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ProNet DB:一个基于蛋白质组的数据库,用于蛋白质表面性质表示和 RNA 结合特性。

ProNet DB: a proteome-wise database for protein surface property representations and RNA-binding profiles.

机构信息

Department of Computer Science and Engineering (CSE), The Chinese University of Hong Kong (CUHK), Chung Chi Rd, Ma Liu Shui, Hong Kong SAR 999077, China.

Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955, Kingdom of Saudi Arabia.

出版信息

Database (Oxford). 2024 Apr 1;2024. doi: 10.1093/database/baae012.

Abstract

The rapid growth in the number of experimental and predicted protein structures and more complicated protein structures poses a significant challenge for computational biology in leveraging structural information and accurate representation of protein surface properties. Recently, AlphaFold2 released the comprehensive proteomes of various species, and protein surface property representation plays a crucial role in protein-molecule interaction predictions, including those involving proteins, nucleic acids and compounds. Here, we proposed the first extensive database, namely ProNet DB, that integrates multiple protein surface representations and RNA-binding landscape for 326 175 protein structures. This collection encompasses the 16 model organism proteomes from the AlphaFold Protein Structure Database and experimentally validated structures from the Protein Data Bank. For each protein, ProNet DB provides access to the original protein structures along with the detailed surface property representations encompassing hydrophobicity, charge distribution and hydrogen bonding potential as well as interactive features such as the interacting face and RNA-binding sites and preferences. To facilitate an intuitive interpretation of these properties and the RNA-binding landscape, ProNet DB incorporates visualization tools like Mol* and an Online 3D Viewer, allowing for the direct observation and analysis of these representations on protein surfaces. The availability of pre-computed features enables instantaneous access for users, significantly advancing computational biology research in areas such as molecular mechanism elucidation, geometry-based drug discovery and the development of novel therapeutic approaches. Database URL:  https://proj.cse.cuhk.edu.hk/aihlab/pronet/.

摘要

蛋白质结构实验和预测数量的快速增长,以及更复杂的蛋白质结构,给计算生物学利用结构信息和准确表示蛋白质表面特性带来了重大挑战。最近,AlphaFold2 发布了各种物种的综合蛋白质组,蛋白质表面特性的表示在蛋白质-分子相互作用预测中起着至关重要的作用,包括涉及蛋白质、核酸和化合物的相互作用预测。在这里,我们提出了第一个广泛的数据库,即 ProNet DB,它集成了多种蛋白质表面表示和 RNA 结合景观,涵盖了 326175 个蛋白质结构。该集合包括来自 AlphaFold 蛋白质结构数据库的 16 个模式生物蛋白质组和来自蛋白质数据库的实验验证结构。对于每个蛋白质,ProNet DB 提供了对原始蛋白质结构的访问,以及详细的表面特性表示,包括疏水性、电荷分布和氢键潜力,以及交互特征,如相互作用面和 RNA 结合位点和偏好。为了方便直观地解释这些特性和 RNA 结合景观,ProNet DB 整合了 Mol*和在线 3D 查看器等可视化工具,允许在蛋白质表面上直接观察和分析这些表示。预计算特征的可用性为用户提供了即时访问,极大地推动了计算生物学在分子机制阐明、基于几何的药物发现和新型治疗方法开发等领域的研究。数据库网址:https://proj.cse.cuhk.edu.hk/aihlab/pronet/。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6cdd/10984565/34a71b902f61/baae012f1.jpg

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