The effect of osmolyte sucrose on the stability and compaction of the folded and unfolded states of ribosomal protein S6 from Thermus thermophilus was analyzed. Confirming previous results obtained with sodium sulfate and trehalose, refolding stopped-flow measurements of S6 show that sucrose favors the conversion of the unfolded state ensemble to a highly compact structure (75% as compact as the folded state). This conversion occurs when the unfolded state is suddenly placed under native conditions and the compact state accumulates in a transient off-folding pathway. This effect of sucrose on the compaction of the unfolded state ensemble is counteracted by guanidinium hydrochloride. The compact state does not accumulate at higher guanidinium concentrations and the unfolded state ensemble does not display increased compaction in the presence of 6 M guanidinium as evaluated by collisional quenching of tryptophan fluorescence. In contrast, accessibility of the tryptophan residue of folded S6 above 1 M sucrose concentration decreased as a result of an increased compaction of the folded state. Unfolding stopped-flow measurements of S6 reflect this increased compaction of the folded state, but the unfolding pathway is not affected by sucrose. Compaction of folded and unfolded S6 induced by sucrose occurs under native conditions indicating that decreased protein conformational entropy significantly contributes to the mechanism of protein stabilization by osmolytes.
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Sensors (Basel)
January 2025
Department of Computer Science, Faculty of Sciences and Humanities Sciences, Majmaah University, Al Majmaah 11952, Saudi Arabia.
Impedance-based biosensing has emerged as a critical technology for high-sensitivity biomolecular detection, yet traditional approaches often rely on bulky, costly impedance analyzers, limiting their portability and usability in point-of-care applications. Addressing these limitations, this paper proposes an advanced biosensing system integrating a Silicon Nanowire Field-Effect Transistor (SiNW-FET) biosensor with a high-gain amplification circuit and a 1D Convolutional Neural Network (CNN) implemented on FPGA hardware. This attempt combines SiNW-FET biosensing technology with FPGA-implemented deep learning noise reduction, creating a compact system capable of real-time viral detection with minimal computational latency.
View Article and Find Full Text PDFInt J Mol Sci
December 2024
ACCESS Health International, 384 West Lane, Ridgefield, CT 06877, USA.
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View Article and Find Full Text PDFJ Chem Phys
January 2025
School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore 637551, Singapore.
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View Article and Find Full Text PDFNat Commun
January 2025
Interdisciplinary Life Sciences Graduate Programs, University of Texas at Austin, Austin, TX, 78712, USA.
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View Article and Find Full Text PDFJ Am Chem Soc
January 2025
Department of Chemistry, University of California, Berkeley, California 94720-1460, United States.
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