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Updated: Jun 29, 2025
10:52
Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions
Published on: September 28, 2017
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ProNet DB: a proteome-wise database for protein surface property representations and RNA-binding profiles
Junkang Wei1, Jin Xiao1, Siyuan Chen2,3
1Department of Computer Science and Engineering (CSE), The Chinese University of Hong Kong (CUHK), Chung Chi Rd, Ma Liu Shui, Hong Kong SAR 999077, China.
Summary
ProNet DB is a new database integrating protein surface properties and RNA-binding landscapes for over 326,000 protein structures. This resource aids computational biology in predicting molecular interactions and drug discovery.
Area of Science:
- Computational Biology
- Structural Biology
- Bioinformatics
Background:
- The increasing number of protein structures presents challenges for computational biology.
- Accurate protein surface property representation is vital for predicting molecular interactions.
- AlphaFold2 has expanded the availability of protein structure data.
Purpose of the Study:
- To introduce ProNet DB, the first extensive database of integrated protein surface representations and RNA-binding landscapes.
- To provide a comprehensive resource for over 326,000 protein structures.
Main Methods:
- Integrated multiple protein surface representations (hydrophobicity, charge, hydrogen bonding).
- Included RNA-binding landscape data (sites and preferences).
- Utilized structures from AlphaFold Protein Structure Database and Protein Data Bank.
- Incorporated visualization tools (Mol*, Online 3D Viewer).
Main Results:
- ProNet DB offers access to 326,175 protein structures with detailed surface property and RNA-binding data.
- Pre-computed features allow for instantaneous user access.
- Interactive visualization tools facilitate intuitive interpretation.
Conclusions:
- ProNet DB significantly advances computational biology research.
- The database supports molecular mechanism elucidation, drug discovery, and therapeutic development.
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