AI-guided discovery of natural pocket proteins for portable small-molecule sensing
- 1Huazhong university of science and technology
Abstract
Recognition-element development remains an important practical challenge in small-molecule biosensing. Here, we present DWCLASS, an AI-guided workflow that combines screening of natural pocket proteins, molecular dynamics simulations, experimental binding assessment, and portable metasurface plasmonic sensing. Using thiamine (vitamin B1, thiamine) and 25-hydroxyvitamin D3 [25(OH)D3] as model analytes, the workflow identified binding responses in 7 of 16 tested analyte-protein pairs (43.8%). Selected proteins were incorporated into a competitive MetaSPR assay with gold nanoparticle amplification and acoustic mixing. The portable device provided a 240 s measurement step for prepared samples. Serum LODs were 2.98 ppt for thiamine and 3.82 ppt for 25(OH)D. Preliminary measurements of human serum specimens were compared with commercial ELISA to explore performance in biological samples. This study establishes an integrated route from AI-assisted screening of natural proteins to portable assay development for two chemically distinct vitamin analytes. Applicability to additional targets and clinical reference accuracy remain to be established.
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BibTeX
@misc{huang2026aiguided,
title = {{AI-guided discovery of natural pocket proteins for portable small-molecule sensing}},
author = {L. Huang and Y. Yang and c. Jiang and h. fan and Y. Li and Y. Zhang and Y. Zhang and D. Li and H. Zhou and Y. Chen and W. Hu and J. Guan and X. Liu and C. Sun and G. L. Liu},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.22.760851},
url = {https://www.biorxiv.org/content/10.64898/2026.10.22.760851v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - AI-guided discovery of natural pocket proteins for portable small-molecule sensing
AU - L. Huang
AU - Y. Yang
AU - c. Jiang
AU - h. fan
AU - Y. Li
AU - Y. Zhang
AU - Y. Zhang
AU - D. Li
AU - H. Zhou
AU - Y. Chen
AU - W. Hu
AU - J. Guan
AU - X. Liu
AU - C. Sun
AU - G. L. Liu
PY - 2026
DA - 2026/10/22
PB - bioRxiv
DO - 10.64898/2026.10.22.760851
UR - https://www.biorxiv.org/content/10.64898/2026.10.22.760851v1
AB - Recognition-element development remains an important practical challenge in small-molecule biosensing. Here, we present DWCLASS, an AI-guided workflow that combines screening of natural pocket proteins, molecular dynamics simulations, experimental binding assessment, and portable metasurface plasmonic sensing. Using thiamine (vitamin B1, thiamine) and 25-hydroxyvitamin D3 [25(OH)D3] as model analytes, the workflow identified binding responses in 7 of 16 tested analyte-protein pairs (43.8%). Selected proteins were incorporated into a competitive MetaSPR assay with gold nanoparticle amplification and acoustic mixing. The portable device provided a 240 s measurement step for prepared samples. Serum LODs were 2.98 ppt for thiamine and 3.82 ppt for 25(OH)D. Preliminary measurements of human serum specimens were compared with commercial ELISA to explore performance in biological samples. This study establishes an integrated route from AI-assisted screening of natural proteins to portable assay development for two chemically distinct vitamin analytes. Applicability to additional targets and clinical reference accuracy remain to be established.
ER -