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A New Spectral Shift-Based Method to Characterize Molecular Interactions.

ABSTRACT: There are many fluorescence-based applications that can be used to characterize molecular interactions. However, available methods often depend on site-specific labeling techniques or binding-induced changes in conformation or size of the probed target molecule. To overcome these limitations, we applied a ratiometric dual-emission approach that quantifies ligand-induced spectral shifts with sub-nanometer sensitivity. The use of environment-sensitive near-infrared dyes with the method we describe enables affinity measurements and thermodynamic characterization without the explicit need for site-specific labeling or ligand-induced conformational changes. We demonstrate that in-solution spectral shift measurements enable precise characterization of molecular interactions for a variety of biomolecules, including proteins, antibodies, and nucleic acids. Thereby, the described method is not limited to a subset of molecules since even the most challenging samples of research and drug discovery projects like membrane proteins and intrinsically disordered proteins can be analyzed.

SUBMITTER: Langer A

PROVIDER: S-EPMC8968852 | biostudies-literature | 2022 Feb-Mar

REPOSITORIES: biostudies-literature

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A New Spectral Shift-Based Method to Characterize Molecular Interactions.

Langer Andreas A Bartoschik Tanja T Cehlar Ondrej O Duhr Stefan S Baaske Philipp P Streicher Werner W

Assay and drug development technologies 20220215 2

There are many fluorescence-based applications that can be used to characterize molecular interactions. However, available methods often depend on site-specific labeling techniques or binding-induced changes in conformation or size of the probed target molecule. To overcome these limitations, we applied a ratiometric dual-emission approach that quantifies ligand-induced spectral shifts with sub-nanometer sensitivity. The use of environment-sensitive near-infrared dyes with the method we describe ...[more]

PMID: 35171002

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Project description:Polarimetric SAR (PolSAR) image segmentation is a key step in its interpretation. For the targets with time series changes, the single-temporal PolSAR image segmentation algorithm is difficult to provide correct segmentation results for its target recognition, time series analysis and other applications. For this, a new algorithm for multi-temporal PolSAR image segmentation is proposed in this paper. Firstly, the over-segmentation of single-temporal PolSAR images is carried out by the mean-shift algorithm, and the over-segmentation results of single-temporal PolSAR are combined to get the over-segmentation results of multi-temporal PolSAR images. Secondly, the edge detectors are constructed to extract the edge information of single-temporal PolSAR images and fuse them to get the edge fusion results of multi-temporal PolSAR images. Then, the similarity measurement matrix is constructed based on the over-segmentation results and edge fusion results of multi-temporal PolSAR images. Finally, the normalized cut criterion is used to complete the segmentation of multi-temporal PolSAR images. The performance of the proposed algorithm is verified based on three temporal PolSAR images of Radarsat-2, and compared with the segmentation algorithm of single-temporal PolSAR image. Experimental results revealed the following findings: (1) The proposed algorithm effectively realizes the segmentation of multi-temporal PolSAR images, and achieves ideal segmentation results. Moreover, the segmentation details are excellent, and the region consistency is good. The objects which can't be distinguished by the single-temporal PolSAR image segmentation algorithm can be segmented. (2) The segmentation accuracy of the proposed multi-temporal algorithm is up to 86.5%, which is significantly higher than that of the single-temporal PolSAR image segmentation algorithm. In general, the segmentation result of proposed algorithm is closer to the optimal segmentation. The optimal segmentation of farmland parcel objects to meet the needs of agricultural production is realized. This lays a good foundation for the further interpretation of multi-temporal PolSAR image.

Dataset Information

A New Spectral Shift-Based Method to Characterize Molecular Interactions.

Publications

A New Spectral Shift-Based Method to Characterize Molecular Interactions.

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