Dithiane Based Boronic Acid as a Carbohydrate Sensor in an Aqueous Solution at pH 7.5: Theoretical and Experimental Approach

Revanna, Bhavya Nelligere; Mahendra, M.

doi:10.1007/s10895-021-02791-4

Cited by 6 publications

(7 citation statements)

References 52 publications

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“…Both boronic acids have similar selectivity trending toward monosaccharides, but 1TBA has one more aromatic ring structure, which may lead to additional spectral changes. [27,28] The reaction between boronic acids and glycans could trigger distinctive spectral changes, and the experimental spectra agreed with the simulation data calculated by the density functional theory (DFT). The glycan-boronic acid reactions influenced the charge distributions of the aromatic structures on the boronic acids; thus, 1TBA and 4MBA receptors offered different types of glycan binding spectra.…”

Section: Introductionsupporting

confidence: 72%

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Advancing Glycan Analysis: A New Platform Integrating SERS, Boronic Acids, and Machine Learning Algorithms

Kuai

Park

et al. 2023

Advanced Sensor Research

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Glycans are the most abundant fundamental biomolecules, but profiling glycans is challenging due to their structural complexity. To address this, a novel glycan detection platform is developed by integrating surface‐enhanced Raman spectroscopy (SERS), boronic acid receptors, and machine learning tools. Boronic acid receptors bind with glycans, and the reaction influences molecular vibrations, leading to unique Raman spectral patterns. Unlike prior studies that focus on designing a boronic acid with high binding selectivity toward a target glycan, this sensor is designed to analyze overall changes in spectral patterns using machine learning algorithms. For proof‐of‐concept, 4‐mercaptophenylboronic acid (4MBA) and 1‐thianthrenylboronic acid (1TBA) are used for glycan detection. The sensing platform successfully recognizes the stereoisomers and the structural isomers with different glycosidic linkages. The collective spectra that combine the spectra from both boronic acid receptors improve the performance of the support vector machine model due to the enrichment of the structural information of glycans. In addition, this new sensor could quantify the mole fraction of sialic acid in lactose background using the machine learning regression technique. This low‐cost, rapid, and highly accessible sensor will provide the scientific community with another option for frequent comparative glycan screening in standard biological laboratories.

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Section: Introductionsupporting

confidence: 72%

“…[ 59 ] The vibration modes were assigned using the literature values, and unknowns were estimated using VEDA. [ 12,13,27,31,60 ]…”

Section: Methodsmentioning

confidence: 99%

Advancing Glycan Analysis: A New Platform Integrating SERS, Boronic Acids, and Machine Learning Algorithms

Kuai

Park

et al. 2023

Advanced Sensor Research

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show abstract

“…In addition, the stereoisomer, glucose and mannose, could cause different charge distributions, leading to changes in Raman spectra. These findings correspond to the frontier molecular orbital (FMO) analysis done by Revanna et al 30 . For instance, DFT calculations show that the bindings of glucose and mannose with 1TBA could intensify the peak at 428 cm -1 (CCCC torsion and SCCC out of plane bending); moreover, 1TBA-glucose has a higher intensity at 421 cm -1 compared to 1TBA-mannose at 423 cm -1 .…”

Section: Comparison Of Experimental and Theoretical Spectrasupporting

confidence: 87%

“…Calculated Raman wavenumbers were calibrated based on the experimental data retrieved from NIST 29 . The vibration modes were assigned using the literature values, and unknowns were estimated using VEDA 12,13,[30][31][32] .…”

Section: Dft Theoretical Calculationsmentioning

confidence: 99%

Advancing Glycan Analysis: A New Platform Integrating SERS, Boronic Acids, and Machine Learning Algorithms

Kuai

Park

et al. 2023

Preprint

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Glycans are the most abundant and diverse fundamental biomolecules. Profiling glycans is essential to elucidate biomolecular mechanisms and to predict biological consequences; however, the analysis of glycans remains challenging due to their structural complexity. A novel glycan detection platform is established through the integration of surface-enhanced Raman spectroscopy (SERS), boronic acid receptors, and machine learning tools. SERS is able to distinguish isomeric structures and provide fingerprint information of molecules. Boronic acid receptors can selectively bind with glycans, and the reaction influences molecular vibrations, leading to unique Raman spectral patterns. For proof-of-concept, two boronic acids, 4-mercaptophenylboronic acid (4MBA) and 1-thianthrenylboronic acid (1TBA) were used for glycan detection. The spectra were analyzed by the machine learning algorithm. The sensing platform successfully recognized the stereoisomers (glucose, mannose, and galactose), the structural isomers with α-1,4 and α-1,6 glycosidic linkages, and the β-1,4 glycosidic linkage within lactose molecules. The collective spectra that combine the spectra from both boronic acid receptors could improve the performance of the support vector machine model due to the enrichment of the structural information of glycans. In addition to qualitative analysis, this new sensor could quantify the mole fraction of sialic acid in lactose background using the machine learning regression technique. The quantification accuracy reached a coefficient of determination (R2) value of 0.998 and a normalized mean square error (NMSE) of 0.00195. This low-cost, rapid, and highly accessible sensor will provide the scientific community with another option for frequent glycan screening in standard biological laboratories.

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“…The detection limit of BFMP to Zn 2+ was evaluated based on the titration profile according to the previously reported method. 68 The comparative uniqueness of the BFMP with the previously reported probes is depicted in Table S1 (ESI ‡).…”

Section: Fluorescence Binding Studiesmentioning

confidence: 99%

Highly selective and sensitive fluorescent “TURN-ON” furan-based Schiff base for zinc(ii) ion probing: chemical synthesis, DFT studies, and X-ray crystal structure

N. R.,

Revanasiddappa,

Yathirajan

et al. 2023

New J. Chem.

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Dithiane Based Boronic Acid as a Carbohydrate Sensor in an Aqueous Solution at pH 7.5: Theoretical and Experimental Approach

Cited by 6 publications

References 52 publications

Advancing Glycan Analysis: A New Platform Integrating SERS, Boronic Acids, and Machine Learning Algorithms

Advancing Glycan Analysis: A New Platform Integrating SERS, Boronic Acids, and Machine Learning Algorithms

Advancing Glycan Analysis: A New Platform Integrating SERS, Boronic Acids, and Machine Learning Algorithms

Highly selective and sensitive fluorescent “TURN-ON” furan-based Schiff base for zinc(ii) ion probing: chemical synthesis, DFT studies, and X-ray crystal structure

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