GigaScienceBioinformaticsPeer-reviewed journal article
NanoporeDB: A Structural Resource Of Multimeric Protein Nanopores In Single-Molecule Sensing
Yuqian LiuiD, Zidong SuiD, Wenzhen YangiD, Denghui LiiD, Jiawen ZhangiD, Yuning ZhangiD, Tao ZengiD, Yong ZhangiD, Yuxiang LiiD, Guangyi FaniD, Kailong MaiD, Shanshan LiuiD, Xun XuiD, Yuliang DongiD, Zongan WangiD
Abstract
Protein nanopores are essential molecular gateways in biology and have inspired transformative technologies in biosensing and single-molecule sequencing. While this technology has transformed genomics and biosensing, the discovery of novel nanopore scaffolds remains limited due to the scarcity of experimentally resolved pore structures. Here, we present NanoporeDB, an open-access structural resource comprising over 6,600 high-confidence multimeric models across four representative pore types. Candidate proteins were systematically mined from large-scale datasets, including the AlphaFold Protein Structure Database, UniRef90, and MGnify90, and assembled using AlphaFold-Multimer and AlphaFold3. We performed membrane embedding, pore axis annotation, and constriction profiling to enable functional interpretation. NanoporeDB features an interactive web interface with 3D visualization and quantitative metrics such as insertion depth, tilt angle, and pore geometry. This resource provides a structural foundation for advancing nanopore-based molecular sensing, precision diagnostics, and synthetic biology.
- assay: protein structure
- research focus: database / resource
- research focus: protein structure prediction
- approach: deep learning
- approach: statistical model
- Citations
- 2
- FWCI
- 3.41
- Field percentile
- top 12%
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