论文标题

Pronet DB:用于蛋白质表面特性表示和RNA结合曲线的蛋白质组数据库

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

论文作者

Wei, Junkang, Xiao, Jin, Chen, Siyuan, Zong, Licheng, Gao, Xin, Li, Yu

论文摘要

实验和预测的蛋白质结构数量以及更复杂的蛋白质结构的快速增长挑战了计算生物学中的使用者,以利用结构信息和蛋白质表面性能表示。最近,AlphaFold2发布了各种物种的综合蛋白质组,蛋白质表面性质表示在蛋白质 - 分子相互作用预测中起着至关重要的作用,例如蛋白质 - 蛋白质相互作用,蛋白质核酸相互作用和蛋白质化合物相互作用。在这里,我们提出了第一个综合数据库,即Pronet DB,该数据库包含了超过326,175个蛋白质结构的多种蛋白质表面表示和RNA结合景观,涵盖了16个模型有机体蛋白质组,来自Alphafold蛋白质结构数据库(Alphafold DB)和实验性验证的蛋白质结构(Protein Inspotient In Protein In Protein In Protein In In Protein Bank)(PDB)。对于每种蛋白质,我们提供了原始的蛋白质结构,表面性能表示,包括疏水性,电荷分布,氢键,相互作用的面和RNA结合景观,例如RNA结合位点和RNA结合偏好。为了直观地解释蛋白质表面特性表示和RNA结合景观,我们还整合了mol*和在线3D查看器,以可视化蛋白质表面上的表示。预先计算的功能可瞬时使用,并提高计算生物学的开发,包括分子机制探索,基于几何的药物发现和新型治疗学开发。现在可以在https://proj.cse.cuhk.edu.hk/aihlab/pronet/上获得该服务器。

The rapid growth in the number of experimental and predicted protein structures and more complicated protein structures challenge users in computational biology for utilizing the structural information and protein surface property representation. Recently, AlphaFold2 released the comprehensive proteome of various species, and protein surface property representation plays a crucial role in protein-molecule interaction prediction such as protein-protein interaction, protein-nucleic acid interaction, and protein-compound interaction. Here, we proposed the first comprehensive database, namely ProNet DB, which incorporates multiple protein surface representations and RNA-binding landscape for more than 326,175 protein structures covering 16 model organism proteomes from AlphaFold Protein Structure Database (AlphaFold DB) and experimentally validated protein structures deposited in Protein Data Bank (PDB). For each protein, we provided the original protein structure, surface property representation including hydrophobicity, charge distribution, hydrogen bond, interacting face, and RNA-binding landscape such as RNA binding sites and RNA binding preference. To interpret protein surface property representation and RNA binding landscape intuitively, we also integrate Mol* and Online 3D Viewer to visualize the representation on the protein surface. The pre-computed features are available for the users instantaneously and boost computational biology development including molecular mechanism exploration, geometry-based drug discovery and novel therapeutics development. The server is now available on https://proj.cse.cuhk.edu.hk/aihlab/pronet/.

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