Visual-SELEX: A technology ensemble for evaluating aptamer structural similarity via 3D visual spatial conformational analysis
To date, the study of single-stranded DNA (ssDNA) similarity has focused mainly on the similarity of bases in the same position in the nucleic acid sequence. However, focusing only on the similarity of base sequences has limitations. This similarity evaluation considers only the one-dimensional simi...
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| Published in: | Journal of bioinformatics and computational biology Vol. 23; no. 4; p. 2550010 |
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| Main Author: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
Singapore
01.08.2025
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| Subjects: | |
| ISSN: | 1757-6334, 1757-6334 |
| Online Access: | Get more information |
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| Summary: | To date, the study of single-stranded DNA (ssDNA) similarity has focused mainly on the similarity of bases in the same position in the nucleic acid sequence. However, focusing only on the similarity of base sequences has limitations. This similarity evaluation considers only the one-dimensional similarity of ssDNA and cannot fully capture the three-dimensional (3D) structural consistency of aptamers for nucleic acids with 3D structures. Therefore, it is necessary to develop a program that can quickly and accurately evaluate the 3D spatial consistency of ssDNA. To this end, we designed a Visual-SELEX rapid response program, which uses a screening ssDNA sequence set enriched in the DKK1 protein for analysis. The program directly generates a stable 3D structure of ssDNA through coarse-grained simulation and molecular dynamics (MD) simulation, converts the structure into a point cloud model, and then analyzes the similarity of the spatial structure of ssDNA through point cloud model alignment and superposition. The analysis results show that Visual-SELEX can accurately match ssDNAs with dissimilar base fragments but similar 3D spatial structures, providing richer 3D spatial similarity information than sequence similarity comparison alone. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1757-6334 1757-6334 |
| DOI: | 10.1142/S0219720025500106 |