinformatics BIOTEC TU Dresden, Tatzberg 47-51 01037 Dresden, Germany.

出版信息

BMC Bioinformatics. 2011 Oct 13;12:398. doi: 10.1186/1471-2105-12-398.

Abstract

BACKGROUND

Protein interactions are essential for coordinating cellular functions. Proteomic studies have already elucidated a huge amount of protein-protein interactions that require detailed functional analysis. Understanding the structural basis of each individual interaction through their structural determination is necessary, yet an unfeasible task. Therefore, computational tools able to predict protein binding regions and recognition modes are required to rationalize putative molecular functions for proteins. With this aim, we previously created SCOWLP, a structural classification of protein binding regions at protein family level, based on the information obtained from high-resolution 3D protein-protein and protein-peptide complexes.

DESCRIPTION

We present here a new version of SCOWLP that has been enhanced by the inclusion of protein-nucleic acid and protein-saccharide interactions. SCOWLP takes interfacial solvent into account for a detailed characterization of protein interactions. In addition, the binding regions obtained per protein family have been enriched by the inclusion of predicted binding regions, which have been inferred from structurally related proteins across all existing folds. These inferences might become very useful to suggest novel recognition regions and compare structurally similar interfaces from different families.

CONCLUSIONS

The updated SCOWLP has new functionalities that allow both, detection and comparison of protein regions recognizing different types of ligands, which include other proteins, peptides, nucleic acids and saccharides, within a solvated environment. Currently, SCOWLP allows the analysis of predicted protein binding regions based on structure-based inferences across fold space. These predictions may have a unique potential in assisting protein docking, in providing insights into protein interaction networks, and in guiding rational engineering of protein ligands. The newly designed SCOWLP web application has an improved user-friendly interface that facilitates its usage, and is available at http://www.scowlp.org.

摘要

背景

蛋白质相互作用对于协调细胞功能至关重要。蛋白质组学研究已经阐明了大量的蛋白质-蛋白质相互作用,这些相互作用需要进行详细的功能分析。通过结构测定来理解每个相互作用的结构基础是必要的,但这是一项不可行的任务。因此,需要能够预测蛋白质结合区域和识别模式的计算工具,以合理推断蛋白质的潜在分子功能。基于此,我们之前创建了 SCOWLP,这是一种基于高分辨率 3D 蛋白质-蛋白质和蛋白质-肽复合物信息的蛋白质家族水平的蛋白质结合区域结构分类。

描述

我们在此介绍了 SCOWLP 的新版本,该版本通过纳入蛋白质-核酸和蛋白质-糖相互作用得到了增强。SCOWLP 考虑了界面溶剂,以对蛋白质相互作用进行详细描述。此外,每个蛋白质家族获得的结合区域通过纳入从所有现有折叠结构中推断出的预测结合区域进行了丰富。这些推断可能非常有助于提出新的识别区域,并比较来自不同家族的结构相似的界面。

结论

更新后的 SCOWLP 具有新的功能,可以在溶剂环境中检测和比较识别不同类型配体(包括其他蛋白质、肽、核酸和糖)的蛋白质区域。目前,SCOWLP 允许根据跨折叠空间的基于结构的推断分析预测的蛋白质结合区域。这些预测在辅助蛋白质对接、深入了解蛋白质相互作用网络以及指导蛋白质配体的合理工程设计方面可能具有独特的潜力。新设计的 SCOWLP 网络应用程序具有改进的用户友好界面,使其使用更加方便,可在 http://www.scowlp.org 上访问。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c491/3210135/68b9eeba14d1/1471-2105-12-398-1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验