@article {70241, title = {Machine Learning Prediction of Analyte-Induced Fluorescence Perturbations in DNA-Functionalized Carbon Nanotubes}, journal = {Nano Letters}, year = {2026}, month = {2026 Jan 07}, abstract = {

Single-walled carbon nanotubes (SWCNTs) functionalized with single-stranded DNAs can function as near-infrared nanosensors for molecular analytes. However, predicting which analytes elicit strong optical responses for specific nanosensors remains challenging. We developed machine learning (ML) models to predict analyte-induced fluorescence changes in a DNA{\textendash}SWCNT dopamine nanosensor. Using a data set of 63 small molecules sampling chemical space around dopamine, we encoded analytes with RDKit fingerprints, with or without HOMO and LUMO energies, and applied principal component analysis to identify structural motifs associated with optical response strength. We trained support vector regression and classification models using two strategies: ensembles of 200 models and cross-validation. Regression models achieved mean\ R2\ values of 0.2{\textendash}0.4, with cross-validation outperforming ensembles, while classifiers reached mean F1 scores of \~{}0.8. Cross-validation performed best for predictions on a blind set of 21 molecules. These findings show that ML can capture structure{\textendash}response patterns in modest data sets and guide in silico DNA{\textendash}SWCNT nanosensor design.

}, doi = {10.1021/acs.nanolett.5c05206}, url = {https://doi.org/10.1021/acs.nanolett.5c05206}, author = {Chakraborty, Sayantani and Krasley, Andrew T. and Smith, Colby H. and Beyene, Abraham G. and Vukovi{\'c}, Lela} } @article {69747, title = {Molecular Determinants of Optical Modulation in ssDNA{\textendash}Carbon Nanotube Biosensors}, journal = {ACS Nano}, year = {2025}, month = {01/2025}, abstract = {

Most traditional optical biosensors operate through molecular recognition, where ligand binding causes conformational changes that lead to optical perturbations in the emitting motif. Optical sensors developed from single-stranded DNA-functionalized single-walled carbon nanotubes (ssDNA{\textendash}SWCNTs) have started to make useful contributions to biological research. However, the mechanisms underlying their function have remained poorly understood. In this study, we combine experimental and computational approaches to show that ligand binding alone is not sufficient for optical modulation in this class of synthetic biosensors. Instead, the optical response that occurs after ligand binding is highly dependent on the chemical properties of the ligands, resembling mechanisms seen in activity-based biosensors. Specifically, we show that in ssDNA{\textendash}SWCNT catecholamine sensors, the optical response correlates positively with the electron density on the aryl motif, even among ligands with similar ligand binding affinities. Importantly, despite the strong correlations with electrochemical properties, we find that catechol oxidation itself is not necessary to drive the sensor optical response. We discuss how these findings could serve as a framework for tuning the performance of existing sensors and guiding the development of new biosensors of this class.

}, doi = {10.1021/acsnano.4c13814}, url = {https://doi.org/10.1021/acsnano.4c13814}, author = {Krasley, Andrew T. and Chakraborty, Sayantani and Vukovi{\'c}, Lela and Beyene, Abraham G.} }