Combining AlphaFold 3 with microscale thermophoresis for aptamer optimisation
- 1Department of Molecular Biology, Institute of Biochemistry and Molecular Biology, Semmelweis University
Abstract
Although use of AI-based tools has gained ground in molecular biology research, their reliability remains a matter of debate. Here, we combined AlphaFold 3 modelling with microscale thermophoresis to investigate the interactions between glucan-binding protein C and the biofilm-inhibiting aptamer and its five derivatives. Structural modelling identified a binding motif on the aptamer and suggested a mechanism of action; however, the predictions were only partially supported by the experimental results. The AlphaFold generated confidence metrics did not correlate directly with the measured binding affinities, indicating that confidence scores can help identify plausible interaction interfaces, but they are not reliable predictors of binding strength. These results highlight the importance of integrating structural prediction with biophysical validation to dissect aptamer-protein recognition.
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BibTeX
@misc{harkai2026combining,
title = {{Combining AlphaFold 3 with microscale thermophoresis for aptamer optimisation}},
author = {A. Harkai and T. Meszaros},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.08.757587},
url = {https://www.biorxiv.org/content/10.64898/2026.10.08.757587v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Combining AlphaFold 3 with microscale thermophoresis for aptamer optimisation
AU - A. Harkai
AU - T. Meszaros
PY - 2026
DA - 2026/10/08
PB - bioRxiv
DO - 10.64898/2026.10.08.757587
UR - https://www.biorxiv.org/content/10.64898/2026.10.08.757587v1
AB - Although use of AI-based tools has gained ground in molecular biology research, their reliability remains a matter of debate. Here, we combined AlphaFold 3 modelling with microscale thermophoresis to investigate the interactions between glucan-binding protein C and the biofilm-inhibiting aptamer and its five derivatives. Structural modelling identified a binding motif on the aptamer and suggested a mechanism of action; however, the predictions were only partially supported by the experimental results. The AlphaFold generated confidence metrics did not correlate directly with the measured binding affinities, indicating that confidence scores can help identify plausible interaction interfaces, but they are not reliable predictors of binding strength. These results highlight the importance of integrating structural prediction with biophysical validation to dissect aptamer-protein recognition.
ER -