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SYNBIP: synthetic binding proteins for research, diagnosis and therapy.

Xiaona WangFengcheng LiWenqi QiuBinbin XuYanlin LiXichen LianHongyan YuZhao ZhangJianxin WangZhaorong LiWei Wei XueJian Zhang
Published in: Nucleic acids research (2021)
The success of protein engineering and design has extensively expanded the protein space, which presents a promising strategy for creating next-generation proteins of diverse functions. Among these proteins, the synthetic binding proteins (SBPs) are smaller, more stable, less immunogenic, and better of tissue penetration than others, which make the SBP-related data attracting extensive interest from worldwide scientists. However, no database has been developed to systematically provide the valuable information of SBPs yet. In this study, a database named 'Synthetic Binding Proteins for Research, Diagnosis, and Therapy (SYNBIP)' was thus introduced. This database is unique in (a) comprehensively describing thousands of SBPs from the perspectives of scaffolds, biophysical & functional properties, etc.; (b) panoramically illustrating the binding targets & the broad application of each SBP and (c) enabling a similarity search against the sequences of all SBPs and their binding targets. Since SBP is a human-made protein that has not been found in nature, the discovery of novel SBPs relied heavily on experimental protein engineering and could be greatly facilitated by in-silico studies (such as AI and computational modeling). Thus, the data provided in SYNBIP could lay a solid foundation for the future development of novel SBPs. The SYNBIP is accessible without login requirement at both official (https://idrblab.org/synbip/) and mirror (http://synbip.idrblab.net/) sites.
Keyphrases
  • binding protein
  • protein protein
  • amino acid
  • small molecule
  • endothelial cells
  • adverse drug
  • multidrug resistant
  • big data
  • stem cells
  • health information
  • machine learning
  • dna binding
  • deep learning
  • data analysis